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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/02/2023 has been considered by the examiner.
Claim Objections
Claims 1, 5-10, and 12-15 are objected to because of the following informalities:
For claims 1, 5-7, and 9-10, references such as “S1”, “A41”, “B41” should be “step S1”, “step A41”, and “step B41” for clarity.
For claim 8, the examiner assumes “frequency f” should be “frequency F” for clarity.
For claims 12-15, elements such as “the wireless signal transmitting device outputs” should be “the wireless signal transmitting device is configured to output” for clarity.
Although the courts have found that the use of the term “and/or” would not be indefinite, (Employers Mut. Liability Ins. Co. v. Tollefsen, 219 Wis. 434 (1935)), the board did note that the preferred way of writing the claim is through use of “at least one of A and B" in the future. Therefore, the Examiner object to the terms "and/or" in claims 1, 6, and 12 such that it is written in accordance with the courts preferred way.
Appropriate correction is required.
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.
Claim 1-15 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.
For claim 1, “channel state information of the wireless signal” is indefinite. It is unclear what is considered “channel state information” of a signal. For the purpose of advancing prosecution, the examiner assumes “channel state information” is any information.
Claims 2-15 are dependent of claim 1, and therefore rejected under this 112(b) rejection above as well.
Claim 2 recites the limitation "the real value". There is insufficient antecedent basis for this limitation in the claim. It is unclear what is the “real value” (i.e., real value of the big error, real value of the small error, real value of the Huber objective function, real value of the input vital sign waveform signal, real value of something else). For the purpose of advancing prosecution, the examiner reads the limitation as “Huber objective function divides the error into two parts, including big error and small error”.
However, the term “big error” and “small error” in claim 2 is a relative term which renders the claim indefinite. The term “big” and “small” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For the purpose of advancing prosecution, the examiner assumes the “big error” and “small error” is the same error.
Claim 2 recites the limitation "the optimal estimated value". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the optimal estimated value” should be “an optimal estimated value” for clarity.
Claim 2 recites the limitation "the current moment". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the current moment” should be “a current moment” for clarity.
Claim 2 recites the limitation "the previous moment". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the previous moment” should be “a previous moment” for clarity.
Claim 2 recites the limitation "the observed value ". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the observed value” should be “an observed value” for clarity.
Claims 3-4 are dependent of claim 2, and therefore rejected under these 112(b) rejections as well.
For claim 3, “a represents the threshold between a big error and a small error” is indefinite. It is unclear if the errors are the same errors in claim 2, or different errors. For the purpose of advancing prosecution, the examiner assumes the big error and small error are the same as the errors in claim 2.
For claim 3, “posterior error” is indefinite. It is unclear what is the difference between posterior error vs prior error. For the purpose of advancing prosecution, the examiner assumes posterior error is error in a current moment in time.
For claim 3, “process noise” is indefinite. It is unclear what is the difference between process noise vs measurement noise vs random noise. For the purpose of advancing prosecution, the examiner assumes the noises are the same.
Claim 4 is dependent of claim 3, and therefore rejected under this 112(b) rejection as well.
Claims 5 and 6 recites the limitation "the tested human body". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the tested human body” should be “a tested human body” for clarity.
Claims 5 and 6 recites the limitation "the time window". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the time window” should be “a time window” for clarity.
Claim 6 recites the limitation " obtain the frequency spectrum characteristics". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “obtain the frequency spectrum characteristics” should be “obtain frequency spectrum characteristics” for clarity.
Claim 6 recites the limitation "the spectrum characteristics". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the spectrum characteristics” should be “the frequency spectrum characteristics” for clarity.
For claim 9, “outputting the wireless signal to the measured target, and simultaneously using the wireless signal as a reference signal, and transmitting the wireless signal in a wired way” is indefinite. It is unclear if the reference signal is transmitted in a wireless way or a wired way. For the purpose of advancing prosecution, the examiner assumes the reference signal is transmitted in a wired way.
Claims 10-11 are dependent of claim 9, and therefore rejected under this 112(b) rejection as well.
