Office Action 1: Non-Final Rejection (2024-06-13)
Rejection types: 101 - Patent-Eligible Subject Matter, 102 - Lack of Novelty, 103 - Obviousness, 112 - Written Description/Enablement

CLAIMS:
What is claimed is:

1\. A medical-device system, comprising:
a risk stratification circuit configured to:
receive physiological information sensed from the patient;
generate distinct first, second, and third signal metrics using the received physiological information;
calculate a primary pulmonary risk score using the first pulmonary signal metric, and calculate a secondary pulmonary risk score using the second and the third pulmonary signal metrics;
calculate a composite pulmonary risk score using the primary and the secondary pulmonary risk scores; and
an output circuit configured to provide the calculated composite pulmonary risk to a user or a process.
2\. The medical-device system of claim 1, comprising a physiological event detector circuit configured to automatically detect a cardiorespiratory event of the patient based at least in part on the calculated composite pulmonary risk score.
3\. The medical-device system of claim 2, wherein to automatically detect the cardiorespiratory event, the physiological event detector circuit is configured to:
calculate a cardiorespiratory event score using one or more physiological signals sensed from the patient;
determine or adjust an alert threshold based at in part on the calculated composite pulmonary risk score; and
generate an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold.
4\. The medical-device system of claim 2, wherein the cardiorespiratory event includes at least one of worsening heart failure (WHF), chronic obstructive pulmonary disease (COPD), asthma, or pulmonary edema.
5\. The medical-device system of claim 1, wherein the first, the second, and the third signal metrics are each selected from the group consisting of:
a respiration rate;
a ratio of respiration rate to tidal volume;
a third heart sound (S3) intensity;
a ratio of the S3 intensity to a reference heart sound intensity;
a heart rate;
a thoracic impedance; and
a physical activity level.
6\. The medical-device system of claim 1, wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition.
7\. The medical-device system of claim 6, wherein the second signal metric include a respiratory rate and the third signal metric incudes a physical activity intensity or duration, wherein the measurements of the second signal metric include respiratory rates measured during a time period when the physical activity intensity or duration exceeds a threshold.
8\. The medical-device system of claim 1, wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using the second signal metric weighted by the third signal metric.
9\. The medical-device system of claim 1, wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a linear or a nonlinear combination of the primary and secondary pulmonary risk scores.

10\. The medical-device system of claim 1, wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a neural network taking the primary and the secondary pulmonary risk scores as input.

11\. The medical-device system of claim 1, wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score further using a classification of chronic obstructive pulmonary disease (COPD) stages one through four.

12\. The medical-device system of claim 1, comprising a therapy circuit configured to initiate or adjust a therapy to treat a cardiorespiratory disease in accordance with the calculated composite pulmonary risk score.

13\. A method, comprising:
receiving physiological information sensed from the patient;
generating, via a risk stratification circuit of a medical-device system, distinct first, second, and third signal metrics using the received physiological information;
calculating, via the risk stratification circuit, a primary pulmonary risk score using the first pulmonary signal metric, and calculate a secondary pulmonary risk score using the second and the third pulmonary signal metrics;
calculating, via the risk stratification circuit, a composite pulmonary risk score using the primary and the secondary pulmonary risk scores; and
providing, via an output circuit, the calculated composite pulmonary risk to a user or a process.

14\. The method of claim 13, further comprising automatically detecting a cardiorespiratory event of the patient based at least in part on the calculated composite pulmonary risk score, the cardiorespiratory event including at least one of worsening heart failure (WHF), chronic obstructive pulmonary disease (COPD), asthma, or
pulmonary edema.

15\. The method of claim 14, wherein automatically detecting the cardiorespiratory even includes:
calculating a cardiorespiratory event score using one or more physiological signals sensed from the patient;
determining or adjusting an alert threshold based at in part on the calculated composite pulmonary risk score; and
generating an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold.

16\. The method of claim 13, wherein calculating the secondary pulmonary risk score includes using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition.

17\. The method of claim 13, wherein calculating the secondary pulmonary risk score includes using the second signal metric weighted by the third signal metric.

18\. The method of claim 13, wherein calculating the composite pulmonary risk score includes using a neural network taking the primary and the secondary pulmonary risk scores as input.

19\. The method of claim 13, wherein calculating the composite pulmonary risk score further using a classification of chronic obstructive pulmonary disease (COPD) stages one through four.

20\. The method of claim 13, further comprising initiating or adjusting a therapy to treat a cardiorespiratory disease in accordance with the calculated composite pulmonary risk score. 40 41 42 43

