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 Amendment
The amendment filed 06/01/2026 has been entered. Claims 1-20 are pending in this application. Applicant’s amendment overcomes the 101 rejections from the previously filed Office Action. Examiner maintains the provisional non-statutory double patenting rejection as set forth in the previous Office Actions.
Response to Arguments
Applicant's arguments filed 06/01/2026 regarding the 103 rejections of claims 1-20 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments for the USC § 103 rejection of claim 1, Applicant argues on pgs. 13-15 of the Remarks,
“As mentioned in the Office Action, Weitnauer discloses frequency-domain harmonic analysis for estimating physiological characteristics. However, Weitnauer does not disclose the amended limitations of claim 1. In particular, Weitnauer does not disclose processing reflected RADAR signals received from within a vehicle cabin into a plurality of different range bins, identifying a repeating pattern of Doppler spectrum peaks in RADAR signal data corresponding to at least two of the plurality of different range bins, identifying an estimated frequency distance for each of the at least two range bins, and calculating the estimated rate by combining vital-sign rate estimates generated from those frequency distances.
Weitnauer's reference to "bins" does not disclose or suggest Applicant's claimed range bins. Weitnauer's bins are DFT bins-i.e., frequency-domain indices produced by applying a DFT to time-domain measurement data. Paragraph [0042] of Weitnauer explains that the x-axis of FIG. 4 is in DFT bins and that those DFT bins correspond to frequencies of the digitally sampled time-domain data.
By contrast, the claimed range bins are RADAR range bins corresponding to different distances from an in-cabin vehicle sensor. The disclosure of the Application expressly distinguishes these concepts, explaining that FIG. 3 shows signals in different range bins, that each range bin represents a distance from the sensor, and that each frequency bin represents a frequency band. See Application at I [0039]…
… Hazra does not cure these deficiencies. The Office Action relies on Hazra for identifying a repeating pattern over a plurality of range bins. However, the cited portions of Hazra relate to target detection and localization rather than the claimed multi-range-bin vital-sign extraction technique.
For example, Paragraphs [0045]-[0048] of Hazra describe generating range data or a range image, such as a range-Doppler image or range-angle image, identifying potential targets based on power levels in the range image, identifying a range of interest or target bin, and clustering target range bins to fuse a target point cloud and determine a mean range of a single target. These disclosures concern identifying or localizing a target. They do not disclose calculating a vital-sign rate estimate from an estimated frequency distance between adjacent Doppler spectrum peaks for each of at least two range bins, much less combining such range-bin- specific vital-sign rate estimates to calculate the estimated rate.
Hazra's vital-sign estimation pipeline is materially different. After identifying target data, Hazra proceeds by generating target I/Q data and a target displacement signal, then estimating a vital sign from that displacement signal. See, e.g., Hazra " [0049]-[0053], [0095]. Thus, even if Hazra processes multiple range bins during target detection, Hazra does not use multiple range bins in the manner now recited in amended claim 1. Indeed, Hazra does not identify an estimated frequency distance between adjacent peaks of a repeating Doppler spectrum pattern for each of at least two range bins, does not generate vital-sign rate estimates from such frequency distances for at least two range bins, and does not combine those vital-sign rate estimates to calculate the estimated rate.
The rejection therefore relies on the cited references at too high a level of generality. It is not enough that Weitnauer generally teaches harmonic peak spacing and Hazra generally teaches range-bin target detection. Amended claim 1 requires a specific multi-range-bin vital-sign extraction process in which reflected in-cabin RADAR signals are processed into range bins, Doppler peak-spacing estimates are identified for at least two range bins, and vital-sign rate estimates generated from those range-bin-specific frequency distances are combined.”
Examiner respectfully disagrees. Weitnauer does not explicitly teach “range bins,” but the teachings of Hazra read onto the claim limitations as written. Hazra discloses receiving radar signals in the cabin of a vehicle to measure a person’s vital signs. The received data is formed into I/Q data, which then after quality sorting is generated into a displacement signal that represents small body motion, such as chest movement from breathing and heartbeat, which is then used to measure vital signs (see Hazra paragraphs 0005-008, 0030-0032, and 0075-0099). The displacement signal measures distance and range, and range bins are needed to generate displacement signal; therefore Hazra does disclose processing reflected radar signals into a plurality of different range bins. The combination of the target detection and localization techniques of Hazra (range bins, which leads to vital sign estimation) with the peak-to-peak detection technique of Weitnauer teaches a multi-range-bin vital-sign extraction process. The teachings of Weitnauer can be applied to the range bins of Hazra. See 103 rejection section of this Office Action for further claim 1 mapping.
