Office Action 3: Final Rejection (2024-04-17)
Rejection types: 101 - Patent-Eligible Subject Matter, 103 - Obviousness, 112 - Written Description/Enablement

CLAIMS:
AMENDMENTS TO THE CLAIMS

The following listing of claims will replace all previous versions and listings of claims:

Listing of Claims

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1\. (Currently Amended) A wearable fetal health monitoring device for determining a health \[\[heath\]\] condition of a fetus based on biosignals of an expecting mother and the fetus, the wearable fetal health monitoring device comprising:a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso a- ;
an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data \[\[value\]\] from a second location on the maternal torso ;
a securing device configured to provide skin contact of the passive sensor and the optical sensor to the maternal torso for continuous non-invasive non-clinical monitoring;
 and
a microcontroller configured for \[\[to\]\]:
SVG {EMBED HERE} 0.432.067monitoring fetal movement (fM) using the passive sensor while operating in a first mode, wherein the first mode is a reduced power mode; and
upon detecting reduced fM activity, transitioning to a second mode comprising:decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract \[\[a\]\] mechano-acoustically sensed fetal phonocardiogram (fPCG) data \[\[value\]\];
determining fetal heart rate variability (fHRV) data from the mechano- acoustically sensed fPCG data; and providing an alert to the expecting mother based on the fHRV data.

2\. (Canceled)

3\. (Canceled)

4\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein the microcontroller is further configured to calculate \[\[a\]\] fetal movement (fM)data \[\[value\]\] from the mechano-acoustically sensed aPCG data .

5\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein:the optical sensor is further configured to sense \[\[a\]\] maternal peripheral capillary oxygen saturation (mSpO2) data \[\[value\]\], and
transitioning to the second mode is further based upon detecting reduced mSpO2 data.
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6\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein the passive sensor comprises at least one of an acoustic wave sensor and a pressure wave sensor.

7\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein the microcontroller is further configured to calculate a maternal activity level from the optical sensor .

8\. (Currently Amended) The wearable fetal health monitoring device of claim 1, further comprising one or more of: a MEMS inclinometer, an inertia sensor, and a gyroscope.

9\. (Currently Amended) The wearable fetal health monitoring device of claim 1, further comprising a patch configured to removably attach to the\[\[a\]\] maternal torso.

10\. (Canceled)

11\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein the wearable fetal health monitoring device further an acoustic impedance matching housing.

12\. (Canceled)

13\. (Currently Amended) The wearable fetal health monitoring device of claim 1, further comprising an inclinometer sensor that detects a sub-audible abdominal acoustic wave.
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14\. (Currently Amended) The wearable fetal health monitoring device of claim 1, wherein a first portion of the wearable fetal health monitoring device is disposable, and a second portion of the wearable fetal health monitoring device is re-usable.

15\. (Canceled)

16\. (Currently Amended) The wearable fetal health monitoring device of claim 1, further comprising a noise attenuator configured to: at least partially constructively or destructively combine a first physiological signal component of a first signal output by a first acoustic sensor and a second physiological signal component of a second signal output by a second acoustic sensor.

17\. (Currently Amended) A method of determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus, the method comprising:providing a wearable fetal health monitoring device, comprising:
a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso a- ;
an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data \[\[value\]\] from a second location on the maternal torso ;
a securing device configured to provide skin contact of the passive sensor and the optical sensor to the maternal torso for continuous non-invasive non- clinical monitoring;
and a microcontroller configured for \[\[to\]\]:SVG {EMBED HERE} 0.432.067
monitoring fetal movement (fM) using the passive sensor while operating in a first mode, wherein the first mode is a reduced power mode; and
upon detecting reduced fM activity, transitioning to a second mode comprising:decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract \[\[a\]\] mechano-acoustically sensed fetal phonocardiogram (fPCG) data \[\[value\]\];
determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and
providing an alert to the expecting mother based on the fHRV data.

18\. (Canceled)

19\. (Currently Amended) The method of claim 17, further comprising outputting at least one of a normal state, caution state, and emergency state based on the mechano- acoustically sensed fPCG data .

20\. (Currently Amended) The method of claim 17, further comprising calculating \[\[a\]\] fetal movement (fM) data \[\[value\]\] from the mechano-acoustically sensed aPCG data .
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21\. (Currently Amended) A non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium storing instructions to be implemented on a wearable fetal health monitoring device comprising:a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso a- ;
an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data \[\[value\]\] from a second location on the maternal torso ;a securing device configured to provide skin contact of the passive sensor and the optical sensor to the maternal torso for continuous non-invasive non-clinical monitoring;
 and
at least one processor;
the instructions when executed by the at least one processor cause wearable fetal health monitoring device to perform a method of determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus, the method comprising:
monitoring fetal movement (fM) using the passive sensor while operating in a first mode, wherein the first mode is a reduced power mode; and
upon detecting reduced fM activity, transitioning to a second mode comprising:
SVG {EMBED HERE} 0.432.067decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract \[\[a\]\] mechano- acoustically sensed fetal phonocardiogram (fPCG) data \[\[value\]\];
determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and providing an alert to the expecting mother based on the fHRV data.

22\. (New) The wearable fetal health monitoring device of claim 1, wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using a Hidden Semi-Markov Model (HSMM).

23\. (New) The wearable fetal health monitoring device of claim 1, wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using empirical mode decomposition (EMD).

24\. (New) The wearable fetal health monitoring device of claim 1, wherein the passive sensor is selected from the group consisting of a microelectromechanical system (MEMS), an accelerometer, and a ferroelectric nanogenerator sensor.

25\. (New) The wearable fetal health monitoring device of claim 1, wherein the securing device is selected from the group consisting of a belt, a band, and an adhesive patch.