For claim 10, “performing subcarrier fusion processing on the preprocessed signal to output a respiratory characteristic waveform signal” is indefinite. It is unclear what is considered “subcarrier fusion processing”. For the purpose of advancing prosecution, the examiner reads the limitation as “performing processing on the preprocessed signal to output a respiratory characteristic waveform signal”.
Claim 11 is dependent of claim 10, and therefore rejected under this 112(b) rejection as well.
Claim 11 recites the limitation "the subcarrier signal ". There is insufficient antecedent basis for this limitation in the claim. For the purpose of advancing prosecution, the examiner assumes “the subcarrier signal” should be “a subcarrier signal” for clarity.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over Ser et al. (US 20110257536 A1, published October 20, 2011) in view of Lu et al. (CN 107808393 A, published March 16, 2018), hereinafter referred to as Ser and Lu, respectively.
Regarding claim 1, and similarly for claim 12, Ser teaches a contactless breathing or heartbeat detection method, including the following steps:
S1, acquiring channel state information (any information) of the wireless signal according to the output wireless signal and the wireless signal reflected by the measured target (Fig. 1B-2; see para. 0052 – “The wireless heartbeat and respiratory rate monitoring (WHRM) device 5 first transmits a wave signal to the subject 1…The wireless heartbeat and respiratory rate monitoring (WHRM) device 5 then receives another wave signal 3, where this received wave signal 3 may include the reflected transmitted wave signal from the subject 1, for example.”);
S2, extracting a vital sign waveform signal from the channel state information of the wireless signal (Fig. 2; see para. 0121 - “Further, the first signal 13 provided to the heartbeat/respiratory detection and estimation module (HRDEM) 14 may include the Doppler frequency information of the heartbeat and/or respiratory rate.”);
S3, filtering the vital sign waveform signal based on a Kalman filtering algorithm to obtain a filtered vital sign waveform signal (see para. 0125 – “In one embodiment, a Kalman filter [filtering signal] like processing system may be used, in order to extract the heartbeat/respiratory rate with high resolution.”);
S4, extracting respiratory characteristic parameters and/or heartbeat characteristic parameters from the filtered vital sign waveform signals (see para. 0125 – “In one embodiment, a Kalman filter [filtered signals] like processing system may be used, in order to extract the heartbeat/respiratory rate [respiratory characteristic parameters and/or heartbeat characteristic parameters] with high resolution.”).
Ser teaches filtering a signal via a Kalman filter, but does not explicitly teach filtering a signal via a Huber-Kalman filter.
Whereas, Lu, in an analogous field of endeavor, teaches filtering the vital sign waveform signal based on a Huber-Kalman filtering algorithm to obtain a filtered vital sign waveform signal, wherein the Huber-Kalman filtering algorithm uses a Huber objective function to update a formula of the Kalman filtering algorithm (see pg. 9, claim 5 – “…(3.2) re-constructing observation model and calculating measurement-update by Huber estimation diagonal matrix Ψ y in the equation of x and y x of the diagonal matrix Ψ obtained in the filter update in Kalman filtering model, predicting the target state.”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified filtering a signal via a Kalman filter, as disclosed in Ser, by filtering the signal via a Huber-Kalman filter, as disclosed in Lu. One of ordinary skill in the art would have been motivated to make this modification in order to improve the moving target tracking accuracy of the device and the environment noise under abnormal condition and improves the monitoring capability, as taught in Lu (see pg. 5, para. 2).