Regarding the amended limitation of automatically initiating or modifying operation of at least one vehicle function, tertiary reference Zeng (US 20240069185 A1) discloses a vehicle action as a result of the detected vital sign. Even if Hazra was insufficient to teach the amended claim limitations, Zeng also teaches range bins and target bins (see Zeng Fig. 14, range bins; Fig. 11, raw adc samples 1102 into range fft 1104; paragraph 0080, one or more target bins are selected that correspond to one or more peaks.)
Regarding Applicant’s arguments for the USC § 103 rejection of claim 9, Applicant argues on pg. 17 of the Remarks,
“As discussed above, Weitnauer's "bins" are DFT bins-frequency-domain indices produced by applying a DFT to time-domain measurement data-not range bins corresponding to different distances from an in-cabin vehicle sensor. Thus, Weitnauer's frequency-bin harmonic analysis does not teach or suggest the amended claim 9 requirement of identifying a signal repetition frequency from Doppler spectrum data corresponding to a plurality of range bins, including a target range bin and at least one adjacent or otherwise associated range bin.
Hazra does not cure these deficiencies. Although Hazra may process range- bin data when detecting or localizing a target, Hazra does not disclose identifying a signal repetition frequency comprising an estimated frequency distance between adjacent peaks in a repeating pattern of Doppler spectrum peaks identified in Doppler spectrum data corresponding to a target range bin and at least one adjacent or otherwise associated range bin. Instead, Hazra's range-bin processing is used for target detection/localization, after which Hazra proceeds with target I/Q data and a displacement-signal pipeline for vital-sign estimation.”
Examiner respectfully disagrees. Weitnauer discloses identifying peak patterns and signal repetition frequency. Hazra discloses Doppler data and target range bins being analyzed with adjacent range bins. It is reasonable to believe that the identifying peak pattern and signal repetition process of Weitnauer could be applied to the Doppler data and range bins of Hazra. The same cited sections, rationale, and analysis from above regarding claim 1 is applied to the arguments regarding claim 9.
Regarding Applicant’s arguments for the USC § 103 rejection of claim 16, the same cited sections, rationale, and analysis from claim 1 and claim 9 are applied.
For at least these reasons, Examiner is unpersuaded and maintains previous rejections corresponding to the USC § 103 rejection. Therefore, the Examiner asserts that Weitnauer (US 20140378809 A1) and Hazra et al. (US 20230393259 A1) and Zeng (US 20240069185 A1) disclose each and every limitation of independent claim 1 based on the broadest reasonable interpretation of claim 1. The same cited sections and rationale are applied to the independent claims 9 and 16.
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.
Claims 1-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Weitnauer (US 20140378809 A1) in view of Hazra et al. (US 20230393259 A1) and further in view of Zeng (US 20240069185 A1).