OFFICE ACTION:
DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1, 4-9, 11, 13-14, 16-17, and 19-25 are rejected. Claims 2-3, 10, 12, 15, and 18 are canceled.
Response to Arguments
Claim Rejections - 35 USC § 112
The previous 112 rejections have been withdrawn in view of the amendment.
Claim Rejections - 35 USC § 101
Applicant's arguments filed 1/12/24 have been fully considered but they are not persuasive. Applicant argues that amended claim 1 recites additional limitations the reflect an improvement of a technical field (e.g., determining a health condition of a fetus based on biosignals of an expecting mother and the fetus) (Remarks, page 25). However, the Examiner disagrees. The claim amounts to nothing more than the abstract idea itself as recited in the rejection below. Applicant is encouraged to amend further details for the limitation “determining fetal heart rate variability” to show that it is too complex to be performed in the human mind. For instance, how many data points are used?
Applicant argues that the additional elements recited in the present claims amount to significantly more than the judicial exception (Remarks, page 29). However, the Examiner disagrees. The Examiner has provided references to show that the additional elements are well-understood, routine, and conventional structures in the rejection below.
The 101 rejection is maintained and has been updated to reflect the amendments.
Claim Rejections - 35 USC § 103
Applicant’s arguments with respect to claims 1, 4-9, 11, 13-14, 16-17, and 19-25 have been considered but are moot in view of the new ground of rejections.
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter.  See 37 CFR 1.75(d)(1) and MPEP § 608.01(o).  Correction of the following is required:
“reduced power mode” in claims 1, 17, and 21; and
“a passive sensor” in claims 1, 17, and 21.
Claim Objections
Claim 17 is objected to because of the following informalities: “heath” should read –health--.  Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA  35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.  The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph:
(A)	the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B)	the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C)	the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.  Such claim limitation(s) is/are:
a securing device in claims 1, 17, and 21
noise attenuator in claim 16
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
For “securing device” in claims 1, 7, and 21, the specification recites a belt or adhesive patch (¶28). Therefore, the Examiner is interpreting the securing device to be a belt or adhesive patch.
For “noise attenuator” in claim 16, the specification recites “the noise attenuator comprises at least one of: circuitry including an amplifier, a signal processor, or a general - purpose processor” (¶76). The Examiner is interpreting the noise attenuator to be an amplifier, a signal processor, or a general purpose processor.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, applicant may:  (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA  35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 22 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA  35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
For the limitation of “Hidden Semi-Markov Model (HSMM)” in claim 22, this is a computer implemented functional limitation “after smoothing and spike removal, peaks are segmented using a duration-dependent hidden Semi-Markov Model (DD-HSMM) into relevant cardiac states, first heart sound (S1), second heart sound (S2), systolic silence, and diastolic silence” according to ¶57 of the disclosure. ¶57 of the specification fails to disclose how the machine learning algorithm is used to determine fHRV. MPEP 2161.01(I) states the following:
Claims may lack written description when the claims define the invention in functional language
specifying a desired result but the specification does not sufficiently describe how the function is
performed or the result is achieved. For software, this can occur when the algorithm or
steps/procedure for performing the computer function are not explained at all or are not
explained in sufficient detail (simply restating the function recited in the claim is not necessarily
sufficient). In other words, the algorithm or steps/procedure taken to perform the function must
be described with sufficient detail so that one of ordinary skill in the art would understand how
the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection
IV.”
Applicant has claimed a black-box algorithm without any clear description of what is inside the box to determine fHRV. This is a functional result and the description is lacking information, for instance, how is the model trained, what are the inputs to the model, what is the order of the inputs into the model, and how are the weights determined for the model? Therefore, the claims with the limitation of “Hidden Semi-Markov Model (HSMM)” are rejected under 112(a) for failing to meet the written description requirement.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4-9, 11, 13-14, 16-17, and 19-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, specifically an abstract idea (mental process of “determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data” and certain methods of organizing human activity of “providing an alert to the expecting mother based on the fHRV data”) without significantly more.
Step 1
The claimed invention in claims 1, 4-9, 11, 13-14, 16-17, 19-25 are directed to statutory subject matter as the claims recite a wearable fetal health monitoring device, a method, and a non-transitory computer-readable storage medium for determining a health condition of a fetus based on biosignals of an expecting mother and the fetus.
Step 2A, Prong One
Regarding claims 1, 17, and 21, the recited steps are directed to certain methods of organizing human activity and a mental process of performing concepts in a human mind or by a human using a pen and paper (see MPEP 2106.04(a)(2) subsections (II) and (III)).
Regarding claims 1, 17, and 21, the limitation of “providing an alert to the expecting mother based on the fHRV data” is a process, as drafted, covers performance of the limitation that is directed to organizing human activity (managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions). For example, this limitation is nothing more than a medical professional verbally communicating the result to the mother.
Regarding claims 1, 17, and 21, the limitation of “determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data” is a process, as drafted, covers performance of the limitation that can be performed by a human mind (including an observation, evaluation, judgment, opinion) under the broadest reasonable standard. For example, this limitation is nothing more than a medical professional receiving a print out of fPCG data and making an evaluating of the fHRV based off of the data.
Step 2A, Prong Two
For claims 1, 17, and 21, the judicial exception is not integrated into a practical application. In particular, claims 1, 17, and 21 recite “a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso, an optical sensor  configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso, a securing device configured to provide skin contact of the passive sensor and the optical sensor to the maternal torso for continuous non-invasive non-clinical monitoring, a microcontroller/processor for monitoring fetal movement (fM) using the passive sensor while operating in a first mode, upon detecting reduced fM activity, transitioning to a second mode comprising: decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data, and extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data.” The passive sensor, optical sensor, securing device, decomposing step, and extracting step amount to nothing more than pre-solution activity of data gathering. The microcontroller/processor and mode transitioning step are recited at a high-level of generality and amount to nothing more than a part of a generic computer. Merely including instructions to implement an abstract idea on a computer does not integrate a judicial exception into practical application.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into
a practical application, the additional elements of a passive sensor, an optical sensor, a securing device, decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data, and extracting mechano-acoustically sensed fetal phonocardiogram (fPCG) data amount to nothing more than mere pre-solution activity of data gathering, which does not amount to an inventive concept. Moreover, the passive sensor, optical sensor, securing device, decomposing step, and extracting step are recited at a high level of generality and are well-understood, routine, and conventional activities as evidenced by WO 2019133926 (¶6; ¶73), NPL “Validation of beat by beat fetal heart signals acquired from four-channel fetal phonocardiogram with fetal electrocardiogram in healthy late pregnancy” (page 3, Phonogram Signal recording section; Figs. 1-2; page 5, last ¶; Fig. 5), NPL “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home” (page 619, section 4), US 20180000405 (¶101), and US 20180108440 (¶54-55; ¶59; ¶80). Further, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)). In this case, elements of general computer are being used to implement the abstract idea.
Regarding dependent claims 4-9, 11, 13-14, 16, 19-20, and 22-25, the limitations of claims 1, 17, and 21 further define the limitations already indicated as being directed to the abstract idea.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4, 7-9, 17, 20-21, and 24-25 are rejected under 35 U.S.C. 103 as being unpatentable over Queyam (NPL “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home” published in 2018) in view of Holt (WO 2019133926 filed on 12/28/18), Khandoker (NPL “Validation of beat by beat fetal heart signals acquired from four-channel fetal phonocardiogram with fetal electrocardiogram in healthy late pregnancy published in 2018), and Hayes (WO 2014162135 filed on 4/2/14).
Regarding claims 1, 17, and 21, Queyam teaches a wearable fetal health monitoring device, a method, and a non-transitory computer-readable storage medium for determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus, the device comprising: a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso (page 619, section 4-doppler ultrasound transducer as shown in Fig. 2(D) was placed on the mother's chest for maternal heart sound acquisition. When this transducer was placed on mother's abdomen at a location just above the fetal heart, then it captures maternal heart activity along with fetal heart activity); a securing device configured to provide skin contact of the passive sensor and the optical sensor to the maternal torso for continuous non-invasive non-clinical monitoring (page 619, Data Acquisition section-several non-invasive medical grade transducers attached to the mother's body for acquiring various maternal and fetal bio-physiological parameter like respiration rate, body temperature, photoplethysmogram (PPG), phonocardiogram (PCG), abdominal electrocardiogram (AECG) and fetal movements); and a microcontroller configured for: monitoring fetal movement (fM) using the passive sensor while operating in a first mode (page 620, Fetal Movement section-detection of the fetal movements), wherein the first mode is a reduced power mode (page 620, Fetal Movement section-detection of the fetal movements).
However, Queyam does not teach an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso; and upon detecting reduced fM activity, transitioning to a second mode comprising: decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data; determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and providing an alert to the expecting mother based on the fHRV data.
Holt relates generally to the field of medical devices and, more particularly, in the field of trans-abdominal fetal oximetry and trans-abdominal fetal pulse oximetry (¶2). Holt further teaches the invention using the following step:
an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso (¶6-maternal photoplethysmogram; ¶8-separated signal that corresponds to light incident upon the pregnant mammal (e.g., maternal photoplethysmogram); ¶73-pulse oximetry probe; ¶10-detected optical signal may correspond to an optical signal projected into the pregnant mammal’s abdomen by one or more light sources).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso of Holt in order to assess the health of a fetus (e.g., a level of hypoxia or fetal acidosis) (Holt, ¶23).
Khandoker relates generally to a proposed beat to beat fetal heart rate measurement system (page 1, ¶1). Khandoker further teaches the invention using the following steps:
decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data (page 5, last ¶-fetal phonocardiogram signal processing, the raw phonocardiogram signal to be decomposed; Fig. 5); determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data (page 9, Table 2-comparison of fetal heart rate (FHR) and heart rate variability (from 1 minute heart rate time series) extracted from fetal ECG and fetal Phonocardiogram (FPCG) recordings).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Queyam to include decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data; determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data of Khandoker in order to have a low cost and non-invasive fetal phonocardiography based signal system to measure the fetal heart sounds and fetal heart rate (Khandoker, page 1, ¶1).
Hayes relates generally to the monitoring of fetal movements, commonly referred to as fetal activity, in the womb (page 1, ¶1). Hayes further teaches the invention using the following steps:
and upon detecting reduced fM activity, transitioning to a second mode comprising (page 28, ¶1-determination of reduced or abnormal fetal movement; page 21, ¶3-a further mode; page 7, ¶3-a second mode): and providing an alert to the expecting mother based on the fHRV data (page 24, last ¶-processor may control output of an alarm or other visual, audible or tactile alert to the mother warning her; page 27, last ¶-record fetal heart rate alongside fetal movements to provide HRV (Heart Rate Variability) analysis).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Queyam to include and upon detecting reduced fM activity, transitioning to a second mode comprising and providing an alert to the expecting mother based on the fHRV data of Hayes in order to provide equipment offering more reliable and/or convenient monitoring of fetal activity in a home environment (Hayes, page 3, ¶2).