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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b)  CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA  35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 13 recites the limitation the first pulmonary signal metric and “the second and the third pulmonary signal metrics” in the claims.  There is insufficient antecedent basis for these limitations in the claims. It is not clear whether the signal metrics (or the physiological information) should be pulmonary signal metrics and/or whether the physiological information should be pulmonary information.
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, 5-6, 8-13, and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the process of using a mathematical formula to output a pulmonary risk score. This judicial exception is not integrated into a practical application because the calculation is merely output such as the case in Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above, the inputs to this formula are well-known and conventional metrics, further analogous to Electric Power. Evidence that such additional elements are well-known and convention is shown by the publications cited herein. The use of a neural network as claimed in claim 18 is insufficient to transform the abstract idea into eligible subject matter given that this neural network is still another calculation using well-known and conventional techniques to arrive at a mathematical answer that is a pulmonary risk score.  Moreover, simply providing therapy based on a calculated metric is no more than routine and conventional techniques that fail to integrate the abstract idea into a practical application given that there does not appear to be any language in the claim that particularly links the abstract idea to the further limitations.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA  35 U.S.C. 102 and 103 (or as subject to pre-AIA  35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA  to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 5, 12, and 20  is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2012/0157799 A1 to Patangay et al. (“Patangay”).
As to claim 1, Patangay discloses a medical-device system, comprising:
a risk stratification circuit configured to:
receive physiological information sensed from the patient (see Fig 3, element 300);
generate distinct first, second, and third signal metrics using the received physiological information (see Fig 3, elements 430A, 440A, and 440B, respectively);
calculate a primary pulmonary risk score using the first pulmonary signal metric (see Fig 4, element 433 – note that other scores may be used when calculating the first pulmonary risk score given that the open-ended “comprising” is used in the claim), and calculate a secondary pulmonary risk score using the second and the third pulmonary signal metrics (see Fig 4, element 443);
calculate a composite pulmonary risk score using the primary and the secondary pulmonary risk scores (see Fig 4, element 450) ; and
an output circuit configured to provide the calculated composite pulmonary risk to a user or a process (see Fig 3, element 335 and [0046])
As to claims 5, Patangay further discloses wherein the first, the second, and the third signal metrics are each selected from the group consisting of: a respiration rate; a ratio of respiration rate to tidal volume; a third heart sound (S3) intensity; a ratio of the S3 intensity to a reference heart sound intensity; a heart rate; a thoracic impedance; and a physical activity level (see [0040]-[0042]).
As to claims 12 and 20, Patangay further discloses a therapy circuit configured to initiate or adjust a therapy to treat a cardiorespiratory disease in accordance with the calculated composite pulmonary risk score (see [0045]).
Claim 13 is rejected for the reasons provided in the treatment of claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA  35 U.S.C. 102 and 103 (or as subject to pre-AIA  35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA  to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary.  Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 2, 4, 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patangay in view of US 2008/0183085 A1 to van Oort et al. (“van Oort”).
As to claims 2, Patangay fails to disclose wherein the system further comprises a physiological event detector circuit configured to automatically detect a cardiorespiratory event of the patient based at least in part on the calculated composite pulmonary risk score.
However, van Oort discloses a similar system and further teaches a physiological event detector circuit configured to automatically detect a cardiorespiratory event of the patient based at least in part on a calculated health risk in several health categories, many of which include pulmonary risk (see, e.g., [0028], [0032], [0037], [0044], and [0049]). It would have been obvious to one of ordinary skill in the art to combine the pulmonary risk score of Patangay with the automatic detection of cardiorespiratory events of a patient as taught by van Oort in order to achieve the predictable result of allowing the device to store higher resolution data that may be particularly relevant for a health care clinician and/or delivering particular therapies to the user based on the more detailed monitoring caused by increased risk determination.
As to claims 4 and 14 (see treatment of claim 2 for other limitations), van Oort further discloses wherein the cardiorespiratory event includes at least one of worsening heart failure (WHF), chronic obstructive pulmonary disease (COPD), asthma, or pulmonary edema (see [0013]).
Claim(s) 8-9 and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patangay and further in view of US 2013/0116578 A1 to An et al. (“An”).
As to claims 8 and 17, it does not appear that either Patangay discloses wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using the second signal metric weighted by the third signal metric.
