Office Action 1: Non-Final Rejection (2022-12-27)
Rejection types: 102 - Lack of Novelty, 103 - Obviousness

CLAIMS:
WE CLAIM:
1\. A system for wireless vital sign monitoring, comprising:
a transmitter configured to transmit a wireless signal through a wireless channel of a venue;
a receiver configured to receive the wireless signal through the wireless channel, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue; and
a processor configured for:
obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and
monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition.
2\. The system of claim 1, wherein the processor is further configured for:
computing a time series of CI-feature (TSCF) based on the TSCI, each CI-feature (CF) comprising a concatenation of a basic feature of a respective CI and a basic feature of a corresponding denoised CI, wherein the basic feature of any CI comprises at least one of: the CI, a magnitude of the CI, a phase of the CI, a magnitude of a component of the CI, or a phase of the component of the CI, wherein the denoised CI is computed by processing the TSCI with a first denoising filter, the first denoising filter comprising at least one of: a low-pass filter, a bandpass filter, a highpass filter, a median filter, or a percentile filter; and
computing the 2D decomposition based on the TSCF.
3\. The system of claim 2, wherein the processor is further configured for:
determining a series of sliding time windows, each sliding time window being associated with a time stamp;
computing a respective one dimensional (iD) characteristic function of the CF of the TSCF in each sliding time window; and
constructing the 2D decomposition based on the respective 1D characteristic function in each sliding time window.
4\. The system of claim 3, wherein: the respective 1D characteristic function is computed based on a transformation of the CF of the TSCF in each sliding time window; and
the transformation comprises at least one of a frequency transformation, a transformation to frequency domain, a short-time Fourier transform (STFT), a wavelet transform, a filter-bank representation, a time transformation, a transformation to a time-shift domain, an auto-correlation function (ACF), an auto-covariance function, or a time-frequency decomposition.
5\. The system of claim 4, wherein the processor is further configured for:
constructing a 2D matrix by lining up and aligning the 1D characteristic functions of the sliding time windows in time order according to the associated time stamps, wherein i-th column of the 2D matrix represents the 1D characteristic function associated with i-th sliding time window, j -th row of the 2D matrix is associated with a time-shift of j time units, a matrix element at the i-th column and the j-th row of the 2D matrix is a value of the 1D characteristic function in the i-th sliding time window with a time-shift of j time units, and
the 2D matrix is a result of the 2D decomposition.
6\. The system of claim 5, wherein the processor is further configured for:
enhancing the 2D decomposition by applying, to each matrix element of the 2D matrix, a vertical highpass filtering, a horizontal lowpass filtering, or both.
7\. The system of claim 6, wherein the processor is further configured for:
filtering each matrix element of the 2D matrix with a respective 2D vertical highpass horizontal lowpass filter that is either separable or non-separable, either linear or nonlinear.
8\. The system of claim 7, wherein the processor is further configured for:
enhancing the 2D decomposition by filtering each matrix element of the 2D matrix with at least one of a respective vertical highpass filter or a respective horizontal lowpass filter, wherein each of the respective vertical highpass filter and the respective horizontal lowpass filter is either linear or nonlinear.
9\. The system of claim 8, wherein the processor is further configured for enhancing the 2D decomposition by at least one of filtering part of each column of the 2D matrix with a respective first common vertical highpass filter;
filtering part of each row of the 2D matrix with a respective second common vertical highpass filter;
filtering part of each column of the 2D matrix with a respective first common horizontal lowpass filter; or
filtering part of each row of the 2D matrix with a respective second common horizontal lowpass filter.

10\. The system of claim 9, wherein:
a vertical highpass filter is a directional 1D highpass filter applied in a vertical direction or in a near-vertical direction.

11\. The system of claim 10, wherein:
a horizontal lowpass filter is a directional 1D lowpass filter applied in a horizontal direction or in a near-horizontal direction.