Regarding claims 4 and 20, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device and the method of claims 1 and 17, wherein the microcontroller is further configured to calculate fetal movement (fM) data from the mechano-acoustically sensed aPCG data (Khandoker, Fig. 4-four-channel unprocessed fetal phonocardiogram signals with 4 FPCG sensors. Ch 1–4 show maternal breathing movement (as low frequency baseline oscillation), and maternal and fetal heart movements (as high frequency oscillations)).
Regarding claim 7, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1, calculating a maternal activity level (Hayes, page 15-activity level; page 16, ¶3) from the optical sensor (Holt, ¶6-maternal photoplethysmogram; ¶8-separated signal that corresponds to light incident upon the pregnant mammal (e.g., maternal photoplethysmogram); ¶73-pulse oximetry probe; ¶10-detected optical signal may correspond to an optical signal projected into the pregnant mammal’s abdomen by one or more light sources).
Regarding claim 8, the combination Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1, further comprising one or more of: a MEMS inclinometer, an inertia sensor, and a gyroscope (Hayes, page 14, ¶2-a gyro, an inertial motion sensor).
Regarding claim 9, Holt teaches a patch that removably attaches to the maternal torso (¶46-an adhesive designed to be applied to the skin of the pregnant mammal’s abdomen (e.g., glue, tape, etc.) configured to apply housing 102/fetal hemoglobin probe 115 directly to the skin of the pregnant mammal’s abdomen and hold it in place there in a manner similar to a sticker).
Regarding claim 24, the combination of Queyam, Holt, Khandoker, and Hayes The wearable fetal health monitoring device of claim 1, wherein the passive sensor is selected from the group consisting of a microelectromechanical system (MEMS), an accelerometer, and a ferroelectric nanogenerator sensor (Queyam, page 620, ¶2-3-axis accelerometer).
Regarding claim 25, the combination of Queyam, Holt, Khandoker, and Hayes teaches the wearable fetal health monitoring device of claim 1, wherein the securing device is selected from the group consisting of a belt, a band, and an adhesive patch (Khandoker, page 3, elastic belts proved a simple, efficient and comfortable way to place the sensors in a consistent pattern without the need for previous knowledge of the fetal lie or position).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Venugopalan (US 20170049414 filed on 5/22/15), hereinafter referred to as Ven.
Regarding claim 5, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach wherein the optical sensor is further configured to sense maternal peripheral capillary oxygen saturation (mSpO2) data; and transitioning to the second mode is further based upon detecting reduced mSpO2 data.
Venugopalan teaches wherein the optical sensor is further configured to sense maternal peripheral capillary oxygen saturation (mSpO2) data (¶35-maternal pulse oximetry (SpO2); ¶43); and transitioning to the second mode is further based upon detecting reduced mSpO2 data (¶29).
Ven relates generally to providing wireless sensor. More specifically the subject matter relates to a wireless sensor capable of communicating with a remote ultrasound processing system for managing fetal and maternal data (¶1). Ven also relates to the fetal and maternal data being examined by a medical practitioner to determine the health status of the fetus and the subject (¶6). Ven further teaches the maternal pulse oximetry (SpO2) (¶35).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include wherein the optical sensor is further configured to sense maternal peripheral capillary oxygen saturation (mSpO2) data; and transitioning to the second mode is further based upon detecting reduced mSpO2 data of Ven in order to provide a wireless fetal sensor and system for managing fetal data and maternal data of a subject, so that the fetal and maternal data can be examined by a medical practitioner to determine the health status of the fetus and the subject (Ven, ¶6).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Stahmann (US 7787946 filed on 9/1/04).
Regarding claim 6, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach wherein the passive sensor comprises at least one of an acoustic wave sensor and a pressure wave sensor.
Stahmann teaches wherein the passive sensor comprises at least one of an acoustic wave sensor and a pressure wave sensor (col. 238 and lines 19-28-accelerometer based acoustic sensors, MEMS-based acoustic sensors).
Stahmann relates generally to systems and methods providing patient monitoring, diagnosis and/or therapy (Field of the Invention section). Stahmann further teaches one or more functions of two or more individual medical procedures may be used in combination to enhance patient monitoring, diagnosis and/or therapy (col. 2 and lines 52-54).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include wherein the passive sensor comprises at least one of an acoustic wave sensor and a pressure wave sensor of Stahmann in order for one or more functions of two or more individual medical procedures may be used in combination to enhance patient monitoring, diagnosis and/or therapy (Stahmann, col. 2 and lines 52-54).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Zia (US 20140180153 filed on 12/23/13).
Regarding claim 11, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach an acoustic impedance matching housing.
Zia teaches wherein the device further comprises an acoustic impedance matching housing (¶32-acoustically impedance matched, housing).
Zia relates generally to medical diagnostic systems, and more particularly, to a system and method for acoustic detection of coronary artery disease and automated editing of heart sound data (¶3). Zia also teaches systems and methods for adaptively canceling noise in an acoustic heart signal and/or automatically editing heart sound data (¶10).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include an acoustic impedance matching housing of Zia in order for adaptively canceling noise in an acoustic heart signal and/or automatically editing heart sound data (Zia, ¶10).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Ransbury (US 20180317789 filed on 5/2/18).
Regarding claim 13, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach an inclinometer sensor that detects a sub- audible abdominal acoustic wave.
Ransbury teaches an inclinometer sensor that detects a sub-audible abdominal acoustic wave (¶37-inclinometer; ¶30-acoustic waveforms; ¶31-sub-audile frequencies).
Ransbury relates generally to methods and systems for remote monitoring of heart activity (¶2). Ransbury more particularly relates to a wearable heart monitoring device for monitoring heart activity comprising one or more acoustic sensors, including at least one microphone configured to operate in a frequency range related to human hearing, and at least one accelerometer configured to operate in the range of low or sub-audible frequencies (¶4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include an inclinometer sensor that detects a sub- audible abdominal acoustic wave of Ransbury in order to operate in the range of low or sub-audible frequencies and analyzing the data collected by the one or more sensors to determine a condition of a heart (Ransbury, ¶9).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Khine (US 20170086709 A1 as cited in the IDS and filed on 5/18/15).
Regarding claim 14, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach wherein a first portion of the wearable fetal health monitoring device is disposable, and a second portion of the fetal health monitoring device  is re-usable.
Khine teaches wherein a first portion of the device is disposable, and a second portion of the device is re-usable (¶70-a disposable patient interface; ¶95-reusable component).
Khine relates generally to a wearable sensor for monitoring fetal movement (e.g., fetal kicks) and/or health. The disclosure relates to technology for monitoring fetal health during later stages (e.g., weeks 24+) of pregnancy. More specifically, a sensor can be worn by a mother to extract biometric data about the fetus. This data can be used as an indirect indicator of fetal health (¶9). Khine further teaches that this wearable sensor is less cumbersome then existing technology to improve user compliance. With continuous monitoring a decline in fetal movement can be detected earlier then without this device (¶10).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include wherein a first portion of the wearable fetal health monitoring device is disposable, and a second portion of the wearable fetal health monitoring device is re-usable of Khine in order to improve user compliance and with continuous monitoring a decline in fetal movement can be detected earlier then without this device (Khine, ¶10).
Claims 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Bureev (RU 2656518 filed on 3/6/14).
Regarding claim 16, the combination of Queyam, Holt, Khandoker, and Hayes teaches the device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach a noise attenuator configured to: at least partially constructively or destructively combine a first physiological signal component of a first signal output by a first acoustic sensor and a second physiological signal component of a second signal output by a second acoustic sensor.
Bureev teaches a noise attenuator configured to: at least partially constructively or destructively combine a first physiological signal component of a first signal output by a first acoustic sensor and a second physiological signal component of a second signal output by a second acoustic sensor (claim 1-attentuation of external noise and interference; page 7, middle of page-combined in one housing with complex acoustic sensors 1 and 2).
Bureev relates generally to medicine and obstetrics, in particular to medical diagnostics and can be used for mobile monitoring, and monitoring and evaluating the state of the fetus and method (page 4, top of page). Bureev more particularly relates to evaluating with maximum accuracy, the state of the fetus and mother, having a higher quality of registered signals, and increasing reliability and diagnostic value of produced data (page 9, middle of the page).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include a noise attenuator configured to: at least partially constructively or destructively combine a first physiological signal component of a first signal output by a first acoustic sensor and a second physiological signal component of a second signal output by a second acoustic sensor of Bureev in order to evaluate with maximum accuracy the state of the fetus and mother, have higher quality of registered signals, and increase reliability and diagnostic value of produced data (Bureev, page 9, middle of the page).
Regarding claim 19, the combination of Queyam, Holt, Khandoker, and Hayes teaches the method of claim 17. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach outputting at least one of a normal state, caution state, and emergency state based on the mechano-acoustically sensed fPCG data.
Bureev teaches outputting at least one of a normal state, caution state, and emergency state based on the mechano-acoustically sensed fPCG data (page 5, top of page- monitoring the fast changes of the state of the fetus; page 8, ¶2-emergency mode; page 6, ¶2-tones of the fetus heart; page 7, middle of page-digital or an analog output, is intended for recording tones of fetus heart).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include outputting at least one of a normal state, caution state, and emergency state based on the mechano-acoustically sensed fPCG data of Bureev in order to evaluate with maximum accuracy the state of the fetus and mother, have higher quality of registered signals, and increase reliability and diagnostic value of produced data (Bureev, page 9, middle of the page).
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Oliveira (NPL “Adaptive Sojourn Time HSMM for Heart Sound Segmentation” published in 2019).
Regarding claim 22, the combination of Queyam, Holt, Khandoker, and Hayes teaches the wearable fetal health monitoring device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using a Hidden Semi-Markov Model (HSMM).
Oliveira teaches wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using a Hidden Semi-Markov Model (HSMM) (page 649, left col., ¶2-HSMMs to segment a PCG signal into its main sound components; page 645, left col., ¶1-estimate the heart rate).
Oliveira relates to a new algorithm for heart sound segmentation using a hidden semi-Markov model (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using a Hidden Semi-Markov Model (HSMM) of Oliveira in order to segment a PCG signal into its main sound components (Oliveira, page 649, left col., ¶2).
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Queyam in view of Holt, Khandoker, and Hayes as applied to claims 1, 4, 7-9, 17, 20-21, and 24-25 above, and further in view of Vadali (NPL “Fetal Phonocardiogram Decomposition Framework” published in 2018).
Regarding claim 23, the combination of Queyam, Holt, Khandoker, and Hayes teaches the wearable fetal health monitoring device of claim 1. However, the combination of Queyam, Holt, Khandoker, and Hayes does not teach wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using empirical mode decomposition (EMD).
Vadali teaches wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using empirical mode decomposition (EMD) (page 2, left col., last ¶-EMD is used to decompose the FPCG signal; page 4, left col., ¶1-study can also be refined to detect the short term variability in the Fetal Heart Rate).
Vadali relates to an efficient procedure to identify vital bio-signals from the Fetal Phonocardiogram (FPCG) signal (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective
filing date of the claimed invention to modify the invention of Queyam to include wherein determining fHRV data from the mechano-acoustically sensed fPCG data comprises using empirical mode decomposition (EMD) of Vadali in order to extract the vital bio-signals in a single step (Vadali, Abstract).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action.  Accordingly, THIS ACTION IS MADE FINAL.  See MPEP § 706.07(a).  Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action.  In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action.  In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.