However, in a similar invention, An teaches that a first signal metric may be used to influence (i.e., weight) of another signal metric when combining the two to signal an alert (i.e. a score that reaches a particular threshold for sounding an alarm) (see, e.g., [0194] – “In an illustrative example, the first physiological parameter may be the amplitude of the S3 heart sound and the second physiological parameter may be fluid status of the subject that is derived from intrathoracic impedance. Decreasing intrathoracic impedance may indicate fluid retention. Based on the measured S3 amplitude, the risk analysis module 3005 may assign a higher risk to the subject. The risk analysis module 3005 may then lower the value of an intrathoracic impedance threshold used by the WHF detection module 3010 to increase the sensitivity of prediction of a WHF event. If the risk analysis module 3005 does not identify an S3 heart sound in the heart sound signal, the risk analysis module 3005 may raise the value of an intrathoracic impedance threshold used by the WHF detection module 3010 to decrease the sensitivity of prediction of an HF event.”)(emphasis added).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the calculation of the second pulmonary risk score of Patangay as taught by An in order to achieve the predictable result of lowering false positives and/or reducing false negatives by adjusting the weights to better reflect a user’s health condition as taught by An.
As to claim 9, Patangay fails to disclose wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a linear or a nonlinear combination of the primary and secondary pulmonary risk scores.
However, An discloses such a combination for calculating a related composite health score (see [0061]-[0065]). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the linear combination as taught by An given that An teaches that such a composite score allows its user to weight symptoms and signs in such a way as to emphasize those factors that are most important to patient health.
As to claims 10 and 18, Patangay fails to disclose wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a neural network taking the primary and the secondary pulmonary risk scores as input.
However, An discloses such a risk stratification circuit that uses a neural network in a similar fashion (see [0174]). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of Patangay with the neural network of An given that neural networks were well-known for the advantage of automatically learning and extracting relevant features from raw sensor data, reducing the need for manual feature engineering.
Claim(s) 3 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patangay in view of van Oort and further in view An.
As to claims 3 and 15, neither Patangay nor van Oort discloses wherein to automatically detect the cardiorespiratory event, the physiological event detector circuit is configured to:
calculate a cardiorespiratory event score using one or more physiological signals sensed from the patient;
determine or adjust an alert threshold based at in part on the calculated composite pulmonary risk score; and
generate an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold.
However, in a related invention, An discloses wherein the physiological event detector circuit is configured to:
calculate a cardiorespiratory event score using one or more physiological signals sensed from the patient (see [0193] – “The risk analysis module 3005 may adjust the detection threshold criterion to make the detection more sensitive or less sensitive to detection according to the determined HF risk score.”);
determine or adjust an alert threshold based at in part on the calculated composite pulmonary risk score (see [0193]); and
generate an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold (see [0193]).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the pulmonary risk score and event detection of Patangay/van Oort with the threshold modification based on a calculated composite pulmonary risk score in order to achieve the predictable result of increasing sensitivity of the event detection.
Claim(s) 6-7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patangay in view of van Oort and further in view of US 2014/0243690 A1 to Dumont et al. (“Dumont”).
As to claims 6 and 16, it does not appear that either Patangay or van Oort discloses wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition.
However, in a related disclosure, Dumont teaches that decision trees may be constructed that operate in a Boolean decision tree that calculates risk scores (see Fig 1 – alert/no alert is a binary score, but still a score) using measurements of one metric obtained at time when another metric satisfies a specified condition (see Fig 1 and [0058]-[0063]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teachings of Dumont in the systems of Patangay/van Oort to calculate the secondary pulmonary risk score using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition in order to achieve the predictable result of reducing false positives and increasing true negatives by finding the proper combinations of thresholds and signal metrics that are most powerful.
As to claim 7, Dumont further discloses wherein the second signal metric include a respiratory rate and the third signal metric incudes a physical activity intensity or duration, wherein the measurements of the second signal metric include respiratory rates measured during a time period when the physical activity intensity or duration exceeds a threshold (see Fig 1 and [0058]-[0063]).
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 .
Interview Request in Reply Filed August 12, 2024
Examiner acknowledges the request for interview in the reply filed August 12, 2024. Where a complete reply to a first action includes a request for an interview, the examiner, after consideration of the reply, should grant such an interview request if it appears that the interview would result in expediting the allowance of the application. MPEP 713.01. After consideration of the reply, it does not appear that an interview would expedite allowance given the nature of the rejections of both Sections 101 and 103.
Election/Restrictions
Newly submitted claims 21-22 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
I. Claims 1-10 and 12, drawn to a medical device system for calculating and providing a pulmonary risk score, classified in 600/529.
II. Claims 13-18, drawn to a method of calculating and providing a pulmonary risk score, classified in 600/529.
III. Claims 21-22, drawn to a medical device system for calculating a pulmonary risk score and detecting a cardiorespiratory risk, classified in 600/484.
Invention I and III are directed to related products. The related inventions are distinct if: (1) the inventions as claimed are either not capable of use together or can have a materially different design, mode of operation, function, or effect; (2) the inventions do not overlap in scope, i.e., are mutually exclusive; and (3) the inventions as claimed are not obvious variants.  See MPEP § 806.05(j). In the instant case, the inventions have a materially different effect in that no specific event is determined in Invention I. In addition, there is nothing that is output in invention III.  Furthermore, the inventions as claimed do not encompass overlapping subject matter and there is nothing of record to show them to be obvious variants.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 21-22 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA  35 U.S.C. 103(a) of the other invention.