12\. The system of claim 11, wherein the processor is further configured for:
filtering each matrix element of the 2D matrix with a succession of at least two 1D filters, each being either the vertical highpass filter or the horizontal lowpass filter.

13\. The system of claim 12, wherein the processor is further configured for:
enhancing the 2D decomposition by applying histogram equalization to a number of consecutive columns of the 2D matrix to generate an enhanced 2D matrix.

14\. The system of claim 13, wherein the processor is further configured for:
computing a distance score based on dynamic time warping (DTW) between a reference column and a particular column of the enhanced 2D matrix associated with a particular time, wherein:
the reference column is computed in a training session by clustering a number of training columns matched based on DTW, the training columns are computed based on training TSCI obtained from training wireless signals that are received through the wireless channel when training objects with vital signs are present and impacting the wireless channel, and when the distance score is larger than a first threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time.

15\. The system of claim 14, wherein the processor is further configured for:
subtracting a quantity from each matrix element in the particular column of the enhanced 2D matrix; and
computing a zero-crossing count of the particular column, wherein when the zero-crossing count is larger than a second threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time.

16\. The system of claim 15, wherein the processor is further configured for:
computing multiple peaks of the particular column of the enhanced 2D matrix; and
computing an inter-peak distance based on the multiple peaks.

17\. The system of claim 16, wherein:
when the inter-peak distance is in an acceptable range, the periodic motion of the vital sign of the object is tentatively detected at the particular time, and the inter-peak distance is determined to be equal to a frequency or a period of the vital sign; and
when the inter-peak distance is not in an acceptable range, the periodic motion of the vital sign of the object is tentatively not detected at the particular time.

18\. The system of claim 17, wherein the processor is further configured for:
detecting the vital sign of the object when P is larger than a third threshold, wherein P is a percentage of the periodic motion of the vital sign being tentatively detected in a period of time.

19\. A wireless device of a system for wireless vital sign monitoring, comprising:
a processor;
a memory communicatively coupled to the processor; and
a receiver communicatively coupled to the processor, wherein:
an additional wireless device in the system is configured to transmit a wireless signal through a wireless channel of a venue, the receiver is configured to receive the wireless signal through the wireless channel, the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue, and the processor is configured for:
obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and
monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition.

20\. A method for wireless vital sign monitoring, comprising:
transmitting a wireless signal through a wireless channel of a venue;
receiving the wireless signal through the wireless channel, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue;
obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal;
computing a two dimensional (2D) decomposition of the time series of CI (TSCI);
enhancing the 2D decomposition; and
monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition. 80 81 82 83 84