Furthermore, regarding claim 2, Lu further teaches wherein in step S3, the Huber-Kalman filtering algorithm uses the Huber objective function to update the formula of the Kalman filtering algorithm, specifically including the following steps:
the iterative calculation process of Kalman equation is modified by Huber objective function, and the input vital sign waveform signal is filtered (see pg. 9, claim 5 – “…(3.2) re-constructing observation model and calculating measurement-update by Huber estimation diagonal matrix Ψ y in the equation of x and y x of the diagonal matrix Ψ obtained in the filter update in Kalman filtering model, predicting the target state.”);
Huber objective function divides the error into two parts, including big error and small error, big error refers to the error value that deviates from the real value and is greater than the big error threshold, and small error refers to the error value that fluctuates within the small error threshold based on the real value (see pg. 4, para. 7 – “defining residual error, i.e. the difference between the estimated value and the measured value, the formula is: ζ =Gx – z…the diagonal matrix Ψ is divided into two parts to obtain Ψ y x…”);
the iterative calculation means that the optimal estimated value at the current moment is determined by the optimal estimated value calculated according to Kalman update equation at the previous moment and the observed value calculated according to Huber objective function at the current moment (see pg. 9, claim 5 – “…(3.2) re-constructing observation model and calculating measurement-update by Huber estimation diagonal matrix Ψ y in the equation of x and y x of the diagonal matrix Ψ obtained in the filter update in Kalman filtering model, predicting the target state.”).
Furthermore, regarding claim 3, Lu further teaches wherein in step S3, the prediction equation based on Huber objective function is expressed as:
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214
586
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Kalman update equation is:
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418
826
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where k represents the k-th moment; a represents the threshold between a big error and a small error; xk represents the predicted value at moment k, and xk-1 represents the optimal estimated value at moment k-1; zk is the input data; uk-1, represents the random noise in the state transition process; vk represents measurement noise (see pg. 8, para. 1 – “wherein, the subscript k represents time at time k; x is the state vector, y is the measured value, u is the system input, v is system noise, w is measurement noise, v and k are zero-mean white noise;”);
Q represents the covariance of process noise; R represents the measurement noise covariance; A represents the state transition coefficient; B represents the control input coefficient; H represents the measurement coefficient (see pg. 6, para. 3 – “X (k) is a target current state, F (k) is the state transition matrix, T is the sampling period, α is target motor frequency, α =1/20. the covariance matrix of V (k) satisfies”);
ek stands for posterior error; ek-1 represents prior error; ρa-(ek-) represents a prior error function; ρa(ek) represents a posterior error function; Kk stands for Kalman gain (see pg. 4, para. 7 – “defining residual error, i.e. the difference between the estimated value and the measured value, the formula is: ζ =Gx – z…the diagonal matrix Ψ is divided into two parts to obtain Ψ y x…”).
Furthermore, regarding claim 4, Lu further teaches wherein step S3 further includes detecting the environmental noise level in real time, and adjusting the threshold between the big error and the small error according to the environmental noise level (see pg. 2, para. 7 - “the measurement equation is: Z (k) = HX (k) + w (k); wherein Z is observation value, H is matrix, w is measurement noise, k represents time;”).
The motivation for claims 2-4 was shown previously in claim 1.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu, as applied to claim 1 above, and in further view of J. Tu et al, “Fast Acquisition of Heart Rate in Noncontact Vital Sign Radar Measurement Using Time-Window-Variation Technique”, IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 1, pp. 112-122, Jan. 2016, hereinafter referred to as Tu.
Regarding claim 5, Ser in view of Lu teaches all of the elements disclosed in claim 1 above.
Ser in view of Lu teaches extracting respiratory characteristic parameters and/or heartbeat characteristic parameters from the filtered vital sign waveform signals, but does not explicitly teach segmenting the signal according to a time window.
Whereas, Tu, in an analogous field of endeavor, teaches wherein step S4 specifically includes the following steps:
A41, segmenting the filtered vital sign waveform signal according to the time window to obtain a vital sign waveform (Fig. 6, “Select a time window of M samples” as segmenting signal);
A42, extracting the time interval between the peaks of the vital sign waveform, and determining the frequency (rate) of breathing or heartbeat of the tested human body according to the time interval between the peaks (Fig. 6, “HR decided”; see pg. 116, col. 1, para. 1 – “…a time window variation technique is developed based on this condition to measure the HR from short-period time windows.”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified extracting respiratory characteristic parameters and/or heartbeat characteristic parameters from the filtered vital sign waveform signals, as disclosed in Ser in view of Lu, by also segmenting the signal according to a time window, as disclosed in Tu. One of ordinary skill in the art would have been motivated to make this modification in order to improve the accuracy of measuring HR and HR variation, as taught in Tu (see Abstract).