Claim Objections
Claims 1 and 13 are objected to because of the following informalities: In the penultimate line of each claim, “pulmonary risk” should be changed to “pulmonary risk score.”
Claim 3 is objected to because of the following informalities: In line 5 of the claim, it appears that “based at in part” should be changed to “based at least in part.”  Appropriate correction is required.
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, 5-6, 8-13, and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the process of using a mathematical formula to output a pulmonary risk score. This judicial exception is not integrated into a practical application because the calculation is merely output such as the case in Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above, the inputs to this formula are well-known and conventional metrics, further analogous to Electric Power. Evidence that such additional elements are well-known and convention is shown by the publications cited herein. The use of a neural network as claimed in claim 18 is insufficient to transform the abstract idea into eligible subject matter given that this neural network is still another calculation using well-known and conventional techniques to arrive at a mathematical answer that is a pulmonary risk score.  Moreover, simply providing therapy based on a calculated metric is no more than routine and conventional techniques that fail to integrate the abstract idea into a practical application given that there does not appear to be any language in the claim that particularly links the abstract idea to the further limitations.
In keeping with the requirement that all claims be considered as a whole, Examiner notes that several claims have not been rejected under Section 101. As an example, claim 3 is not rejected because it includes the limitation wherein the physiological detection circuit is configured to determine or adjust an alert threshold based at least in part on the calculated composite pulmonary risk score. This has an effect of technological improvement as one of ordinary skill in the art would appreciate that the composite pulmonary risk score is being used to adjust the operation of the machine itself by determining or adjusting alert thresholds. This has the effect of making the device more responsive to the needs of the user by at least reducing false positive alerts. Moreover, such a configuration must take in as an input the current state of the user, much like the rubber molding press in Diamond v. Diehr, 450 U.S. 175 (1981) (holding patentable a process that iteratively computed a cure time using a mathematical formula to control the physical process of transforming rubber). These additional elements in, for example, claim 3 amount to significantly more than the judicial exception such that it is integrated into a practical application.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA  35 U.S.C. 102 and 103 (or as subject to pre-AIA  35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA  to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4, 12-14, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2011/0040713 A1 to Colman et al. (“Colman”).
As to claim 1, Colman discloses a medical-device system, comprising:
a risk stratification circuit configured to:
receive physiological information sensed from a patient;
generate distinct first, second, and third signal metrics using the received physiological information (see Fig 4A, elements 170A, 170B, and 176 and [0105], [0115]-[0116] – “According to some exemplary embodiments, the parameters used may include, for example, parameters, such as: EtCO2, Respiratory Rate (RR), Heart Rate (HR), SpO2, blood pressure, spirometry, relative flow parameters, CO2 waveform patterns, blood gas, and the like.” See also [0135] --  “The additional parameters (factors) may include various patient specific parameters that may be characteristic of the patient, such as, for example, blood pressure, age, medical condition, sedation, patient awake, patient asleep, and the like. For example, an additional parameter (factor), such as, for example, additional parameter (factor) 176 may enter into one or more of the characterization processes and may thus control/tune the membership functions and membership value for each Output Characteristic Group that result from the characterization process.”);
calculate a primary pulmonary risk score using the first signal metric, and calculate a secondary pulmonary risk score using the second and the third signal metrics (see Fig 4A, elements 170A-B, 172A-B, 176), the primary pulmonary risk score and the secondary pulmonary risk score each taking a numerical value (see [0135] – “In the characterization process, the respective membership value to each characteristic group (such as groups 173A-C) is calculated/computed/assigned. The characteristic groups may be labeled, for example, as: “Normal”, “High”, “Low”, “Very High”, “Very Low”, and the like [Examiner notes that such processes, by their nature, will be given numerical values given that computers process data numerically] The same process may be applied onto any number of input main parameters, such as, for example, input parameter 170B, which may be characterized by characterization process 172B, where the respective membership value to each characteristic group (such as groups 173D-F) is calculated.”); and
calculate a composite pulmonary risk score using the primary and the secondary pulmonary risk scores (see Fig 4A, element 175 and [0135]); and
an output circuit configured to provide the calculated composite pulmonary risk to a user or a process (see [0142], [0146] and Fig 6A, elements 204, 206).
As to claim 2, Colman further discloses a physiological event detector circuit configured to automatically detect a cardiorespiratory event of the patient based at least in part on the calculated composite pulmonary risk score (see [0096]).
As to claims 4 and 14, Colman further discloses wherein the cardiorespiratory event includes at least one of worsening heart failure (WHF), chronic obstructive pulmonary disease (COPD), asthma, or pulmonary edema (see [0102]).
As to claim 12 and 20, Colman further discloses a therapy circuit configured to initiate or adjust a therapy to treat a cardiorespiratory disease in accordance with the calculated composite pulmonary risk score (see [0036]).
Claim 13 is rejected for the reasons provided in treatment of claim  1.