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 § 102
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, 19-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Liu et al. (“Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi”).
To claim 1, Liu teach a system for wireless vital sign monitoring, comprising:
a transmitter configured to transmit a wireless signal through a wireless channel of a venue (Figs. 2, 10);
a receiver configured to receive the wireless signal through the wireless channel (Figs. 2, 10), wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue (pages 270-273, sections 4-6); and
a processor (Fig. 2) configured for:
obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (pages 269-272, sections 3.3-5, Figs. 1, 3, 5-8).
To claim 19, Liu teach a wireless device of a system for wireless vital sign monitoring, comprising: a processor; a memory communicatively coupled to the processor; and a receiver communicatively coupled to the processor, wherein: an additional wireless device in the system is configured to transmit a wireless signal through a wireless channel of a venue, the receiver is configured to receive the wireless signal through the wireless channel, the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue, and the processor is configured for: obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (as explained in response to claim 1 above).
To claim 20, Liu teach a method for wireless vital sign monitoring, comprising: transmitting a wireless signal through a wireless channel of a venue; receiving the wireless signal through the wireless channel, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue; obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal; computing a two dimensional (2D) decomposition of the time series of CI (TSCI); enhancing the 2D decomposition; and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (as explained in response to claim 1 above).
To claim 2, Liu teach claim 1.
Liu teach wherein the processor is further configured for: computing a time series of CI-feature (TSCF) based on the TSCI, each CI-feature (CF) comprising a concatenation of a basic feature of a respective CI and a basic feature of a corresponding denoised CI, wherein the basic feature of any CI comprises at least one of: the CI, a magnitude of the CI, a phase of the CI, a magnitude of a component of the CI, or a phase of the component of the CI (page 270, sections 4.1-4.2), wherein the denoised CI is computed by processing the TSCI with a first denoising filter, the first denoising filter comprising at least one of: a low-pass filter, a bandpass filter, a highpass filter, a median filter, or a percentile filter (page 270, section 4.1 data calibration); and computing the 2D decomposition based on the TSCF (pages 270-271, section 4.2-4.3).
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.
Claim(s) 3-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi”).
To claim 3, Liu teach claim 2.
Liu teach wherein the processor is further configured for: determining a series of sliding time windows, each sliding time window being associated with a time stamp (page 270, sections 4.1-4.2, sliding window or moving time window, associating time stamp would have been an obvious feature); computing a respective one dimensional (1D) characteristic function of the CF of the TSCF in each sliding time window; and constructing the 2D decomposition based on the respective 1D characteristic function in each sliding time window (pages 271-272, Figs. 5-8).
To claim 4, Liu teach claim 3.
Liu teach wherein: the respective 1D characteristic function is computed based on a transformation of the CF of the TSCF in each sliding time window; and the transformation comprises at least one of a frequency transformation, a transformation to frequency domain, a short-time Fourier transform (STFT), a wavelet transform, a filter-bank representation, a time transformation, a transformation to a time-shift domain, an auto-correlation function (ACF), an auto-covariance function, or a time-frequency decomposition (page 271, section 4.4, PSD transforms the time series of CSI measurements on each subcarrier to its power distribution in the frequency domain).
To claim 5, Liu teach claim 4.
Liu teach wherein the processor is further configured for: constructing a 2D matrix by lining up and aligning the 1D characteristic functions of the sliding time windows in time order according to the associated time stamps, wherein i-th column of the 2D matrix represents the 1D characteristic function associated with i-th sliding time window, j -th row of the 2D matrix is associated with a time-shift of j time units, a matrix element at the i-th column and the j-th row of the 2D matrix is a value of the 1D characteristic function in the i-th sliding time window with a time-shift of j time units, and the 2D matrix is a result of the 2D decomposition (despite lack of description on matrix and alignment, it would have been obvious in view of pages 271-272, vector representation on CSI measurement, claimed 2D matrix representations above are well-known in practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data analysis, hence Official Notice is taken).
To claim 6, Liu teach claim 5.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by applying, to each matrix element of the 2D matrix, a vertical highpass filtering, a horizontal lowpass filtering, or both (despite of lack of description in Liu, using particular filtering technique(s) on matrix data is well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 7, Liu teach claim 6.