Furthermore, regarding claim 6, Ser further teaches wherein step S4 specifically includes the following steps: B43, performing low-pass filtering on the spectrum characteristics of the vital sign waveform to obtain the breathing frequency of the tested human body, and/or performing high-pass filtering on the spectrum characteristics of the vital sign waveform to obtain the heartbeat frequency of the tested human body (Fig. 9; see para. 0136 – “Next, the Fast Fourier Transform (FFT) module 104 may apply a Fourier Transform operation on the new block signal 110, and provide an output signal 112 to the rate extraction unit 106.”; see para. 0138 – “The rate extraction module 106 may select the peak of the output signal 112 in low frequency band according to the sampling rate of the first signal 13′ and the conventional frequency band of heartbeat and respiratory signal. The rate extraction module 106 provides an output being the result signal 7.”), and
Tu further teaches B41, segmenting the filtered vital sign waveform signal according to the time window to obtain a vital sign waveform (Fig. 6, “Select a time window of M samples” as segmenting signal); and
B42, performing frequency domain analysis on the vital sign waveform to obtain the frequency spectrum characteristics of the vital sign waveform (Fig. 6, FFT (frequency domain analysis) on segmented signals).
The motivation for claim 6 was shown previously in claim 5.
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu, as applied to claim 1 above, and in further view of Wu et al. (CN 111803045 A, published October 23, 2020), hereinafter referred to as Wu.
Regarding claim 5, Ser in view of Lu teaches all of the elements disclosed in claim 1 above, and
Ser further teaches step S1 specifically includes the following steps: S1, outputting a signal to a measured target, and taking the signal at the transmitting time as a reference signal (Fig. 5, reference high frequency signal 63 as reference signal);
S12, the measured target reflects the millimeter wave radar signal to form an echo signal, and the echo signal and the reference signal are demodulated to generate an intermediate frequency signal (Fig. 5; see para. 0097 – “The demodulator 45 processes the amplified received signal 55 [echo signal] using the reference high frequency signal 63, in order to retrieve a demodulated baseband signal 57 [intermediate frequency signal].”);
S13, performing ADC sampling on the intermediate frequency signal in turn to obtain the information of the measured target (Fig. 5; see para. 0098 – “Next, the analog to digital converter (A/D) 43 may be used to sample [ADC sampling] and convert the demodulated baseband signal 57 [intermediate frequency signal] into the processed wave signal 25.”).
Ser in view of Lu teaches transmitting and receiving wireless signals, but does not explicitly teach where the wireless signal is a millimeter wave radar signal.
Whereas, Wu, in an analogous field of endeavor, teaches wherein, the wireless signal is a millimeter wave radar signal (see Abstract – “…the millimetre wave front end system transmits and receives signal through two antennas…”),
performing FFT transformation on the intermediate frequency signal in turn to obtain the distance information and the phase information of the measured target (see pg. 5, para. 7 – “2. Distance-dimensional FFT: firstly performing fast Fourier transform (FFT) to the digital signal, according to the radar distance measuring principle, obtaining the frequency f of the frequency spectrum peak…can be calculated to obtain the target point distance…”; see pg. 5, para. 9 – “…extracting the phase value of the digital signal in the target range box…”);
S14, the phase information of the millimeter wave radar signal is used as the channel state information of the millimeter wave radar signal (see pg. 3, para. 11 – “…according to the relationship between the body sign displacement and the phase information caused by the millimeter wave radar…”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified transmitting and receiving a wireless signal, as disclosed in Ser in view of Lu, by having the wireless signal as a millimeter wave radar signal, as disclosed in Wu. One of ordinary skill in the art would have been motivated to make this modification in order to increase the feasibility of detection, improving the detection quality, as taught in Wu (see pg. 3, para. 11).