Claim(s) 3, 8-10, 15, and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Colman in view of  US 2013/0116578 A1 to An et al. (“An”).
As to claims 3 and 15, Colman does not appear to disclose wherein to automatically detect the cardiorespiratory event, the physiological event detector circuit is configured to:
calculate a cardiorespiratory event score using one or more physiological signals sensed from the patient;
determine or adjust an alert threshold based at in part on the calculated composite pulmonary risk score; and
generate an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold.
However, in a related invention, An discloses wherein the physiological event detector circuit is configured to:
calculate a cardiorespiratory event score using one or more physiological signals sensed from the patient (see [0193] – “The risk analysis module 3005 may adjust the detection threshold criterion to make the detection more sensitive or less sensitive to detection according to the determined HF risk score.”);
determine or adjust an alert threshold based at in part on the calculated composite pulmonary risk score (see [0193]); and
generate an alert of the cardiorespiratory event when the cardiorespiratory event score exceeds the alert threshold (see [0193]).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the pulmonary risk score and event detection of Colman with the threshold modification based on a calculated composite pulmonary risk score in order to achieve the predictable result of increasing sensitivity of the event detection.
As to claims 8 and 17, it does not appear that Colman discloses wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using the second signal metric weighted by the third signal metric.
However, in a similar invention, An teaches that a first signal metric may be used to influence (i.e., weight) of another signal metric when combining the two to signal an alert (i.e. a score that reaches a particular threshold for sounding an alarm) (see, e.g., [0194] – “In an illustrative example, the first physiological parameter may be the amplitude of the S3 heart sound and the second physiological parameter may be fluid status of the subject that is derived from intrathoracic impedance. Decreasing intrathoracic impedance may indicate fluid retention. Based on the measured S3 amplitude, the risk analysis module 3005 may assign a higher risk to the subject. The risk analysis module 3005 may then lower the value of an intrathoracic impedance threshold used by the WHF detection module 3010 to increase the sensitivity of prediction of a WHF event. If the risk analysis module 3005 does not identify an S3 heart sound in the heart sound signal, the risk analysis module 3005 may raise the value of an intrathoracic impedance threshold used by the WHF detection module 3010 to decrease the sensitivity of prediction of an HF event.”)(emphasis added).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the calculation of the second pulmonary risk score of Colman as taught by An in order to achieve the predictable result of lowering false positives and/or reducing false negatives by adjusting the weights to better reflect a user’s health condition as taught by An.
As to claim 9, Colman fails to disclose wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a linear or a nonlinear combination of the primary and secondary pulmonary risk scores.
However, An discloses such a combination for calculating a related composite health score (see [0061]-[0065]). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the linear combination as taught by An given that An teaches that such a composite score allows its user to weight symptoms and signs in such a way as to emphasize those factors that are most important to patient health.
As to claims 10 and 18, Colman fails to disclose wherein the risk stratification circuit is configured to calculate the composite pulmonary risk score using a neural network taking the primary and the secondary pulmonary risk scores as input.
However, An discloses such a risk stratification circuit that uses a neural network in a similar fashion (see [0174]). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of Colman with the neural network of An given that neural networks were well-known for the advantage of automatically learning and extracting relevant features from raw sensor data, reducing the need for manual feature engineering.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Colman in view of  US 2012/0157799 A1 to Patangay et al. (“Patangay”).
As to claim 5, while Colman discloses that many of the claimed parameters (see [0007] – “In addition to CO2 concentration, various other parameters may be indicative (directly or indirectly) of the ventilation (respiratory) status of a patient. Such parameters may include, for example, saturation of oxygen in the blood cells and other organs, heart rate, respiration rate, breath flow rate, blood pressure, and the like. Combinations of various parameters may yield an improved indication of the clinical condition of the patient, in general, and of the ventilatory status of the patient, in particular.”), it is not clear that the first, the second, and the third signal metrics are each selected from the group consisting of: a respiration rate; a ratio of respiration rate to tidal volume; a third heart sound (S3) intensity; a ratio of the S3 intensity to a reference heart sound intensity; a heart rate; a thoracic impedance; and a physical activity level.
However, in a related cardiorespiratory metric determination invention, Patangay discloses these metrics (see [0042]). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the respiratory metric determination of Colman with the parameters disclosed by Patangay given that Patangay teaches that they are indicative of patient cardiorespiratory health.
Claim(s) 6-7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Colman in view of US 2014/0243690 A1 to Dumont et al. (“Dumont”).
As to claims 6 and 16, it does not appear that either Colman discloses wherein the risk stratification circuit is configured to calculate the secondary pulmonary risk score using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition.
However, in a related disclosure, Dumont teaches that decision trees may be constructed that operate in a Boolean decision tree that calculates risk scores (see Fig 1 – alert/no alert is a binary score, but still a score) using measurements of one metric obtained at time when another metric satisfies a specified condition (see Fig 1 and [0058]-[0063]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teachings of Dumont in the systems of Colman to calculate the secondary pulmonary risk score using measurements of the second signal metric obtained at times when the third signal metric satisfies a specified condition in order to achieve the predictable result of reducing false positives and increasing true negatives by finding the proper combinations of thresholds and signal metrics that are most powerful.