Regarding claim 1, Weitnauer discloses [Note: what Weitnauer fails to disclose is strike-through]
A method for detection of an occupant vital sign (see Abstract, “Methods, systems and computer program products are provided estimating a physiological characteristic of a subject based on a reflected signal received by a UWB radar system”), the method comprising the steps of:
identifying a repeating pattern of Doppler spectrum peaks in RADAR signal data corresponding to at least two of the plurality of (see Fig. 2, discern harmonics elements 118; pg. 6, paragraph 0049, “block 118 may involve an additional or alternative evaluation process of comparing peak-to-peak distances (in the frequency or bin domain) between pairs of peaks”; Fig. 4, spectrum with peaks in a variety of bins; Fig. 6C, peaks associated with different bins);
identifying an estimated frequency distance between adjacent peaks of the repeating pattern for each of the at least two range bins (see pg. 6, paragraph 0054, “the harmonic test may involve: evaluating the average peak-to-peak separation f of the peaks in the path (in the frequency or bin domain);”; Fig. 6C, peaks associated with different bins); and
calculating an estimated rate of a repeating vital sign of an occupant s by combining vital-sign rate estimates generated from the estimated frequency distances for the at least two range bins; and (see Fig. 7A, step 124 of estimating physiological characteristic after computing peak to peak distance; paragraph 0075, “Method 230 then proceeds to block 234 which comprises using the set of block 232 to apply a pair-wise distance evaluation to discern pairs of peaks which are spaced apart (in the bin/frequency domain) by distances that correspond to viable heart rates for the particular subject and to reject pairs of peaks which are spaced apart (in the bin/frequency domain) by distances that correspond to heart rates that are not-realistic for the particular subject.”; paragraph 0087, “ A variety of different techniques may be used alone or in combination to select the preferred path in block 286. In some embodiments, a metric based on the amplitudes of the peaks belonging to the paths may be used to select a preferred path in block 286. In some embodiments, the selection metric comprises average peak amplitude of the peaks in the path and the path with the highest average peak amplitude is selected to be the preferred path. In some embodiments, selection of the preferred path in block 286 is based at least in part on the power associated with the peaks in each path. By way of non-limiting example, in some embodiments, the preferred path may comprise the path with the highest average power per peak. Various techniques for determining the power associated with a peak are described above. Any of these techniques may be used in the block 286 selection. Another non-limiting example of a suitable technique which may additionally or alternatively be used, in some embodiments, for the block 286 selection as between paths may comprise selecting the path with the highest aggregate power associated with its peaks to be the preferred path. The power of each peak may be determined as described above and then these peak powers may be aggregated (e.g. summed) as opposed to averaged. This technique might give a preference to relatively long paths, which have a greater number of peaks.”)
Hazra discloses [Note: what Hazra fails to disclose is strike-through]
detection of an occupant vital sign from within a cabin of a vehicle (see pg. 2, paragraph 0029, “Some embodiments may be used for monitoring a driver of a car.”)
processing reflected RADAR signals received from within the cabin of the vehicle into a plurality of different range bins (paragraph 0045, “In some embodiments, range data, such as a range image, such as a range-Doppler image (RDI) or a range-angle image (RAI) is generated during step 206.”);
identifying a repeating pattern… corresponding to at least two of the plurality of different range bins (see pg. 3, paragraph 0045, “In some embodiments, range data, such as a range image, such as a range-Doppler image (RDI) or a range-angle image (RAI) is generated during step 206”; pg. 3, paragraph 0046, “ During step 208, detection of potential targets is performed…For example, in some embodiments, potential targets are identified by comparing power levels of the range image with a threshold, where points above the threshold are labeled as targets while points below the threshold are labeled as non-targets. In some embodiments, the range of interest associated with the detected target (the target distance or target bin) is identified based on the location of peaks of the range image having power levels above the threshold.”; pgs. 3-4, paragraph 0048, “ In some embodiments, target range bins are clustered to “fuse” the target point cloud belonging to one target to a single target and thus determine the mean range of such single target…In some embodiments, the clustered targets are used to identify the range of interest associated with the detected target (the target distance or target bin).”)
calculating an estimated rate of a repeating vital sign of an occupant within the cabin of the vehicle (see pg. 5, paragraphs 0072 and 0073, example of vital sign estimate settings such as “a human target driving a car at a distance…from the millimeter-wave radar sensor 102 (which may be located, e.g., in a steering wheel or dashboard of a car)”)
Zeng discloses
automatically initiating or modifying operation of at least one vehicle function based at least in part on the estimated rate (paragraph 0047, “The system response may include actions relating to one or more components of the vehicle 10. In this regard, the one or more components may include an electronic component, a computer component, a mechanical component, or any number and combination thereof. For example, the system 100 is configured to generate control data for a system response, which includes controlling deployment of an airbag associated with a seat inside the vehicle 10 based on the class data of that seat. More specifically, for instance, the system response includes activating or enabling deployment of an airbag associated with a seat when the class data indicates or suggests that the radar subject located at the seat is a human (e.g., a human, an adult, etc.). Also, the system response includes deactivating or disabling deployment of an airbag associated with a seat inside the vehicle when the class data indicates or suggests that the radar subject at that seat is not human (e.g., box, backpack, etc.).”).