Liu teach wherein the processor is further configured for: filtering each matrix element of the 2D matrix with a respective 2D vertical highpass horizontal lowpass filter that is either separable or non-separable, either linear or nonlinear (obvious in explanation in response to claim 6 above).
To claim 8, Liu teach claim 7.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by filtering each matrix element of the 2D matrix with at least one of a respective vertical highpass filter or a respective horizontal lowpass filter, wherein each of the respective vertical highpass filter and the respective horizontal lowpass filter is either linear or nonlinear (obvious in explanation in response to claim 6 above).
To claim 9, Liu teach claim 8.
Liu teach wherein the processor is further configured for enhancing the 2D decomposition by at least one of filtering part of each column of the 2D matrix with a respective first common vertical highpass filter; filtering part of each row of the 2D matrix with a respective second common vertical highpass filter; filtering part of each column of the 2D matrix with a respective first common horizontal lowpass filter; or filtering part of each row of the 2D matrix with a respective second common horizontal lowpass filter (obvious in explanation in response to claim 6 above).
To claim 10, Liu teach claim 9.
Liu teach wherein: a vertical highpass filter is a directional 1D highpass filter applied in a vertical direction or in a near-vertical direction (obvious in explanation in response to claim 6 above).
To claim 11, Liu teach claim 10.
Liu teach wherein: a horizontal lowpass filter is a directional 1D lowpass filter applied in a horizontal direction or in a near-horizontal direction (obvious in explanation in response to claim 6 above).
To claim 12, Liu teach claim 11.
Liu teach wherein the processor is further configured for: filtering each matrix element of the 2D matrix with a succession of at least two 1D filters, each being either the vertical highpass filter or the horizontal lowpass filter (obvious in explanation in response to claim 6 above).
To claim 13, Liu teach claim 12.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by applying histogram equalization to a number of consecutive columns of the 2D matrix to generate an enhanced 2D matrix (despite of lack of description in Liu, using particular histogram equalization technique(s) on matrix data is well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 14, Liu teach claim 13.
But, Liu do not expressly disclose wherein the processor is further configured for: computing a distance score based on dynamic time warping (DTW) between a reference column and a particular column of the enhanced 2D matrix associated with a particular time, wherein: the reference column is computed in a training session by clustering a number of training columns matched based on DTW, the training columns are computed based on training TSCI obtained from training wireless signals that are received through the wireless channel when training objects with vital signs are present and impacting the wireless channel, and when the distance score is larger than a first threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, having distance score on dynamic time warping with threshold detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 15, Liu teach claim 14.
Liu teach wherein the processor is further configured for: subtracting a quantity from each matrix element in the particular column of the enhanced 2D matrix; and computing a zero-crossing count of the particular column, wherein when the zero-crossing count is larger than a second threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, claimed particular matrix arrangement on threshold detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 16, Liu teach claim 15.
Liu teach wherein the processor is further configured for: computing multiple peaks of the particular column of the enhanced 2D matrix; and computing an inter-peak distance based on the multiple peaks (pages 270-271, section 4.3).
To claim 17, Liu teach claim 16.
Liu teach wherein: when the inter-peak distance is in an acceptable range, the periodic motion of the vital sign of the object is tentatively detected at the particular time, and the inter-peak distance is determined to be equal to a frequency or a period of the vital sign; and when the inter-peak distance is not in an acceptable range, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, having particular inter-peak distance arrangement for periodic motion detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
Liu teach 18, Liu teach claim 17.
Liu teach wherein the processor is further configured for: detecting the vital sign of the object when P is larger than a third threshold, wherein P is a percentage of the periodic motion of the vital sign being tentatively detected in a period of time (despite of lack of description in Liu, using particular threshold arrangement for periodic motion detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
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 .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (“Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi”) in view of Li et al. (CN109684941).
To claim 1, Liu teach a system for wireless vital sign monitoring, comprising:
a transmitter configured to transmit a wireless signal through a wireless channel of a venue (Figs. 2, 10);