As to claim 7, Dumont further discloses wherein the second signal metric include a respiratory rate and the third signal metric incudes a physical activity intensity or duration, wherein the measurements of the second signal metric include respiratory rates measured during a time period when the physical activity intensity or duration exceeds a threshold (see Fig 1 and [0058]-[0063]).
Response to Arguments
Applicant's arguments filed August 12, 2024 have been fully considered but they are not persuasive.
As to the arguments in favor of eligibility under Section 101, Applicants argue that the inventions of claims 1, 5-6, 8-13, and 16-20 amount to an improvement in technology and are therefore eligible under the Alice/Mayo test. Applicants argue that the improvement is in the field of computerized, device-based patient monitoring and pulmonary risk management. Applicants describe the features of the invention as allowing the device to be turned off when the patient as low pulmonary risk as well as back on when the patient has high pulmonary risk. A more accurate composite pulmonary risk assessment would lead to improved accuracy of risk-based pulmonary disease detection. Further, because pulmonary disease detection can be turned on when high pulmonary risk is indicated, using the pulmonary risk assessment can help save battery power and conserve computing resources, thereby improving the functionality of the medical-device system.
These arguments are respectfully found not persuasive for at least two reasons.
First, a more accurate composite risk assessment is an insufficient reason to convey subject matter eligibility. Examiner has concluded that the judicial exception in the inventions of claims 1, 5-6, 8-13, and 16-20 is the computation of a pulmonary risk score. That such a score results in an improvement in the assessment of pulmonary risk that is sufficient to confer patentability is at odds at least in the conclusion reached in Parker v. Flook, 437 U.S. 584, 598, n. 18 (“…[the patentee’s] process patent rests solely on the claim that his mathematical algorithm, when related to a computer program, will improve the existing process for updating alarm units. Very simply, our holding today is that a claim for an improved method of calculation, even when tied to a specific end use, is unpatentable subject matter under § 101”) (emphasis added). Here, Applicants have failed to identify a technological problem that the claimed invention addresses that is of the type that has been found eligible by the courts.
In reviewing the pertinent precedent out of the Federal Circuit, the “technological improvement” argument has been successful in very different scenarios than at issue here. In DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245 (Fed. Cir. 2014), the problem was unique to e-commerce in that it concerned the tendency for users to “click-away” from a merchant’s site. The eligible patent solved this problem by modifying the website interface to retain consumers. In BASCOM Global Internet Services, Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016), the problem was unique to content filtering over the internet and allowed for customizable filtering at a specific network location, such as a particular ISP, that would be less susceptible to circumvention by a user. By making the filter more dynamic and efficient, the software-based invention improved the performance of the computer itself. In Data Engine Technologies LLC v. Google LLC, 906 F.3d 999 (Fed. Cir. 2018), the problem was unique to navigation through prior art three-dimensional or multipage electronic spreadsheets. The eligible patent solved the problem in a particular way by providing an intuitive, user-friendly interface with familiar notebook tabs for navigating the three-dimensional worksheet environment.
As summarized above, Applicants argue that the technology improvement is in the field of computerized, device-based patient monitoring and pulmonary risk management. A more accurate composite pulmonary risk assessment, Applicants further argue, would lead to improved accuracy of risk-based pulmonary disease detection. The problem with this framing of the issue is that the benefits of the composite pulmonary indicator are independent of any technological use case. In other words, whether or not the pulmonary risk score was used in a patient monitor, its salient benefit would still be the same. A doctor could independently calculate this score based on medical records alone and the result would still be the same—an assessment of medical risk for the patient. For at least this reason, the claims cannot be said to be a technological improvement of the type that would confer patent eligibility.
Second, while there are several examples offered by Applicants as to why the claimed invention is a technological improvement, none of these benefits are commensurate with the scope of claims 1, 5-6, 8-13, and 16-20. For example, Applicants argue that the device may be turned off or on depending on the patient risk. Setting aside the question of how the patient risk can be calculated by the monitor when it is turned off, these features are nowhere to be found in the text of claims 1 and 13. Claim 1 is illustrative of this point. It comprises two circuits. One to calculate the risk and another to output it. There is little in the text of the claims that would realize the advantages proposed by Applicants. Applicants further argue that the score uses a unique combination of primary and secondary risk scores each computed using distinct signal metrics. But close scrutiny of the claims finds little “distinct” or “unique” about the metrics or risks scores claimed here. Given that they are only tethered to “physiological information,” the metrics embrace almost any information related to patient health. Similarly, it is difficult to understand how these scores may be unique without any distinguishing text. In short, the claims are insufficiently aligned with the features pointed out in Applicants’ remarks. For at least this reason, the arguments are found not persuasive to finding patent eligibility. Accordingly, the rejection of claims 1, 5-6, 8-13, and 16-20 under Section 101 are maintained.
As to the art rejections, Applicants’ arguments are moot in view of the newly applied rejections.
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.