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Hazra and Zeng into the invention of Weitnauer. Zeng, Weitnauer, and Hazra are considered analogous arts to the claimed invention as they all disclose vital sign monitoring with radar signals. Weitnauer discloses identifying a repeating pattern of radar peaks over a plurality of discrete Fourier transform (DFT) bins, identifying an estimated frequency distance between peaks, and calculating a rate of a vital sign using the frequency distance; however, Weitnauer fails to disclose identifying a pattern over range bins, the application of the vital sign detection radar within the cabin of a vehicle, and initiating or modifying operation of at least one vehicle function based at least in part on the estimated rate. These features are disclosed by Hazra and Zeng. In Hazra, the vital sign detection can be applied to a driver of a vehicle, and range bins and target bins can be derived from range-Doppler data where potential targets are identified within those bins when the targets surpass a threshold. In Zeng, the vehicle can respond with various actions to the vital sign rate estimation and its corresponding classification. Using a bin in the range-Doppler map requires that each bin correspond to both a frequency and a distance (i.e. ranging with range bins). Weitnauer does not teach Doppler signals, but Hazra and Zeng do. Hazra teaches a range-Doppler map. It is reasonable to believe that the peak-to-peak distance signal analysis process of Weitnauer could be applied to the range bins of Hazra and Zeng to produce the same result, a vital sign rate estimation. The combination of Zeng, Weitnauer, and Hazra would be obvious with a reasonable expectation of success in order to analyze data with existing radar signal analysis techniques, reduce the manufacturing cost of having to create new software or hardware to accommodate the detection process, and increase vehicle safety by modifying vehicle operations based on detected passengers. The combination would also be obvious to apply to in-vehicle vital sign detection of an occupant as a practical application of health monitoring in a frequently occupied space, such as a car.
Regarding claim 2, Weitnauer further discloses
The method of claim 1, wherein the estimated repeating vital sign comprises a breathing rate (see pg. 2, paragraph 0021, “In some embodiments, the physiological characteristic comprises a respiration rate of a human”).
Regarding claim 3, Weitnauer further discloses
The method of claim 1, wherein the estimated repeating vital sign comprises a heart rate (see pg. 2, paragraph 0021, “In some embodiments, the physiological characteristic comprises a heart rate of a human”).
Regarding claim 4, Weitnauer further discloses
The method of claim 1, wherein the step of identifying a repeating pattern of Doppler spectrum peaks comprises selecting a strongest repeating signal from among a plurality of RADAR signals (see pg. 5, paragraph 0045, “Accordingly, in some embodiments, block 118 comprises discerning ascertaining local maxima (peaks) in frequency domain data 116. In some embodiments, such peak detection may comprise application of a suitable power threshold to select peaks of interest (i.e. peaks which may be considered to be candidates for the heart rate harmonic set may be discerned to have local maxima that are greater than the power threshold).”).
Regarding claim 5, Weitnauer further discloses [Note: what Weitnauer fails to disclose is strike-through]
The method of claim 4, further comprising:
identifying an estimated frequency distance between adjacent peaks of a repeating pattern from a RADAR signal in the at least one range bin adjacent to the range bin associated with the strongest signal (see Fig. 4; pg. 6, paragraph 0049, example of adjacent bin peak-to-peak analysis).
Hazra discloses
selecting at least one range bin adjacent to a range bin associated with the strongest signal (see pgs. 3-4, paragraph 0048, “ In some embodiments, target range bins are clustered to “fuse” the target point cloud belonging to one target to a single target and thus determine the mean range of such single target…In some embodiments, the clustered targets are used to identify the range of interest associated with the detected target (the target distance or target bin).”; and
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Hazra into the invention of Weitnauer. Weitnauer discloses identifying an estimated frequency distance between peaks in DFT bins adjacent to a bin with the strongest signal; however, Weitnauer fails to disclose signal identifying over range bins. This feature is disclosed by Hazra where multiple range bins can be combined to help identify a range of interest. The combination of Weitnauer and Hazra would be obvious with a reasonable expectation of success in order to analyze data with existing radar signal analysis techniques in the range domain instead of a DFT bin domain, providing an alternative way of displaying and analyzing the radar data.