APPLICANT REBUTTAL: REMARKS
Applicant has carefully reviewed the non-final Office Action mailed on September 15, 2023 and offers the following remarks to accompany the above amendments.
Summary of Remarks
With respect to the rejected claims, the cited art fails to disclose or suggest a wearable fetal health monitoring device configured for continuous non-invasive non- clinical monitoring and having a microcontroller configured for:
monitoring fetal movement (fM) using the passive sensor while
operating in a first mode, wherein the first mode is a reduced power
mode; and
upon detecting reduced fMV activity, transitioning to a second mode
comprising:
decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano- acoustically sensed fetal phonocardiogram (fPCG) data;
determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and
providing an alert to the expecting mother based on the fHRV data.
Status of the Claims
Claims 1-14 and 16-21 were previously pending. Claims 1, 3-9, 11, 13-14, 17, and 19-21 are amended herein. Claim 15 was previously canceled. Claims 2, 10, 12, and 18 are canceled herein. Claims 22-25 are added herein. As such, claims 1, 3-9, 11, 13-14, 17, and 19-25 remain pending.
Claim Rejections - 35 USC § 112
Claim 1, 12, 17, and 21 stand rejected under 35 U.S.C. 112 as failing to comply with the written description requirement. The Office Action contends the subject matter was not described in the specification in such a way as to reasonably convey to a person of ordinary skill in the art had possession of the claimed invention.
Regarding claims 1, 17, and 21 the Office Action further identifies the limitation reciting "identify a noise correction value" based on comparing "the first mHR value with the second mHR value."
Claims 1, 17, and 21 have been amended to remove the above limitation.
Regarding claims 1, 17, and 21 the Office Action contends the limitation of "a ferroelectric nanogenerator sensor that detects abdominal pressure waves" seems unclear.
Claims 1, 17, and 21 have been amended to remove the above limitation.
Regarding claim 12, the Office Action further identifies the limitation reciting "deconvolute the abdominal acoustic signal" based on "using at least one of the first mHR value and the second mHR value."
Claim 12 has been canceled rendering its rejection moot.
Accordingly, it is respectfully submitted that the rejection of claims 1, 17, and 21 under 35 USC § 112 be withdrawn.
Claim Rejections Under 35 U.S.C. § 103
Claims 1-3, 7-9, 16-19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Holt (WO 2019133926 filed on 12/28/18) in view of Bureev (RU 2656518 filed on 3/6/14), Meriheina (US 20180092564 filed on 10/2/17), and Bera (NPL
"Piezoelectricity in PVDF and PVDF Based Piezoelectric Nanogenerator: A Concept" 2017).
Claim 1 has been amended to recite:
A wearable fetal health monitoring device for determining a
health
[[heath]] condition of a fetus based on biosignals of an expecting mother
and the fetus, the
wearable fetal health monitorin
g
device comprising:
a passive sensor con
fig
ured to provide mechano-acoustically sensed
phonocardio
g
ram (aPCG) data from a first location on a maternal torso
a-
micro
c
lectromechanical system
(
MEMS) acc
e
lerometer that converts an acoustic wave sensed in an abdominal region into an abdominal acoustic
signal
;
an optical sensor
a pulse oxim
e
ter that generates a
con
fig
ured to
provide optically sensed
maternal photoplethysmogram (mPPG)
data
[[value]] from
a second location on the maternal torso
a pulse sensed in
the abdominal region
;
a securin
g
device con
fig
ured to provide skin contact of the passive
sensor and the optical sensor to the maternal torso for continuous non- invasive non-clinical monitorin
g;
a ferroelectric n
ano
generator sensor that detects abdominal pressure
waves;
and
a microcontroller configured for [[to]]:
generate a maternal phonocardiogram (mPCG) value from the abdominal
acoustic signal;
calculate a
first maternal heart rate (mHR) value from the mPCG valu
e;
calculate a second mHR value from the mPPG valu
e;
compare the first mHR value with the second mHR value to identify a noise
correction value; and
monitorin
g
fetal movement (fM) usin
g
the passive sensor while operatin
g
in
a first mode, wherein the first mode is a reduced power mode; and
upon detectin
g
reduced fM activity, transitionin
g
to a second mode
comprisin
g:
decomposin
g
the mechano-acoustically sensed aPCG data usin
g
the optically sensed mPPG data
apply the identified noise
correction value to the mPCG valu
e
to extract [[a]]
mechano- acoustically sensed
fetal phonocardiogram (fPCG)
data
[[value]];
determinin
g
fetal heart rate variability (fH
RV
) data from the mechano-acoustically sensed
f
PCG data; and
providin
g
an alert to the expectin
g
mother based on the
fH
RV data.
Support for amended claim 1 may be found in at least the following paragraphs and figures of the Published Application:
[0046] In at least one embodiment, the fetal health monitoring
device forming part of system 100 may operate through an operational decision-making cycle shown in FIG. 2. Various aspects of vigilant monitoring 201 are explained further by way of a flowchart illustrated in FIG. 6. According on one embodiment, vigilant monitor 201 may run continuously unless a "fail" condition occurs. The "fail" condition may include instances such as, for example, less than 4 fM events detected per hour, a low mSpO2 condition, or a similar other situation that indicates that the health of the fetus may be negatively impacted. In response to such a "fail" condition, the device and/or system may transition to conduct a quick interrogation cycle such as quick cycle 202. In one embodiment, the quick interrogation cycle by way of quick cycle 202 may average twenty (20) minutes in length; in this embodiment,
the average of twenty (20) minutes may be needed to draw physiologically relevant conclusions. Quick cycle 202 may proceed to investigate fHR and accelerations in fHRV. FIG. 4 illustrates the primary influences on (i.e., the various factors that may cause, impact or affect) Fetal heart rate
variability (fHRV).
FIG. 2
FIG. 6
[0056] Acoustic sensor 502 operates to transduce abdominal
sounds sensed at an abdominal phonocardiogram (aPCG). In at least one embodiment, an abdominal acoustic signal passes through source separation algorithm 503. Source separation algorithm 503 decomposes the abdominal acoustic signal using the maternal heart rate information obtained by optical sensor 501. During low-power vigilant monitoring state (e.g., during vigilant monitor 201) and during quick interrogation cycle (e.g., during quick cycle 202), a low-fidelity source separation algorithm may be used for signal extraction, including band pass filtering, empirical mode decomposition (EMD), and clustering of
intrinsic mode functions (IMF) by signal type. In one embodiment, the IMFs may be selectively recombined into signals such as fetal movement signal (i.e., fM 504) and fetal phonocardiogram signal (i.e., fPCG 505). In detailed interrogation mode of detailed cycle 203, a high-fidelity source separation algorithm  is used. The high-fidelity source separation algorithm may include technics such as bandpass filtering, short-time Fourier transform of the abdominal acoustic signal, and audio source separation using a deep neural network generated soft mask. The detailed interrogation mode of the detailed cycle 203 may use these high-fidelity source separation algorithm technics to remove or separate maternal phonocardiogram and abdominal signals. Subsequently, fM and fPCG are separated using empirical mode decomposition EMD. In vigilant monitoring state (e.g., at vigilant monitor 201), after signal acquisition and source separation, fM 504 and mSpO2 507 are sent to a condition
classifier algorithm to determine a pass/fail state discussed in FIG. 2.
[0057] In either interrogation mode (i.e., in the quick interrogation
cycle such as quick cycle 202, or in the detailed interrogation cycle such as detailed cycle 203), fPCG 505 and mPPG 506 are sent to a feature extraction algorithm 508. Feature extraction algorithm 508 operates to first determine important peaks through homomorphic envelograms and Hilbert-Huang transformation. After smoothing and spike removal, peaks are segmented using a duration-dependent hidden Semi-Markov Model (DD-HSMM) into relevant cardiac states, first heart sound (Si), second heart sound (S2), systolic silence, and diastolic silence. The DD-HSMM is trained with clinical data to segment a signal based on the limited physiological duration of fetal cardiac states. After extraction and
annotation, fHRV is calculated and passed to the condition classifier 509. Additional details regarding the output states of the condition classifier algorithm including output states such as-no alerts 510, concern warning 511, and critical alarm 512 are described earlier with
regard to FIG. 2.
The cited art fails to disclose or suggest a wearable fetal health monitoring device configured for continuous non-invasive non-clinical monitoring and having a microcontroller configured for:
monitoring fetal movement (fM) using the passive sensor while
operating in a first mode, wherein the first mode is a reduced power
mode; and
upon detecting reduced fM activity, transitioning to a second mode
comprising:
decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano- acoustically sensed fetal phonocardiogram (fPCG) data;
determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and
providing an alert to the expecting mother based on the fHRV data.
As such, amended claim 1 is allowable.
Claims 2 and 18 have been canceled rendering their rejection moot.
Claims 3, 7-9, and 16 depend directly from now allowable claim 1. As such, claims 3, 7-9, and 16 are allowable at least by virtue of their dependence from claim 1.
Claims 17 and 21 have been amended to include features that are similar to amended claim 1. As such claims 17 and 21 are also allowable.
Claim 19 depends directly from now allowable claim 17. As such, claim 19 is allowable at least by virtue of their dependence from claim 17.
Claims 4 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Igney (US 20100305481 filed on 5/7/08).
Claim 4 depends directly from now allowable claim 1. As such, claim 4 is allowable at least by virtue of its dependence from claim 1.
Claim 20 depends directly from now allowable claim 17. As such, claim 20 is allowable at least by virtue of its dependence from claim 17.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Venugopalan (US 20170049414 filed on 5/22/15), hereinafter referred to as Ven.
Claim 5 has been amended to recite:
The
wearable fetal health monitorin
g
device of claim 1, wherein:
the
optical sensor
pulse oximeter
is further configured to sense
[[a]] maternal peripheral capillary oxygen saturation (mSp02)
data
[[value]];
and
transitionin
g
to the second mode is further based upon detectin
g
reduced mSp
O
2 data.
Support for the above amendment may be found in at least the following paragraph and figure of the Published Application:
FIG. 6 is a flowchart illustrating various aspects of one
implementation of vigilant monitoring performed by vigilant monitor 201 shown in FIG. 2. According to one embodiment, a primary mode of operation of vigilant monitor 201 comprises checking of fetal movement at track fetal movement 601. When vigilant monitor 201 determines that fetal movement has been sensed greater than 4 times within an hour at decision step 602, vigilant monitor 201 causes the algorithm to repeat checking of fetal movement at track fetal movement 601. If it is determined that fetal movement is sensed only 4 times or less within an hour at decision step 602, vigilant monitor 201 causes the algorithm to commence measuring mSpO2 level at step 603. If at step 603, the mSpO2 level is found to be normal, vigilant monitor 201 causes the algorithm to proceed to quick monitoring at step 604; however, if at step 603, the mSpO2 level is found to be low, vigilant monitor 201 causes the algorithm to proceed to detailed
monitoring at step 605.
FIG. 6
Nowhere do the cited references disclose transitioning to the second mode is further based upon detecting reduced mSpO2 data.
Claim 5 depends directly from now allowable claim 1. As such, claim 5 is allowable at least by virtue of its dependence from claim 1.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Stahmann (US 7787946 filed on 9/1/04).
Claim 6 depends directly from now allowable claim 1. As such, claim 6 is allowable at least by virtue of its dependence from claim 1.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Workman (US 20170281087 as cited in the IDS and filed on 3/31/17).
Claim 10 has been canceled rendering its rejection moot.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Zia (US 20140180153 filed on 12/23/13).
Claim 11 depends directly from now allowable claim 1. As such, claim 11 is allowable at least by virtue of its dependence from claim 1.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Chen (WO 2018148251 filed on 2/7/18).
Claim 12 has been canceled rendering its rejection moot.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Ransbury (US 20180317789 filed on 5/2/18).
Claim 13 depends directly from now allowable claim 1. As such, claim 13 is allowable at least by virtue of its dependence from claim 1.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Holt in view of Bureev, Meriheina, and Bera as applied to claims 1-3, 7-9, and 16-19 above, and further in view of Khine (US 20170086709 Al as cited in the IDS and filed on 5/18/15).
Claim 14 depends directly from now allowable claim 1. As such, claim 14 is allowable at least by virtue of its dependence from claim 1.
Accordingly, it is respectfully submitted that the rejection under 35 U.S.C. 103 of claims 1, 3-9, 11, 13-14, 17, and 19-21 be withdrawn.
Claim Rejections Under 35 U.S.C. 101
Claims 1-20 stand rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The Office Action further contends claims 1-20 are directed toward an abstract idea related to certain methods of organizing human activity such as commercial or legal interactions including advertising, marketing or sales activities or behaviors, or business relations and fail to pass Step 2A - Prong 1 of the Alice/Mayo analysis. Additionally, the Office Action contends claims 1-20 are not integrated into a practical application and fail to pass Step 2A - Prong 2 of the Alice/Mayo analysis. Finally, the Office Action contends claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception and fail to pass Step 2B of the Alice/Mayo analysis.
A clean version of amended claim 1 is recited as follows:
A wearable fetal health monitoring device for determining a health
condition of a fetus based on biosignals of an expecting mother and the
fetus, the wearable fetal health monitoring device comprising:
a passive sensor configured to provide mechano-acoustically
sensed phonocardiogram (aPCG) data from a first location on a maternal
torso;
an optical sensor configured to provide optically sensed maternal
photoplethysmogram (mPPG) data from a second location on the
maternal torso;
a securing device configured to provide skin contact of the passive
sensor and the optical sensor to the maternal torso for continuous non- invasive non-clinical monitoring; and
a microcontroller configured for:
monitoring fetal movement (fM) using the passive sensor while operating in a first mode, wherein the first mode is a reduced power mode;
and
upon detecting reduced fM activity, transitioning to a second mode comprising:
decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data; determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and providing an alert to the expecting mother based on
the fHRV data.
The following remarks will address claims 1-20 in regard to Step 2A - Prong 2 and Step 2B of the Alice/Mayo analysis.
Updates to the Federal Register / Vol 84. No. 4 on Monday, January 7, 2019 titled "2019 Revised Patent Subject Matter Eligibility Guidance" recites the following regarding Step 2A - Prong 2:
Prong Two represents a change from prior guidance. The analysis under Prong Two is the same for all claims reciting a judicial exception, whether the exception is an abstract idea, a law of nature, or a natural