CITED REFERENCE SUMMARIES: Ref US20120157799A1: Claims:
An apparatus comprising: a processor circuit configured to: receive an indication of cardiac filling pressure of a subject; receive an indication of thoracic fluid status of the subject; receive an indication of cardiac output of the subject; classify the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states; classify the indication of thoracic fluid status into one of at least first and second thoracic fluid status states; classify the indication of cardiac output into one of at least first and second cardiac output states; and generate a multi-dimensional heart failure decompensation status indicator using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output.
a processor circuit configured to: receive an indication of cardiac filling pressure of a subject; receive an indication of thoracic fluid status of the subject; receive an indication of cardiac output of the subject; classify the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states; classify the indication of thoracic fluid status into one of at least first and second thoracic fluid status states; classify the indication of cardiac output into one of at least first and second cardiac output states; and generate a multi-dimensional heart failure decompensation status indicator using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output.
receive an indication of cardiac filling pressure of a subject;
receive an indication of thoracic fluid status of the subject;
receive an indication of cardiac output of the subject;
classify the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states;
classify the indication of thoracic fluid status into one of at least first and second thoracic fluid status states;
classify the indication of cardiac output into one of at least first and second cardiac output states; and
generate a multi-dimensional heart failure decompensation status indicator using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output.
The apparatus of claim 1 , wherein the multi-dimensional heart failure decompensation status alert comprises separate cardiac filling pressure, thoracic fluid status, and cardiac output dimensions.
The apparatus of claim 1 , comprising an ambulatory device comprising the processor circuit, wherein the ambulatory device comprises a sensor configured to detect the indication of cardiac filling pressure of a subject, the indication of thoracic fluid status of the subject, and the indication of cardiac output of the subject.
The apparatus of claim 3 , wherein the sensor is configured to detect one or any combination of the following cardiac filling pressure indications: a S3 heart sound amplitude, a pulmonary arterial pressure, left ventricular end diastolic pressure, or a left atrial pressure.
The apparatus of claim 3 , wherein the sensor is configured to detect one or any combination of the following thoracic fluid status indications: thoracic impedance, a respiratory rate, a respiratory volume, a tidal volume, lung sound, or a lymphatic pressure or flow.
The apparatus of claim 3 , wherein the sensor is configured to detect one or any combination of the following cardiac output indications: a core temperature of the subject, a peripheral temperature of the subject, a systolic time interval, a pre-ejection period, a S1 amplitude, a pulmonary artery pressure, or an intracardiac impedance.
The apparatus of claim 1 , wherein the processor circuit is configured to receive or classify an indication of respiratory function, and to generate the multi-dimensional heart failure decompensation status alert using the classified indication of respiratory function, the multi-dimensional heart failure decompensation status alert comprising a separate respiratory function dimension.
The apparatus of claim 7 , comprising an ambulatory device comprising the processor circuit, wherein the ambulatory device comprises a sensor configured to detect the indication of cardiac filling pressure of a subject, the indication of thoracic fluid status of the subject, the indication of cardiac output of the subject, and the indication of respiratory function.
The apparatus of claim 1 , wherein the processor is configured to classify the indications of cardiac filling pressure, thoracic fluid status, and cardiac output into one of respective first and second states indicative of the severity of heart failure.
The apparatus of claim 1 , wherein the apparatus includes a therapy control circuit configured to provide a control signal adapted to adjust, initiate, or cease a therapy regimen using the multi-dimensional heart failure decompensation indication.
The apparatus of claim 1 , wherein the apparatus is coupled to an electronic medical database or memory storage device capable of storing a history of at least one of (1) the indications of cardiac filling pressure, thoracic fluid status, and cardiac output; or (2) the multi-dimensional heart failure decompensation indication.
The apparatus of claim 3 , wherein the processor is configured to compare at least one of the indications of cardiac filling pressure, thoracic fluid status, and cardiac output to information about at least a portion of the history.
The apparatus of claim 1 , wherein the processor is configured to obtain an indication of cardiac filling pressure of the subject and classifying the subject as hemodynamically stable or hemodynamically unstable therefrom; obtain an indication of thoracic fluid status of the subject and classifying the subject as dry or wet therefrom; obtain an indication of cardiac output of the subject and classifying the subject as warm or cold therefrom.
obtain an indication of cardiac filling pressure of the subject and classifying the subject as hemodynamically stable or hemodynamically unstable therefrom;
obtain an indication of thoracic fluid status of the subject and classifying the subject as dry or wet therefrom;
obtain an indication of cardiac output of the subject and classifying the subject as warm or cold therefrom.
A device-readable medium including instructions that, when performed by the device, comprise: obtaining an indication of cardiac filling pressure of a subject; obtaining an indication of thoracic fluid status of the subject; obtaining an indication of cardiac output of the subject; classifying the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states; classifying the indication of thoracic fluid status into one of at least first and second thoracic fluid status states; classifying the indication of cardiac output into one of at least first and second cardiac output states; and generating a multi-dimensional heart failure decompensation status alert using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output, the multi-dimensional heart failure decompensation status alert comprising separate cardiac filling pressure, thoracic fluid status, and cardiac output dimensions.
obtaining an indication of cardiac filling pressure of a subject;
obtaining an indication of thoracic fluid status of the subject;
obtaining an indication of cardiac output of the subject;
classifying the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states;
classifying the indication of thoracic fluid status into one of at least first and second thoracic fluid status states;
classifying the indication of cardiac output into one of at least first and second cardiac output states; and
generating a multi-dimensional heart failure decompensation status alert using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output, the multi-dimensional heart failure decompensation status alert comprising separate cardiac filling pressure, thoracic fluid status, and cardiac output dimensions.
A device-readable medium of claim 14 , wherein the instructions that, when performed by the device, comprise: obtaining an indication of respiratory function; classifying the indication of respiratory function into one of at least first and second respiratory function states; and wherein the generating the multi-dimensional heart failure decompensation status alert comprises using the classified indication of respiratory distress, wherein the multi-dimensional heart failure decompensation status alert comprises a separate respiratory function dimension.
obtaining an indication of respiratory function;
classifying the indication of respiratory function into one of at least first and second respiratory function states; and
wherein the generating the multi-dimensional heart failure decompensation status alert comprises using the classified indication of respiratory distress, wherein the multi-dimensional heart failure decompensation status alert comprises a separate respiratory function dimension.
A method comprising: obtaining an indication of cardiac filling pressure of a subject; obtaining an indication of thoracic fluid status of the subject; obtaining an indication of cardiac output of the subject; classifying the indication of cardiac filling pressure into one of at least first and second cardiac filling pressure states; classifying the indication of thoracic fluid status into one of at least first and second thoracic fluid status states; classifying the indication of cardiac output into one of at least first and second cardiac output states; and generating a multi-dimensional heart failure decompensation status indicator using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output.
generating a multi-dimensional heart failure decompensation status indicator using the classified indication of cardiac filling pressure, the classified indication of thoracic fluid status, and the classified indication of cardiac output.