a receiver configured to receive the wireless signal through the wireless channel (Figs. 2, 10), wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue (pages 270-273, sections 4-6); and
a processor (Fig. 2) configured for:
obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (pages 269-272, sections 3.3-5, Figs. 1, 3, 5-8).
But, Liu do not expressly disclose the 2D decomposition based on a vertical highpass filtering and a horizontal lowpass filtering.
Li teach an image processing system comprising a 2D decomposition based on a vertical highpass filtering and a horizontal lowpass filtering (paragraphs 0012, 0019-0021) followed by a histogram equalization (paragraph 0012).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Li into the system of Liu, in order to further 2D decomposition with enhancement.
To claim 19, Liu and Li teach a wireless device of a system for wireless vital sign monitoring, comprising: a processor; a memory communicatively coupled to the processor; and a receiver communicatively coupled to the processor, wherein: an additional wireless device in the system is configured to transmit a wireless signal through a wireless channel of a venue, the receiver is configured to receive the wireless signal through the wireless channel, the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue, and the processor is configured for: obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition by applying a vertical highpass filter followed by a histogram equalization, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (as explained in response to claim 1 above).
To claim 20, Liu and Li teach a method for wireless vital sign monitoring, comprising: transmitting a wireless signal through a wireless channel of a venue; receiving the wireless signal through the wireless channel, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue; obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal; computing a two dimensional (2D) decomposition of the time series of CI (TSCI); enhancing the 2D decomposition based on a vertical highpass filter and a histogram equalization; and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition (as explained in response to claim 1 above).
To claim 2, Liu and Li teach claim 1.
Liu teach wherein the processor is further configured for: computing a time series of CI-feature (TSCF) based on the TSCI, each CI-feature (CF) comprising a concatenation of a basic feature of a respective CI and a basic feature of a corresponding denoised CI, wherein the basic feature of any CI comprises at least one of: the CI, a magnitude of the CI, a phase of the CI, a magnitude of a component of the CI, or a phase of the component of the CI (page 270, sections 4.1-4.2), wherein the denoised CI is computed by processing the TSCI with a first denoising filter, the first denoising filter comprising at least one of: a low-pass filter, a bandpass filter, a highpass filter, a median filter, or a percentile filter (page 270, section 4.1 data calibration); and computing the 2D decomposition based on the TSCF (pages 270-271, section 4.2-4.3).
To claim 3, Liu and Li teach claim 2.
Liu teach wherein the processor is further configured for: determining a series of sliding time windows, each sliding time window being associated with a time stamp (page 270, sections 4.1-4.2, sliding window or moving time window, associating time stamp would have been an obvious feature); computing a respective one dimensional (1D) characteristic function of the CF of the TSCF in each sliding time window; and constructing the 2D decomposition based on the respective 1D characteristic function in each sliding time window (pages 271-272, Figs. 5-8).
To claim 4, Liu and Li teach claim 3.
Liu teach wherein: the respective 1D characteristic function is computed based on a transformation of the CF of the TSCF in each sliding time window; and the transformation comprises at least one of a frequency transformation, a transformation to frequency domain, a short-time Fourier transform (STFT), a wavelet transform, a filter-bank representation, a time transformation, a transformation to a time-shift domain, an auto-correlation function (ACF), an auto-covariance function, or a time-frequency decomposition (page 271, section 4.4, PSD transforms the time series of CSI measurements on each subcarrier to its power distribution in the frequency domain).
To claim 5, Liu and Li teach claim 4.
Liu teach wherein the processor is further configured for: constructing a 2D matrix by lining up and aligning the 1D characteristic functions of the sliding time windows in time order according to the associated time stamps, wherein i-th column of the 2D matrix represents the 1D characteristic function associated with i-th sliding time window, j -th row of the 2D matrix is associated with a time-shift of j time units, a matrix element at the i-th column and the j-th row of the 2D matrix is a value of the 1D characteristic function in the i-th sliding time window with a time-shift of j time units, and the 2D matrix is a result of the 2D decomposition (despite lack of description on matrix and alignment, it would have been obvious in view of pages 271-272, vector representation on CSI measurement, claimed 2D matrix representations above are well-known in practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data analysis, hence Official Notice is taken).
To claim 6, Liu and Li teach claim 5.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by applying, to each matrix element of the 2D matrix, a vertical highpass filtering, a horizontal lowpass filtering, or both (despite of lack of description in Liu, using particular filtering technique(s) on matrix data is well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 7, Liu and Li teach claim 6.