phenomenon.
In the context of revised Step 2A, the following exemplary considerations are indicative that an  additional element (or combination  of elements) [24] may have integrated the exception into a practical
application:
e An   additional element reflects an  improvement in the
functioning of a computer, or an improvement to other technology
or technical field.
Additionally, slide 19 of the 2019 PEG -Advanced Module dated January 2019 identifies Step 2A as a two prong inquiry with updated guidance to Step 2A-Prong 2 as follows:
o Revised Step 2A: Prong Two
New procedure not found in prior guidance:e Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and
"Integration into a practical application"
e Requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting  effort designed  to  monopolize  the exception.
e  Uses the considerations laid out by the Supreme Court and the Federal Circuit to evaluate whether the judicial exception is integrated into a practical application.
Further, page 11 of the USPTO Memorandum titled "October 2019 Update: Subject Matter Eligibility" recites the following regarding Step 2B -Prong 2:
"For example, if the additional limitations reflect an improvement in the functioning of a computer, or an improvement to another technology or technical field, the claim integrates the judicial exception into a practical application and thus imposes a meaningful limit on the judicial exception.
No further analysis is required. The claim is eligible at Step 2A."
Amended claim 1 recites additional limitations that reflect an improvement of a technical field (e.g., determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus). More specifically, amended claim 1 recites a wearable fetal health monitoring device configured for continuous non-invasive non-clinical monitoring, and including additional limitations as follows:
a microcontroller configured for:
monitoring fetal movement (fM) using the passive sensor while operating in a first mode, wherein the first mode is a reduced power mode;
and
upon detecting reduced fM activity, transitioning to a second mode comprising:
decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data;
determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data; and providing an alert to the expecting mother based on
the fHRV data.
In addition to the microcontroller of the wearable fetal health monitoring device, the claim is further limited by a passive sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso and an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso.
As such, determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus is improved.
A person of ordinary skill in the art would understand that such a method must be implemented on a computing device. Accordingly, amended claim 1 recites a practical application. As such for the reasons above, amended claim 1 passes Step 2A Prong Two of the Alice/Mayo analysis.
In the event the Patent Office believes amended claim 1 is still directed at a judicial exception that is not integrated into a practical application and fails to pass Step 2A of the Alice/Mayo analysis, a further analysis of amended claim 13 against Step 2B follows.
The following paragraph and reference are recited on page 51 in the updates to the Federal Register /Vol 84. No. 4 on Monday, January 7, 2019 titled "2019 Revised Patent Subject Matter Eligibility Guidance":
Finally, if further analysis at Step 2B is needed (for example to determine whether the claim merely recites well-understood, routine, conventional activity), this 2019 Revised Patent Subject Matter Eligibility Guidance
explains that the examiner or administrative patent judge will proceed in
accordance with existing USPTO guidance as modified in April 2018.[6]
6. USPTO Memorandum of April 19, 2018, "Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter
Eligibility Decision (Berkheimer v. HP, Inc.)" (Apr. 19, 2018),
The above USPTO Memorandum recites in Section III updated requirements for a Step 2B analysis of Alice/Mayo. As Applicant understands this guidance, the Examiner must support a 101 rejection using at least one of the following four points of the Memorandum to determine that the combination of elements are well-understood, routine or conventional in nature:
1. A citation to an express statement in the specification or to a statement
made by an applicant during prosecution that demonstrates the well- understood, routine, conventional nature of the additional element(s).
A   specification  demonstrates  the  well-understood,  routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a). A finding that an element is well-understood, routine, or conventional cannot be based only on the fact that the specification is silent with
respect to describing such element.
2. A citation to one or more of the court decisions discussed in MPEP Q
(d)(II) as noting the well-understood, routine, conventional
nature of the additional element(s).
. A citation to a publication that demonstrates the well-understood,
routine, conventional nature of the additional element(s). An appropriate publication could include a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry. It does not include all items that might otherwise qualify as a "printed publication" as used in 35 U.S.C. § 102.3. Whether something is disclosed in a document that is considered a "printed publication"
under 3 5 U.S. C § 102 is a distinct inquiry from whether something is well-known, routine, conventional activity. A document may be a printed publication but still fail to establish that something it describes is well-understood, routine, conventional activity. See Exergen Corp., 2018 WL 1193529, at *4 (the single copy of a thesis written in German and located in a German university library considered to be a "printed publication" in Hall "would not suffice to establish that something is 'well-understood, routine, and conventional activity previously engaged in by scientists who work in the field"'). The nature of the publication and the description of the additional elements in the publication would need to demonstrate that the additional elements are widely prevalent or in common use in the relevant field, comparable to the types of activity or elements that are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a). For example, while U.S. patents and published applications are publications, merely finding the additional element in a single patent or published application would not be sufficient to demonstrate that the additional element is well- understood, routine, conventional, unless the patent or published
application demonstrates that the additional element are widely
prevalent or in common use in the relevant field.
4. A statement that the examiner is taking official notice of the well- understood, routine, conventional nature of the additional element(s).
This option should be used only when the examiner is certain, based upon his or her personal knowledge, that the additional element(s) represents well-understood, routine, conventional activity engaged in by those in the relevant art, in that the additional elements are widely prevalent or in common use in the relevant field, comparable to the types of activity or elements that are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a). Procedures for taking official notice and addressing an applicant's challenge to official notice are discussed in MPEP Q
.
Taking into account the above guidance, it is clear that the
additional elements
recited in the present claims amount to significantly more than the judicial exception and therefor are patent-eligible subject matter because the
additional elements
is not well- understood, routine, or conventional in nature as required by at least one of the above four points of the Memorandum.
Regarding point 1 of the Memorandum, nowhere has Applicant cited in the Specification, or during prosecution that the above
additional elements
would be well- understood, routine, or conventional in nature to a person of ordinary skill in the art at the priority date of the application.
Regarding point 2 of the Memorandum, Applicant is unaware of any court decisions discussed in MPEP § 2106.05(d)(II) as noting a well-understood, routine, or conventional in nature the above
additional elements.
Regarding point 3 of the Memorandum, the Office Action fails to cite any references that disclose the above
additional elements
as well-understood, routine, or conventional in nature.
Regarding point 4 of the Memorandum, the Examiner has not taken official notice in the Office Action that the above
additional elements
are well-understood, routine, or conventional in nature.
As such, amended claim 1 in addition to passing Step 2A also passes Step 2B of the Alice/Mayo analysis.
Claims 2, 10, 12, and 18 has been cancelled rendering their rejection moot.
Claims 3-9, 11, 13-14, and 16 depend directly from amended claim 1 and are allowable at least by virtue of its dependence from amended claim 1.
Claim 17 and 21 have been amended to include features that are similar to amended claim 1. As such claims 17 and 21 are also allowable.
Claims 19-20 depend directly for amended claim 17 and are allowable at least by virtue of their dependence from amended claim 17.
Accordingly, it is respectfully submitted that the rejection under 35 U.S.C. 101 of claims 1, 3-9, 11, 13-14, 17, and 19-21 be withdrawn.
New Claims
New claims 22-25 are added herein.
Support for new claim 22 may be found in at least the following paragraph of the Published Application:
[0057] In either interrogation mode (i.e., in the quick interrogation
cycle such as quick cycle 202, or in the detailed interrogation cycle such as detailed cycle 203), fPCG 505 and mPPG 506 are sent to a feature extraction algorithm 508. Feature extraction algorithm 508 operates to first determine important peaks through homomorphic envelograms and Hilbert-Huang transformation. After smoothing and spike removal, peaks are segmented using a duration-dependent hidden Semi-Markov Model (DD-HSMM) into relevant cardiac states, first heart sound (Si), second heart sound (S2), systolic silence, and diastolic silence. The DD-HSMM is trained with clinical data to segment a signal based on the limited physiological duration of fetal cardiac states. After extraction and annotation, fHRV is calculated and passed to the condition classifier 509. Additional details regarding the output states of the condition classifier algorithm including output states such as-no alerts 510, concern warning 511, and critical alarm 512 are described earlier with
regard to FIG. 2.
Nowhere do the cited references disclose determining fHRV data from the mechano-acoustically sensed fPCG data comprises using a Hidden Semi-Markov Model (HSMM) of claim 22.
Support for new claim 23 may be found in at least the following paragraph of the Published Application:
[0056] Acoustic sensor 502 operates to transduce abdominal
sounds sensed at an abdominal phonocardiogram (aPCG). In at least one embodiment, an abdominal acoustic signal passes through source separation algorithm 503. Source separation algorithm 503 decomposes the abdominal acoustic signal using the maternal heart rate information
obtained by optical sensor 501. During low-power vigilant monitoring state (e.g., during vigilant monitor 201) and during quick interrogation cycle (e.g., during quick cycle 202), a low-fidelity source separation algorithm may be used for signal extraction, including band pass filtering, empirical mode decomposition (EMD), and clustering of intrinsic mode functions (IMF) by signal type. In one embodiment, the IMFs may be selectively recombined into signals such as fetal movement signal (i.e., fM 504) and fetal phonocardiogram signal (i.e., fPCG 505). In detailed interrogation mode of detailed cycle 203, a high-fidelity source separation algorithm is used. The high-fidelity source separation algorithm may include technics such as bandpass filtering, short-time Fourier transform of the abdominal acoustic signal, and audio source separation using a deep neural network generated soft mask. The detailed interrogation mode of the detailed cycle 203 may use these high-fidelity source separation algorithm technics to remove or separate maternal phonocardiogram and abdominal signals. Subsequently, fM and fPCG are separated using empirical mode decomposition EMD. In vigilant monitoring state (e.g., at vigilant monitor 201), after signal acquisition and source separation, fM 504 and mSpO2 507 are sent to a condition classifier algorithm to
determine a pass/fail state discussed in FIG. 2.
Nowhere do the cited references disclose determining fHRV data from the mechano-acoustically sensed fPCG data comprises using empirical mode decomposition (EMD) of claim 23.
Support for new claim 24 may be found in at least the following paragraph of the Published Application:
[0078] In some embodiments, a computer implemented method
using the system is provided. The method is for determining fetal seismocardiography data from abdominal acoustic wave data obtained through inclinometer sensing units as disclosed herein. In some embodiments, the   method  further  comprises  determining  fetal ballistocardiography data from abdominal acoustic wave data obtained through inclinometer sensing units. In some embodiments, the method is for determining fetal phonocardiography data from abdominal acoustic wave data obtained through MEMS accelerometer sensing units. In some embodiments, the method is for determining fetal movement data from  abdominal acoustic wave data obtained through
MEMS
accelerometer sensing units. In some embodiments, the method for determining fetal heartrate data from abdominal pressure wave data obtained through diaphragm or ferroelectric nanogenerator sensing units. In some embodiments, the method is for determining fetal movement data from abdominal pressure wave data obtained through diaphragm or ferroelectric nanogenerator sensing units. In some embodiments, the method is for use of audio source separation for separating fetal movement from abdominal acoustic signal. In some embodiments, the method is for use of audio source separation for separating fetal phonocardiogram from abdominal acoustic signal. In some embodiments, the method is for assessing fetal health based on various input conditions.
Support for new claim 25 may be found in at least the following paragraph of the Published Application:
[0044] FIGS. 1 through 6 illustrate various aspects of the
presently disclosed subject matter. FIG. IA is a block diagram of various physical hardware in a wearable fetal monitoring device, according to at
least one embodiment of the presently disclosed subject matter. FIG. lB is a perspective view illustrating the placement of the belt-based version of the device and the adhesive patch version of the device, according to at least one embodiment of the presently disclosed subject matter. FIG. 2 is a flowchart of the operational cycle of a fetal monitoring device, according to at least one embodiment of the presently disclosed subject matter. FIG. 3A is a top-down view of the non-contact side of a fetal monitoring patch, according to at least one embodiment of the presently disclosed subject matter. FIG. 3B is a profile view of the internal components of a fetal monitoring patch, according to at least one embodiment of the presently disclosed subject matter. FIG. 3C is a bottom view of the skin contacting side of a fetal monitoring patch, according to at least one embodiment of the presently disclosed subject matter. FIG.
3D is a top-down view of the two hardware modules of a fetal monitoring band, according to at least one embodiment of the presently disclosed subject matter. FIG. 5 is a flowchart of the flow of data in a fetal monitoring device, according to at least one embodiment of the presently disclosed subject matter. FIG. 6 is a flowchart of a vigilant monitor decision stream, according to at least one embodiment of the
presently disclosed subject matter.
New claims 22-25 depend directly from now allowable claims. As such new claims 22-25 are allowable at least by virtue of their dependence from claim 1.
CONCLUSION