The method of claim 16 , wherein the multi-dimensional heart failure decompensation status alert comprises using separate cardiac filling pressure, thoracic fluid status, and cardiac output dimensions.
The method of claim 16 , wherein the classifying the indication of cardiac filling pressure comprises using one or any combination of the following indications: a S3 heart sound amplitude, a pulmonary arterial pressure, right ventricular pressure, left ventricular pressure, or a left atrial pressure.
The method of claim 16 , wherein the classifying the indication of thoracic fluid status comprises using one or any combination of the following indications: a thoracic impedance, a respiratory rate, a minute ventilation, a tidal volume, a lung sound, a rapid shallow breathing index, or a lymphatic pressure or flow.
The method of claim 16 , wherein the classifying the indication of cardiac output comprises using one or any combination of the following indications: a core temperature of the subject, a peripheral temperature of the subject, a systolic time interval, a pre-ejection period, a S1 amplitude, a pulmonary artery pressure, or an intracardiac impedance.
The method of claim 16 , comprising: obtaining an indication of respiratory function; classifying the indication of respiratory function into one of at least first and second respiratory function states; and wherein the generating the multi-dimensional heart failure decompensation status alert comprises using the classified indication of respiratory distress, wherein the multi-dimensional heart failure decompensation status alert comprises a separate respiratory function dimension.
Ref US20080183085A1: Claims:
A method for use in an implantable medical device, comprising: storing a first threshold corresponding to detecting a first physiological event; sensing a first physiological signal corresponding to the first physiological event; detecting a plurality of the first physiological events in response to the first physiological signal and the first threshold; storing a second threshold different than the first threshold; determining, in response to detecting at least one of the plurality of the first physiological events, if the second threshold has been met; and enabling detailed monitoring of next ones of the detected plurality of the first physiological events in response to the second threshold being met.
storing a first threshold corresponding to detecting a first physiological event;
sensing a first physiological signal corresponding to the first physiological event;
detecting a plurality of the first physiological events in response to the first physiological signal and the first threshold;
storing a second threshold different than the first threshold;
determining, in response to detecting at least one of the plurality of the first physiological events, if the second threshold has been met; and
enabling detailed monitoring of next ones of the detected plurality of the first physiological events in response to the second threshold being met.
The method of claim 1 wherein the first physiological event corresponds to a first event category comprising a plurality of first physiological event types, and the detailed monitoring comprises monitoring the plurality of the first physiological event types.
The method of claim 1 wherein the detailed monitoring comprises storing a detection threshold for each of the plurality of the first physiological event types.
The method of claim 2 wherein monitoring the plurality of the first physiological event types comprises discriminating between the plurality of the first physiological event types in response to the first physiological signal.
The method of claim 2 wherein the detailed monitoring further comprises enabling sensing a second physiological signal and wherein monitoring the plurality of the first physiological event types includes detecting at least one of the plurality of the first physiological event types in response to the second physiological signal.
The method of claim 1 wherein the detailed monitoring comprises storing physiological signal data.
The method of claim 6 wherein the physiological signal data includes a snapshot of the first physiological signal.
The method of claim 2 further comprising: storing a third threshold corresponding to detecting a second physiological event; sensing a second physiological signal corresponding to the second physiological event, the second physiological event corresponding to a second event category comprising a plurality of second physiological event types; detecting a plurality of the second physiological events in response to the second physiological signal and the third threshold; storing a fourth threshold different than the third threshold; determining, in response to detecting at least one of the plurality of the second physiological events, if the fourth threshold has been met; and enabling detailed monitoring of next ones of the detected plurality of the second physiological events in response to the fourth threshold being met.
storing a third threshold corresponding to detecting a second physiological event;
sensing a second physiological signal corresponding to the second physiological event, the second physiological event corresponding to a second event category comprising a plurality of second physiological event types;
detecting a plurality of the second physiological events in response to the second physiological signal and the third threshold;
storing a fourth threshold different than the third threshold;
determining, in response to detecting at least one of the plurality of the second physiological events, if the fourth threshold has been met; and
enabling detailed monitoring of next ones of the detected plurality of the second physiological events in response to the fourth threshold being met.
The method of claim 8 wherein the detailed monitoring comprises storing physiological signal data upon detecting an event corresponding to one of the first event category and the second event category and further comprising: storing a priority for each of the first event category and the second event category; comparing the priority of one of the first and the second event categories corresponding to the detected event and the priority of the other of the first and the second event categories, and if the priority of the one of the first and the second event categories corresponding to the detected event is higher than the priority of the other of the first and the second event categories, overwriting previously stored physiological signal data corresponding to a previously detected event with physiological data corresponding to the detected event, the previously detected event corresponding to the other of the first and the second event categories.
storing a priority for each of the first event category and the second event category;
comparing the priority of one of the first and the second event categories corresponding to the detected event and the priority of the other of the first and the second event categories, and
if the priority of the one of the first and the second event categories corresponding to the detected event is higher than the priority of the other of the first and the second event categories, overwriting previously stored physiological signal data corresponding to a previously detected event with physiological data corresponding to the detected event, the previously detected event corresponding to the other of the first and the second event categories.
The method of claim 7 wherein the detailed monitoring further comprises: determining a severity index for each of a plurality of previously stored events corresponding to the other of the first and the second event categories; determining one of the plurality of previously stored events having a lowest severity index; and overwriting the one of the previously stored events having the lowest severity index with the physiological data corresponding to the detected event.
determining a severity index for each of a plurality of previously stored events corresponding to the other of the first and the second event categories;
determining one of the plurality of previously stored events having a lowest severity index; and
overwriting the one of the previously stored events having the lowest severity index with the physiological data corresponding to the detected event.
The method of claim 2 wherein the detailed monitoring comprises storing physiological signal data in memory in response to detecting an event and further comprising; storing a priority for each of the plurality of first physiological event types, comparing the priority of one of the plurality of the first physiological event types corresponding to the detected event and the priority of an other of the plurality of the first physiological event types, and if the priority of the one of the plurality of the first physiological event types corresponding to the detected event is higher than the priority of the other of the plurality of the first physiological event types, overwriting previously stored physiological signal data corresponding to a previously detected event with physiological signal data corresponding to the detected event, the previously detected event corresponding to the other of the plurality of the first physiological event types.
storing a priority for each of the plurality of first physiological event types,

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