Regarding claim 6, Hazra further discloses
The method of claim 5, further comprising using the estimated frequency distance between adjacent peaks of a repeating RADAR signal in the at least one range bin adjacent to the range bin associated with the strongest signal to improve accuracy of at least one estimated parameter derived from the repeating RADAR signal (see pg. 3, paragraph 0046, “During step 208, detection of potential targets is performed. … In some embodiments, the range of interest associated with the detected target (the target distance or target bin) is identified based on the location of peaks of the range image having power levels above the threshold.”; pgs. 3-4, paragraph 0048, “In some embodiments, target range bins are clustered to “fuse” the target point cloud belonging to one target to a single target …In some embodiments, the clustered targets are used to identify the range of interest associated with the detected target (the target distance or target bin).”).
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Hazra into the invention of Weitnauer. Weitnauer fails to disclose using bin peak measurements to improve the accuracy of a parameter such as location of an occupant. This feature is disclosed by Hazra where an area of interest for target distance can be determined using peaks and multiple range bins. The combination of Weitnauer and Hazra would be obvious with a reasonable expectation of success in order to narrow the area of interest to reduce the load of signal analysis, and to make sure the radar signals are being sent to and from the appropriate target.
Regarding claim 7, the same cited sections and rationale from claim 6 are applied.
Regarding claim 8, Hazra further discloses
The method of claim 1, further comprising classifying the occupant using the estimated repeating vital sign (see pg. 10, paragraph 0131, “During step 1504, a DNN is used to classify the RDIs into 3 possible classes: 0 humans (1506), 1 human (1508), and more than 1 human (1510).”).
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Hazra into the invention of Weitnauer. Weitnauer fails to disclose classifying an occupant using the estimated repeating vital sign. This feature is disclosed by Hazra a DNN (deep neural network) can classify the occupants based on an RDI (range-Doppler image). The combination of Weitnauer and Hazra would be obvious with a reasonable expectation of success in order to identify how many people are within the range of the radar device, and execute the vital sign detection process accordingly, potentially saving energy by not executing the method when no occupants are detected.
Regarding claim 9, the same cited sections and rationale from claim 1 are applied. Hazra discloses range-Doppler data and target range bins. Weitnauer further discloses
transmitting one or more electromagnetic signals within a cabin of a vehicle (see pg. 2, paragraph 0024, “UWB radar system 30 generates UWB pulses (or impulses) that are transmitted by antenna system 31 into a space where the subject may be located”);
processing signals associated with the one or more electromagnetic signals (see pg. 2, paragraph 0024, “If a person is present in the sensing volume, then the pulses transmitted by UWB transmitter 30A are reflected at interfaces within the person's body (e.g. the surfaces of the lungs and heart) and the corresponding reflected pulses may be received at antenna 31 and detected by UWB receiver 30B”; Fig. 1A, signal processing 33 coupled to UWB radar and receiver 30B);
Regarding claim 10, Weitnauer further discloses
The method of claim 9, wherein the signals associated with the one or more electromagnetic signals comprise reflected signals (see pg. 2, paragraph 0024, “If a person is present in the sensing volume, then the pulses transmitted by UWB transmitter 30A are reflected at interfaces within the person's body (e.g. the surfaces of the lungs and heart) and the corresponding reflected pulses may be received at antenna 31 and detected by UWB receiver 30B”), and wherein the step of processing reflected signals comprises processing reflected signals from the one or more electromagnetic signals in a plurality of range bins (see Fig. 4; pg. 5, paragraph 0042, description example of data signal processing in bins).
Regarding claim 11, the same cited sections and rationale from claim 5 are applied.
Regarding claim 12, Weitnauer further discloses
The method of claim 11, further comprising identifying the target range bin by comparing signal strengths of the reflected signals (see pg. 5, paragraph 0045, “Accordingly, in some embodiments, block 118 comprises discerning ascertaining local maxima (peaks) in frequency domain data 116. In some embodiments, such peak detection may comprise application of a suitable power threshold to select peaks of interest (i.e. peaks which may be considered to be candidates for the heart rate harmonic set may be discerned to have local maxima that are greater than the power threshold).”).