Furthermore, regarding claim 8, Wu further teaches wherein, the range of the frequency f of the millimeter wave radar signal includes: 23 GHz ≤ F ≤ 28 GHz , 60 GHz ≤ F ≤ 65 GHz , and 76 GHz ≤ F ≤ 81 GHz (see Abstract – “The invention claims a vital sign detection system based on millimetre wave radar…” where it is inherent and known in the art that millimeter wave radar signal frequency ranges 23 GHz to 81 GHz).
The motivation for claim 8 was shown previously in claim 7.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu, as applied to claim 1 above, and in further view of Boric-Lubecke et al. (US 20080077015 A1, published March 27, 2008), hereinafter referred to as Boric.
Regarding claim 5, Ser in view of Lu teaches all of the elements disclosed in claim 1 above.
Ser in view of Lu teaches transmitting a wireless signal, but does not explicitly teach transmitting a reference signal in a wired way.
Whereas, Boric, in an analogous field of endeavor, teaches wherein, when the wireless signal is a Wi-Fi signal, step S1 specifically includes the following steps:
C11, outputting the wireless signal to the measured target, and simultaneously using the wireless signal as a reference signal, and transmitting the wireless signal in a wired way (see para. 0020 – “Heart rates may be extracted in real time with custom software based on an autocorrelation algorithm or the like, and heart rate may be compared with that obtained from a wired finger pressure pulse sensor (UFI 1010) used as a reference.”);
C12: the measured object reflects the wireless signal to form a reflected wireless signal, and the reflected wireless signal is differentiated from the reference signal to obtain the phase difference information of the wireless signal, which is used as the channel state information of the wireless signal (see para. 0057 – “The received modulated signal is related to the transmitted source signal with a time delay determined by the nominal distance of the subject, and with its phase modulated by the periodic motion of the subject…For example, when the received and LO signals are mixed and then low-pass filtered, the resulting baseband signal contains the constant phase shift dependent on the distance to the subject, do, and the periodic phase shift resulting from subject motion.”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified transmitting a wireless signal, as disclosed in Ser in view of Lu, by also transmitting a reference signal in a wired way, as disclosed in Boric. One of ordinary skill in the art would have been motivated to make this modification in order to determine the number of subjects within range of a system, separate and isolate subject's motion data from noise as well as other subjects, and the like, as taught in Boric (see para. 0055).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu and Boric, as applied to claim 9 above, and in further view of Y. Wang et al, “Remote Monitoring of Human Vital Signs Based on 77-GHz mm-Wave FMCW Radar”, Sensors, vol. 20, no. 2999, pp. 1-23, Jan. 2020, hereinafter referred to as Wang.
Regarding claim 10, Ser in view of Lu and Boric teaches all of the elements disclosed in claim 9 above.
Ser in view of Lu and Boric teaches extracting a respiratory signal from a wireless signal, but does not explicitly teach unwrapping the phase information in the signal to output a respiratory characteristic waveform signal.
Whereas, Wang, in an analogous field of endeavor, teaches wherein, step S2 specifically includes the following steps:
S21, unwrapping the phase information to obtain a preprocessed signal (Fig. 3; see para. 1 – “After the human target is determined, the DC offset is corrected, and the arctangent demodulation phase is unwrapped by using the extended DACM algorithm.”);
S22, performing subcarrier fusion processing on the preprocessed signal to output a respiratory characteristic waveform signal (Fig. 3; see pg. 6, para. 1 – “The heartbeat signal is enhanced by using the differential phase to further extract the accurate phase change information in Step 2. In Step 3, CS-OMP and RA-DWT algorithms are presented to separate and reconstruct the heartbeat and respiratory signals.”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified extracting a respiratory signal from a wireless signal, as disclosed in Ser in view of Lu and Boric, by also unwrapping the phase information in the signal to output the respiratory characteristic waveform signal, as disclosed in Wang. One of ordinary skill in the art would have been motivated to make this modification in order to obtain correct phase change information of breathing and heartbeat signals and enhance the signals, as taught in Wang (see pg. 3, para. 2).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu, Boric, and Wang, as applied to claim 10 above, and in further view of Wang et al. (US 20200300972 A1, published September 24, 2020), hereinafter referred to as Zhang.