NEXT OFFICE ACTION: DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection.  Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.  Applicant's submission filed on 8/13/24 has been entered.
Status of Claims
Claims 1, 4-5, 7-9, 11, 13-14, 16-17, 19-21, 23, and 25 are rejected. Claims 2-3, 6, 10, 12, 15, 18, 22 and 24 are canceled.
Response to Arguments
Specification Objections
The previous specification objections have been withdrawn.
Claim Objection
The previous claim objection has been withdrawn in view of the amendment.
Claim Rejections - 35 USC § 112
The previous 112 rejection has been withdrawn in view of the claim being canceled.
Claim Rejections - 35 USC § 101
Applicant's arguments filed 6/25/24 have been fully considered but they are not persuasive.
Applicant argues that claim 1 recites additional limitations that reflect an improvement of a technical field (e.g., determining a health condition of a fetus based on biosignals of an expecting mother and the fetus). However, the Examiner disagrees. Providing an alert to the expecting mother of a medical emergency would not be sufficient to overcome the rejection. Providing an alert would still fall under an abstract idea. An improvement to the abstract idea is still an abstract idea.
Applicant argues that an expectant mother would not be capable of continuously monitoring for reduced fetal movement and then determine fHRV from a printout of fPCG data during home monitoring with a fetal electrocardiography (fECG) device. However, the Examiner disagrees. The breadth of the claims is broad. The claims don't specify how often this occurs and how much data is being used. Additionally, applying the abstract idea to a computer does not make the abstract idea eligible under 101.
Applicant argues that the additional elements are not well-understood, routine, or conventional in nature. However, the Examiner disagrees. Under Step 2B of the 101 rejection, the Examiner recited the additional elements of a passive sensor, an optical sensor, a securing device, decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data, and extracting mechano-acoustically sensed fetal phonocardiogram (fPCG) data amount to nothing more than mere pre-solution activity of data gathering, which does not amount to an inventive concept. Moreover, the passive sensor, optical sensor, securing device, decomposing step, and extracting step are recited at a high level of generality and are well-understood, routine, and conventional activities as evidenced by WO 2019133926 (¶6; ¶73), NPL “Validation of beat by beat fetal heart signals acquired from four-channel fetal phonocardiogram with fetal electrocardiogram in healthy late pregnancy” (page 3, Phonogram Signal recording section; Figs. 1-2; page 5, last ¶; Fig. 5), NPL “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home” (page 619, section 4), US 20180000405 (¶101), and US 20180108440 (¶54-55; ¶59; ¶80).
The 101 rejection is maintained and has been updated to reflect the amendments.
Claim Rejections - 35 USC § 103
The 103 rejection has been withdrawn. See the Examiner’s Note section below.
Claim Objections
Claim 21 is objected to because of the following informalities: “heath” should read –health--.  Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA  35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.  The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph:
(A)	the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B)	the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C)	the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.  Such claim limitation(s) is/are:
a securing device in claims 1, 17, 21, and 25; and
noise attenuator in claim 16.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
For “securing device” in claims 1, 7, 21, and 25 the specification recites a belt or adhesive patch (¶28). Therefore, the Examiner is interpreting the securing device to be a belt or adhesive patch.
For “noise attenuator” in claim 16, the specification recites “the noise attenuator comprises at least one of: circuitry including an amplifier, a signal processor, or a general - purpose processor” (¶76). The Examiner is interpreting the noise attenuator to be an amplifier, a signal processor, or a general purpose processor.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph, applicant may:  (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA  35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4-5, 7-9, 11, 13-14, 16-17, 19-21, 23, and 25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, specifically an abstract idea without significantly more.
Step 1
The claimed invention in claims 1, 4-5, 7-9, 11, 13-14, 16-17, 19-21, 23, and 25 are directed to statutory subject matter as the claims recite a wearable fetal health monitoring device, a method, and a non-transitory computer-readable storage medium for determining a health condition of a fetus based on biosignals of an expecting mother and the fetus.
Step 2A, Prong One
Regarding claims 1, 17, and 21, the recited steps are directed to certain methods of organizing human activity and a mental process of performing concepts in a human mind or by a human using a pen and paper (see MPEP 2106.04(a)(2) subsections (II) and (III)).
Regarding claims 1, 17, and 21, the limitation of “providing an alert to the expecting mother based on the fHRV data, wherein the alert is indicative of a medical emergency” is a process, as drafted, covers performance of the limitation that is directed to organizing human activity (managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions). For example, this limitation is nothing more than a medical professional verbally communicating the medical emergency to the mother.
Regarding claims 1, 17, and 21, the limitation of “determining fetal heart rate variability (fHRV) data from the mechano-acoustically sensed fPCG data” is a process, as drafted, covers performance of the limitation that can be performed by a human mind (including an observation, evaluation, judgment, opinion) under the broadest reasonable standard. For example, this limitation is nothing more than a medical professional receiving a print out of fPCG data and making an evaluating of the fHRV based off of the data.
Step 2A, Prong Two
For claims 1, 17, and 21, the judicial exception is not integrated into a practical application. In particular, claims 1, 17, and 21 recite “an acoustic sensor configured to provide mechano-acoustically sensed phonocardiogram (aPCG) data from a first location on a maternal torso; an optical sensor configured to provide optically sensed maternal photoplethysmogram (mPPG) data from a second location on the maternal torso, wherein the first location and the second location are mutually exclusive; a securing device configured to provide skin contact of the acoustic sensor and the optical sensor to the maternal torso for continuous non-invasive non-clinical monitoring, a microcontroller/processor configured for monitoring fetal movement (fM) using the acoustic sensor while operating in a first mode, wherein the first mode is a low-power vigilant monitoring state; upon detecting reduced fM activity, transitioning to a second mode comprising: decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data to extract mechano-acoustically sensed fetal phonocardiogram (fPCG) data.” The acoustic sensor, optical sensor, securing device, and decomposing step amount to nothing more than pre-solution activity of data gathering. The microcontroller/processor and mode transitioning step are recited at a high-level of generality and amount to nothing more than a part of a generic computer. Merely including instructions to implement an abstract idea on a computer does not integrate a judicial exception into practical application.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into
a practical application, the additional elements of an acoustic sensor, an optical sensor, a securing device, decomposing the mechano-acoustically sensed aPCG data using the optically sensed mPPG data, and extracting mechano-acoustically sensed fetal phonocardiogram (fPCG) data amount to nothing more than mere pre-solution activity of data gathering, which does not amount to an inventive concept. Moreover, the acoustic sensor, optical sensor, securing device, decomposing step, and extracting step are recited at a high level of generality and are well-understood, routine, and conventional activities as evidenced by WO 2019133926 (¶6; ¶73), NPL “Validation of beat by beat fetal heart signals acquired from four-channel fetal phonocardiogram with fetal electrocardiogram in healthy late pregnancy” (page 3, Phonogram Signal recording section; Figs. 1-2; page 5, last ¶; Fig. 5), NPL “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home” (page 619, section 4), US 20180000405 (¶101), and US 20180108440 (¶54-55; ¶59; ¶80). Further, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)). In this case, elements of general computer are being used to implement the abstract idea.
Regarding dependent claims 4-5, 7-9, 11, 13-14, 16, 19-20, 23, and 25, the limitations of claims 1, 17, and 21 further define the limitations already indicated as being directed to the abstract idea.
Examiner’s Note
Claims 1, 4-5, 7-9, 11, 13-14, 16-17, 19-21, 23, and 25 distinguish over the prior art but are still rejected under 35 USC § 101.
The following is a statement of reasons for the indication of allowable subject matter:
The scope of a fetal health monitoring device configured to use the acoustic sensor while operating in a first mode, and upon detecting reduced fetal movement activity, transitioning to a second mode was not found in the prior art alone or in combination with one another to be obvious over the prior art of record. The closest prior art of record is Queyam (NPL “An IoT Based Multi-Parameter Data Acquisition System for Efficient Bio-Telemonitoring of Pregnant Women at Home” published in 2018); however it fails to recite these features.
Conclusion