Liu teach wherein the processor is further configured for: filtering each matrix element of the 2D matrix with a respective 2D vertical highpass horizontal lowpass filter that is either separable or non-separable, either linear or nonlinear (obvious in explanation in response to claim 6 above).
To claim 8, Liu and Li teach claim 7.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by filtering each matrix element of the 2D matrix with at least one of a respective vertical highpass filter or a respective horizontal lowpass filter, wherein each of the respective vertical highpass filter and the respective horizontal lowpass filter is either linear or nonlinear (obvious in explanation in response to claim 6 above).
To claim 9, Liu and Li teach claim 8.
Liu teach wherein the processor is further configured for enhancing the 2D decomposition by at least one of filtering part of each column of the 2D matrix with a respective first common vertical highpass filter; filtering part of each row of the 2D matrix with a respective second common vertical highpass filter; filtering part of each column of the 2D matrix with a respective first common horizontal lowpass filter; or filtering part of each row of the 2D matrix with a respective second common horizontal lowpass filter (obvious in explanation in response to claim 6 above).
To claim 10, Liu and Li teach claim 9.
Liu teach wherein: a vertical highpass filter is a directional 1D highpass filter applied in a vertical direction or in a near-vertical direction (obvious in explanation in response to claim 6 above).
To claim 11, Liu and Li teach claim 10.
Liu teach wherein: a horizontal lowpass filter is a directional 1D lowpass filter applied in a horizontal direction or in a near-horizontal direction (obvious in explanation in response to claim 6 above).
To claim 12, Liu and Li teach claim 11.
Liu teach wherein the processor is further configured for: filtering each matrix element of the 2D matrix with a succession of at least two 1D filters, each being either the vertical highpass filter or the horizontal lowpass filter (obvious in explanation in response to claim 6 above).
To claim 13, Liu and Li teach claim 12.
Liu teach wherein the processor is further configured for: enhancing the 2D decomposition by applying histogram equalization to a number of consecutive columns of the 2D matrix to generate an enhanced 2D matrix (despite of lack of description in Liu, using particular histogram equalization technique(s) on matrix data is well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 14, Liu and Li teach claim 13.
But, Liu do not expressly disclose wherein the processor is further configured for: computing a distance score based on dynamic time warping (DTW) between a reference column and a particular column of the enhanced 2D matrix associated with a particular time, wherein: the reference column is computed in a training session by clustering a number of training columns matched based on DTW, the training columns are computed based on training TSCI obtained from training wireless signals that are received through the wireless channel when training objects with vital signs are present and impacting the wireless channel, and when the distance score is larger than a first threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, having distance score on dynamic time warping with threshold detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 15, Liu and Li teach claim 14.
Liu teach wherein the processor is further configured for: subtracting a quantity from each matrix element in the particular column of the enhanced 2D matrix; and computing a zero-crossing count of the particular column, wherein when the zero-crossing count is larger than a second threshold, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, claimed particular matrix arrangement on threshold detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
To claim 16, Liu and Li teach claim 15.
Liu teach wherein the processor is further configured for: computing multiple peaks of the particular column of the enhanced 2D matrix; and computing an inter-peak distance based on the multiple peaks (pages 270-271, section 4.3).
To claim 17, Liu and Li teach claim 16.
Liu teach wherein: when the inter-peak distance is in an acceptable range, the periodic motion of the vital sign of the object is tentatively detected at the particular time, and the inter-peak distance is determined to be equal to a frequency or a period of the vital sign; and when the inter-peak distance is not in an acceptable range, the periodic motion of the vital sign of the object is tentatively not detected at the particular time (despite of lack of description in Liu, having particular inter-peak distance arrangement for periodic motion detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
Liu teach 18, Liu and Li teach claim 17.
Liu teach wherein the processor is further configured for: detecting the vital sign of the object when P is larger than a third threshold, wherein P is a percentage of the periodic motion of the vital sign being tentatively detected in a period of time (despite of lack of description in Liu, using particular threshold arrangement for periodic motion detection is well-known practice in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the system of Liu for data enhancement, hence Official Notice is taken).
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.