Regarding claim 11, Ser in view of Lu, Boric, and Wang teaches all of the elements disclosed in claim 10 above.
Ser in view of Lu, Boric, and Wang teaches transmitting a wireless signal, and transmitting Wi-Fi signals in 2.4G or 5G is known in the art, but does not explicitly teach where the wireless signal is in 2.4G or 5G.
Whereas, Zhang, in an analogous field of endeavor, teaches
wherein, when the wireless signal is a Wi-Fi signal in 2.4G band, the frequency bandwidth of the channel state information is 20MHz or 40MHz, and the frequency range of the subcarrier signal of the channel state information is 2401MHz to 2483MHz (see para. 0060 – “The wireless multipath channel may comprise…The channels may be consecutive (e.g. with adjacent/overlapping bands) or non-consecutive channels (e.g. non-overlapping WiFi channels, one at 2.4 GHz and one at 5 GHz).” where the frequency range of a Wi-Fi signal in 2.4G band is 2401MHz to 2483MHz, and channel bandwidth is 20MHz or 40MHz, which is inherent and known in the art);
when the wireless signal is a Wi-Fi signal in 5G band, the frequency bandwidth of the channel state information is 20MHz, 40MHz or 80MHz, and the frequency range of the subcarrier signal of the channel state information is 5150MHz to 5850MHz (The wireless multipath channel may comprise…see para. 0060 – “The channels may be consecutive (e.g. with adjacent/overlapping bands) or non-consecutive channels (e.g. non-overlapping WiFi channels, one at 2.4 GHz and one at 5 GHz).” where the frequency range of a Wi-Fi signal in 5G band is 5150MHz to 5850MHz, and channel bandwidth is 20MHz, 40MHz or 80MHz, which is inherent and known in the art).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified transmitting a wireless signal, as disclosed in Ser in view of Lu, Boric, and Wang, by transmitting Wi-Fi signals in 2.4G or 5G, as disclosed in Zhang. One of ordinary skill in the art would have been motivated to make this modification in order to accurately track breathing/respiration rate of human being, and heart rate variability (HRV) based on wireless channel information in a rich-scattering environment, as taught in Zhang (see para. 0034).
Claims 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Ser in view of Lu, as applied to claim 12 above, and in further view of McMahon et al. (US 20180081030 A1, published March 22, 2018), hereinafter referred to as McMahon.
Regarding claim 13, Ser in view of Lu teaches all of the elements disclosed in claim 12 above, and
Ser further teaches wherein the wireless signal transmitting device comprises a wireless signal generating element and a transmitting antenna, and the wireless signal receiving device comprises a receiving antenna and a wireless signal receiving element; the wireless signal generating element radiates the generated wireless signal to the measured target through the transmitting antenna (see para. 0059 – “The signal transmit/receive module (STRM) 11 performs the function of transmitting the wave signal to the subject 1.”);
the wireless signal receiving element receives the wireless signal reflected by the measured target through the receiving antenna (see para. 0059 – “The signal transmit/receive module (STRM) 11 further performs the function of receiving the (reflected) wave signal, which may be reflected from the subject 1.”).
Ser in view of Lu teaches transmitting antenna and receiving antenna, but does not explicitly teach the transmitting antenna and the receiving antenna are circularly polarized.