CITED REFERENCE SUMMARIES: Ref US20180000405A1: Claims:
A modular system for monitoring health parameters of a user, the modular system comprising: a housing comprising: a plurality of sensors disposed on an outer surface of the housing or within the housing for measuring a plurality of parameters of interest; a processor disposed in the housing and communicatively coupled to the plurality of sensors; a coupling element positioned on the outer surface the housing for coupling the housing to an accessory; and an accessory identifier positioned on the housing or within the housing, the accessory identifier communicatively coupled to the processor, wherein the housing is reversibly transitionable between an uncoupled state and a coupled state with the accessory, and wherein, in the coupled state, the accessory identifier senses a type of accessory and the processor activates a subset of the plurality of sensors to measure a subset of the plurality of parameters of interest.
a housing comprising:
a plurality of sensors disposed on an outer surface of the housing or within the housing for measuring a plurality of parameters of interest;
a processor disposed in the housing and communicatively coupled to the plurality of sensors;
a coupling element positioned on the outer surface the housing for coupling the housing to an accessory; and
an accessory identifier positioned on the housing or within the housing, the accessory identifier communicatively coupled to the processor, wherein the housing is reversibly transitionable between an uncoupled state and a coupled state with the accessory, and wherein, in the coupled state, the accessory identifier senses a type of accessory and the processor activates a subset of the plurality of sensors to measure a subset of the plurality of parameters of interest.
wherein the housing is reversibly transitionable between an uncoupled state and a coupled state with the accessory, and
wherein, in the coupled state, the accessory identifier senses a type of accessory and the processor activates a subset of the plurality of sensors to measure a subset of the plurality of parameters of interest.
The modular system of claim 1 , wherein the subset of the plurality of parameters of interest measured changes based on the type of accessory coupled to the housing.
The modular system of claim 1 , wherein the accessory identifier comprises a plurality of electrical terminals.
The modular system of claim 3 , wherein, in the coupled state, the plurality of electrical terminals is connected to a plurality of electrical receptacles on the accessory, and wherein an impedance between the plurality of electrical receptacles is detectable by the accessory identifier.
The modular system of claim 1 , wherein the accessory is one or more of: wearable by a user and positionable proximate a user.
The modular system of claim 1 , further comprising an antenna and transceiver communicatively coupled to the processor, wherein the antenna and transceiver wirelessly transmit the subset of the plurality of parameters of interest to a computing device.
The modular system of claim 6 , wherein the subset of the plurality of parameters of interest are displayable to a user on a display of the computing device.
The modular system of claim 7 , wherein a graphical user interface displayed on the display of the computing device adapts based on the type of accessory identified.
The modular system of claim 1 , wherein the plurality of sensors includes one or more of: a physiological sensor, a bio-potential sensor, an activity sensor, an optical sensor, a bio-impedance sensor, an acoustic sensor, an ultrasound sensor, an electrochemical sensor, a near-infrared spectroscopy sensor, and a temperature sensor.
The modular system of claim 1 , wherein the type of accessory is one of a wristband, a bra clip, a first trimester belly patch, a second trimester belly patch, a third trimester belly patch, a pregnancy support belt, a patch coupled to baby clothing, and an accessory integrated into clothing.
The modular system of claim 1 , wherein during pre-conception, the plurality of sensors measure one of: a paternal subset of the plurality of parameters of interest and a maternal subset of the plurality of parameters of interest.
The modular system of claim 9 , wherein the paternal subset of the plurality of parameters of interest include one or more of: an activity level, a sleep quality, a stress level, an oxygen saturation level, a cardiorespiratory fitness level, a heart rate, and a heart rate variability.
The modular system of claim 9 , wherein the maternal subset of the plurality of parameters of interest include one or more of: an activity level, a sleep quality, a stress level, an oxygen saturation level, a cardiorespiratory fitness level, a heart rate, and a heart rate variability.
The modular system of claim 1 , wherein during pregnancy, the plurality of sensors measures a maternal subset of the plurality of parameters of interest and a fetal subset of the plurality of parameters of interest.
The modular system of claim 14 , wherein the maternal subset of the plurality of parameters of interest include one or more of: an electrohysterography signal, maternal uterine activity, maternal uterine contractions, maternal heart electrical activity, maternal heart rate, maternal heart rate variability, a maternal activity level, a maternal sleep quality, a maternal oxygen saturation level, a maternal cardiorespiratory fitness level, and a maternal stress level.
The modular system of claim 14 , wherein the fetal subset of the plurality of parameters of interest include one or more of: fetal movement, fetal heart electrical activity, fetal heart sound, fetal heart rate, fetal heart rate variability, an amount of amniotic fluid, placental oxygenation, placental temperature, placental pH, fetal breathing, fetal position, fetal orientation, and fetal distress.
The modular system of claim 1 , wherein during post-partum, the plurality of sensors measure one of: a maternal subset of the plurality of parameters of interest, a newborn subset of the plurality of parameters of interest, and a paternal subset of the plurality of parameters of interest.
The modular system of claim 17 , wherein the maternal subset of the plurality of parameters of interest include one or more of: an activity level, a sleep quality, stress level, an oxygen saturation level, a cardiorespiratory fitness level, heart rate, and heart rate variability.
The modular system of claim 17 , wherein the newborn subset of the plurality of parameters of interest include one or more of: a heart rate, heart rate variability, blood oxygenation level, breathing rate, movement, temperature, and vocal sounds.
The modular system of claim 17 , wherein the paternal subset of the plurality of parameters of interest include one or more of: an activity level, a sleep quality, a stress level, an oxygen saturation level, a cardiorespiratory fitness level, a heart rate, and a heart rate variability.
The modular system of claim 1 , wherein the modular system is configured for use with a plurality of users and to identify each of the plurality of users based on an identification of the accessory coupled to the housing.
A system for measuring health parameters of a user, the system comprising: a plurality of sensors for measuring a plurality of parameters of interest of a user; a coupling element for coupling the system to an accessory worn by or positionable proximate the user; and a processor communicatively coupled to the plurality of sensors, wherein the processor analyzes a plurality of sensor outputs from the plurality of sensors and automatically determines a type of the accessory coupled to the system based on the analyzed plurality of sensor outputs.
a plurality of sensors for measuring a plurality of parameters of interest of a user;
a coupling element for coupling the system to an accessory worn by or positionable proximate the user; and
a processor communicatively coupled to the plurality of sensors, wherein the processor analyzes a plurality of sensor outputs from the plurality of sensors and automatically determines a type of the accessory coupled to the system based on the analyzed plurality of sensor outputs.
wherein the processor analyzes a plurality of sensor outputs from the plurality of sensors and automatically determines a type of the accessory coupled to the system based on the analyzed plurality of sensor outputs.
The system of claim 22 , wherein the plurality of parameters of interest of the user includes one or more of: a maternal activity level, maternal sleep quality, maternal stress level, maternal oxygen saturation level, maternal cardiorespiratory fitness level, maternal heart rate, maternal heart rate variability, maternal electrohysterography signal, maternal uterine activity, maternal uterine contractions, maternal heart electrical activity, paternal activity level, paternal sleep quality, paternal stress level, paternal oxygen saturation level, paternal cardiorespiratory fitness level, paternal heart rate, paternal heart rate variability, paternal heart electrical activity, fetal movement, fetal heart electrical activity, fetal heart sound, fetal heart beat, fetal heart rate, fetal heart rate variability, an amount of amniotic fluid, placental oxygenation, placental temperature, placental pH, fetal breathing, fetal position, fetal orientation, fetal distress, fetal breathing movement, newborn heart rate, newborn blood oxygenation level, newborn breathing rate, newborn movement, newborn temperature, and newborn vocal sounds.
Ref US20180108440A1: Claims:
A system for receiving and transducing biological events into electrical signals and diagnosing a medical condition based thereon, the system comprising: a sensor array comprising a vibro-acoustic sensor for measuring body sounds of a target living organism and a bio-electric sensor for measuring a bio-electric signal of the target living organism; a processor; and a machine learning module, executable by the processor and trained on signals characteristic of the sensor array, the machine learning module receiving signals from the sensors and, based on the training, outputting a probability indicative of a physiological condition.
a sensor array comprising a vibro-acoustic sensor for measuring body sounds of a target living organism and a bio-electric sensor for measuring a bio-electric signal of the target living organism;
a processor; and
a machine learning module, executable by the processor and trained on signals characteristic of the sensor array, the machine learning module receiving signals from the sensors and, based on the training, outputting a probability indicative of a physiological condition.
The system of claim 1 , wherein the physiological condition is a biomarker.
The system of claim 1 , wherein the sensor array further comprises one or more sensors for measuring at least one environmental stimulus or condition.
The system of claim 3 , wherein the at least one environmental stimulus or condition is at least one of skin temperature, ambient temperature, barometric pressure, 9-axis motion geolocation, location-dependent real-time weather conditions, galvanic skin response, or pollution.
The system of claim 1 , wherein the sensor array comprises at least one sensor for measuring at least one of wavelength transmittance/absorbance, oxygen saturation, ambient skin temperature, core temperature, ACG, BCG, VCG, EKG, EMG, EOG, EEG, VOC excretion or vocal tonal inflection.
The system of claim 1 , wherein the sensor array further comprises an optical sensor.
The system of claim 1 , further comprising a database of longitudinal health records, the health record of a target living organism being monitored by the sensors providing an input to the machine learning module.
The system of claim 1 , wherein the machine learning module is a neural network.
The system of claim 8 , wherein the neural network is a recurrent neural network.
The system of claim 8 , wherein the neural network is a feedforward neural network.
The system of claim 8 , wherein the neural network is an ensemble of neural networks.
The system of claim 1 , wherein the vibro-acoustic sensor and the bio-electric sensor each produce time-varying signals, the signals received by the machine learning module from the vibro-acoustic sensor and the bio-electric sensor being time-synchronized.
The system of claim 12 , wherein the signals are received by the machine learning module as catenated raw amplitude sequences.
The system of claim 12 , wherein the signals are received by the machine learning module as combined short-time Fourier transform spectra.
The system of claim 1 , wherein the sensor array is connected by wires.
The system of claim 1 , wherein the sensor array communicates wirelessly.
The system of claim 1 , wherein the machine learning module is remote from the sensors and in communication therewith via a network.
The system of claim 1 , further comprising at least one acoustic stimulus generators.
Ref WO2014162135A1: Claims:
Fetal movement monitoring apparatus comprising:
a first sensor device arranged to be applied to a mother's abdomen for detection of fetal movements and to output a signal comprising one or more record of said fetal movements;
a second sensor device by which a user can input a record of perceived fetal movements; and
one or more processor under the control of machine readable instructions arranged to compare the output of the first sensor device and the user's input via the second sensor device and to output a log of fetal movements over time based upon said comparison.
Apparatus according to claim 1 , wherein the first sensor device comprises a deflection sensor arranged to sense deflections in the mother's abdomen indicative of a fetal movement.
Apparatus according to claim 1 or 2, wherein the first sensor device comprises a piezoelectric or piezoresistive sensor component.
Apparatus according to any preceding claim wherein the first sensor device comprises a plurality of fetal movement sensors arranged at spaced locations and/or different relative orientations.
Apparatus according to any preceding claim wherein the first sensor device comprises a patch comprising an adhesive material for adhering the patch to the mother's abdomen.
Apparatus according to any preceding claim, wherein the first sensor device comprises an intelligent textile material to be worn by the mother in the abdominal region, the stress/strain in said textile material being sensed to provide an indication of fetal movement.
Apparatus according to any preceding claim, wherein the second sensor device comprises a tactile sensor and a timer or clock, which may be synchronised with a corresponding timer or clock in the first sensor device.
Apparatus according to claim 7, wherein the second sensor device comprises a user interface device, separate from the first sensor device and arranged for data communication therewith, the user interface device having one or more processors for processing of the sensor signals.
Apparatus according to claim 8, wherein the user interface device has a display and the one or more processors control output of prompts to the user to commence input of perceived maternal movements using the device.
Apparatus according to any preceding claim, wherein the first sensor device comprises any, or any combination, of an amplifier, bandpass filter, analogue-to- digital converter and/or data sampler.
1 . Apparatus according to any preceding claim, comprising a further sensor in the form of a maternal movement sensor, the further sensor being different to the first or second sensor and being arranged to sense coarse maternal movement.
Apparatus according to claim 1 1 , wherein the maternal movement sensor is arranged to be applied to the mother's skin, or worn by the mother, for example as part of the first sensor device.
Apparatus according to claim 1 1 or claim 12, wherein the maternal movement sensor comprises an accelerometer.
Apparatus according to any one of claims 1 1 to 13, wherein the one or more processor is arranged to compare a signal output from the maternal movement sensor with the input via the second sensor device and/or the signal output from the first sensor device and to output the log of fetal movements over time based upon said comparison.
Apparatus according to claim 14, wherein the processor is arranged to process the signal output from the first sensor device and to accept or record or reject an instance of fetal movement in dependence upon a concurrent sensed level of maternal activity.
Apparatus according to any preceding claim, wherein the comparison performed by the processor comprises comparing the time and/or magnitude of any records or signals.
Apparatus according to any preceding claim, wherein the log of fetal movements comprises a summation or count of fetal movements over a
predetermined time period.
Apparatus according to any preceding claim, wherein the processor compares the log of fetal movements to one or more predetermined threshold value, such as a predetermined count or rate of fetal movement and/or a predetermined rate of change of fetal movement and outputs a signal indicative of abnormal fetal movement if the log of fetal movement meets or passes said one or more predetermined threshold value.
Apparatus according to claim 18, wherein the threshold value is a variable which varies according to a predetermined trend and/or in response to previous logs of fetal movement.
Apparatus according to any preceding claim, wherein the processor determines a confidence value associated with the signal output from the first sensor device based on the user's input via the second sensor device.
Apparatus according to any preceding claim, wherein the processor has a first or learning mode of operation in which it compares the user's input via the second sensor device with the signal output from the first sensor device and a 

 second or normal mode of operation, in which the processor processes only the signal output from the first sensor device.
Apparatus according to any preceding claim, further comprising a transmitter for transmitting the log of fetal activity or an alert signal derived therefrom to a remote location.
A method of monitoring fetal movement comprising:
obtaining or receiving a signal comprising a first record of fetal movements from a first sensor device applied to a mother's abdomen;
obtaining or receiving a second record of perceived fetal movements manually input by a user for a time period concurrent with the first record of fetal movement; and
using one or more processor under the control of machine readable instructions to compare the first and second records and to output a log of fetal movements over time based upon said comparison.
A method according to claim 23, wherein the user is the mother.
A data carrier comprising machine readable instructions for the control of one or more processors to:
receive a signal comprising a first record of fetal movements from a first sensor device applied to a mother's abdomen;
receive a second record of perceived fetal movements manually input by a user for a time period concurrent with the first record of fetal movement; and, compare the first and second records and output a log of fetal movements over time based upon said comparison.
Ref US20180000405: Claims:
1. A modular system for monitoring health parameters of a user, the modular system comprising:
a housing comprising: a plurality of sensors disposed on an outer surface of the housing or within the housing for measuring a plurality of parameters of interest; a processor disposed in the housing and communicatively coupled to the plurality of sensors; a coupling element positioned on the outer surface the housing for coupling the housing to an accessory; and an accessory identifier positioned on the housing or withi
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