Whereas, McMahon, in an analogous field of endeavor, teaches the transmitting antenna and the receiving antenna are circularly polarized, and the polarization directions of the transmitting antenna and the receiving antenna are opposite (see para. 0162 – “When the sensors transmit and receive RF signals are circularly polarised (i.e., their RF signal electric and magnetic fields have a preferred transmit and receive direction) then further noise reduction can be achieved by arranging the sensors such that the polarisation of one sensor is orthogonal to that of the other.”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified transmitting antenna and receiving antenna, as disclosed in Ser in view of Lu, by having the transmitting antenna and the receiving antenna circularly polarized, as disclosed in McMahon. One of ordinary skill in the art would have been motivated to make this modification in order have the reflected movement signal preferred (suffers no attenuation due to polarisation) while the received interference RF signal rejected (suffers attenuation due to its orthogonal polarisation), as taught in McMahon (see para. 0162).
Furthermore, regarding claim 14, McMahon further teaches wherein the clock signal on which the wireless signal generating element generates the wireless signal is the same as the clock signal on which the data processor receives the wireless signal reflected by the measured object (see para. 0112 – “(i) timing synchronization [clock signals the same] can be implemented between the sensors via a wire or wirelessly (where precise timing signals are used between cooperating sensors),”).
One of ordinary skill in the art would have been motivated to make this modification in order to mitigate interference for effective low noise operation, as taught in McMahon (see para. 0111).
Furthermore, regarding claim 15, McMahon further teaches wherein when the wireless signal is a Wi-Fi signal, the system further comprises a power distributor, the Wi-Fi signal generating element outputs the generated Wi-Fi signal to a power distributor, the power distributor outputs the received Wi-Fi signal to the transmitting antenna and simultaneously outputs the Wi-Fi signal to the data processor through the coaxial cable; the data processor generates the channel state information of the Wi-Fi signal according to the Wi-Fi signal received from the coaxial cable and the Wi-Fi signal reflected by the measured object (ese para. 0127 – “In addition the two wires could provide timing synchronization and power to a second unit by modulating the signals. The wire could also reduce the need for other wireless chipsets; e.g., a set of sensors may form a pair, with only one of them having a Wi-Fi or Bluetooth interface and power adaptor or space for batteries [power distributor], and the second simply connected via cable…”).
One of ordinary skill in the art would have been motivated to make this modification in order to not have a need of a separate Wi-Fi etc. radio capability as relevant control/sensor data are also modulated onto the wire, as taught in McMahon (see para. 0127).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Wang et al. (US 20230021342 A1, published January 26, 2023 with a priority date of February 13, 2020) discloses 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.
Wu et al. (US 20200268257 A1, published August 27, 2020) discloses generate signal strength versus distance data by analyzing the received reflecting millimeter wave signal; perform an extreme value reserving process to generate signal extreme value versus distance data; perform a peak search algorithm to obtain a peak list including a plurality of peak values and a plurality of corresponding peak distances; generate a distance array including a plurality of distance variables; and perform a vital sign detection algorithm to generate multiple sets of vital sign data.
Sakamoto et al. (US 20230112537 A1, published April 13, 2023 with a priority date of February 27, 2020) discloses a controller includes circuitry that converts a plurality of received ultra-wideband millimeter-waves to radar signals reflected by the subject, stores the radar signals, calculates the differential signals among the radar signals at each position, calculates the intensity of the differential signals at each position, and estimates respiratory intervals, heartbeat intervals and position of the subject.
H. Kim et al, “Non-Contact Measurement of Human Respiration and Heartbeat Using W-band Doppler Radar Sensor”, vol. 20, no. 5209, pp. 1-9, Sensors, Aug. 2020 discloses the arctangent demodulation with automatic phase unwrapping was utilized to obtain the displacement signals without null-point issues. Together with the trend and peak removal, low-pass and band-pass filtering allows the accurate extraction of very small displacement by the heartbeat from very large respiration signals, thanks to the very short wavelength of W-band frequency.
J. Wei et al, “Non-Contact Life Signal Extraction and Reconstruction Technique Based on MAE”, IEEE Access, vol. 7, pp. 110826-110834, July 2019 discloses extracting the human body micro-motion signal and unwrapping its phase, the time-varying phase proportioned to the time-varying displacement of chest wall can be obtained. As a result, the information corresponding to respiration and heartbeat motion can be detected.
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/N.C./Examiner, Art Unit 3798
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