Regarding claim 13, Weitnauer further discloses
The method of claim 9, wherein the one or more electromagnetic signals comprise RADAR signals (see pg. 2, paragraph 0024, “UWB radar system 30 generates UWB pulses (or impulses) that are transmitted by antenna system 31”).
Regarding claim 14, Weitnauer further discloses
The method of claim 9, further comprising transmitting one or more electromagnetic signals within a cabin of a vehicle to an intended direction corresponding with an anticipated location of an occupant (see pg. 2, paragraph 0024, “UWB radar system 30 generates UWB pulses (or impulses) that are transmitted by antenna system 31 into a space where the subject may be located”).
Regarding claim 15, the same cited section as claim 2 applies.
Regarding claim 16, the same cited sections and rationale from claim 1 and claim 9 are applied.
Regarding claim 17, Weitnauer further discloses
The system of claim 16, wherein the electromagnetic sensor comprises a RADAR sensor (see Fig. 1A, UWB radar 30).
Regarding claim 18, Zeng discloses
The system of claim 16, further comprising a classification module configured to receive information from the vital sign module and classify the occupant according to an age group using the rate associated with the vital sign of the occupant (see Fig. 13, vital signs features element 1312 and classifier element 1318; Pg. 5, paragraph 0043, “the system 100, via the classifier, is operable to generate (i) an adult label when the radar subject is classified as being an adult (ii) a child label when the radar subject is classified as being a child, and (iii) a baby label when the radar subject is classified as being a baby.”).
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Zeng into the invention of Weitnauer and Hazra. Weitnauer and Hazra fail to disclose a classification module that can classify an occupant to an age group based on the received vital sign rate. This feature is disclosed by Zeng where the vital sign elements can be used to classify an occupant to an age group. The combination of Weitnauer, Hazra, and Zeng would be obvious with a reasonable expectation of success in order to identify if an occupant has a vital sign rate outside of the normal range for their age group, allowing monitoring of a health or medical issue.
Regarding claim 19, the same cited section as claim 2 applies.
Regarding claim 20, the same cited section as claim 14 applies.
Additional Relevant Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure and may be found on the accompanying PTO-892 Notice of References Cited:
Lorato (US20190008459A1); A method for detecting a vital sign of a subject (102) comprises: receiving (302) a reflected radio frequency signal from the subject (102), the reflected signal being based on a transmitted signal, which is Doppler-shifted due to mechanical movements corresponding to the heart rate and/or the respiratory rate; dividing (304) a baseband signal into a sequence of sliding windows (200), each sliding window (200) representing a time interval; estimating (306) a vital sign parameter in at least one sliding window (200); determining (308) whether a vital sign parameter may be reliably estimated in at least one sliding window (200); on condition that the vital sign parameter may not be reliably estimated in a sliding window (200), determining (310) a vital sign parameter of the sliding window (200) based on vital sign parameters estimated in a plurality of windows representing time intervals close to the time interval of the window (200).; see paragraphs 0036-0037 regarding vital sign detection in the frequency domain
Bliss et al. (US20220142478A1); A precise cardiac data reconstruction method is provided, which may also be referred to herein as radar cardiography (RCG). RCG can reconstruct cardiac data, such as heart rate and/or electrocardiogram (ECG)-like heartbeat waveform signals wirelessly by using advanced radar signal processing techniques. For example, heartbeat and related characteristics can be monitored by isolating cardiovascular activity from strong respiratory interference in spatial spaces: azimuth and elevation. This results in significant improvements to pulse signal-to-noise-ratio (SNR) compared to conventional approaches, facilitating heart-rate variability (HRV) analysis.; see range-Doppler spectrum in Fig. 11
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISABELLA A EDRADA whose telephone number is (571)272-4859. The examiner can normally be reached Mon - Fri 9am-5pm ET.
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/ISABELLA A EDRADA/Examiner, Art Unit 3648
/BERNARR E GREGORY/Primary Examiner, Art Unit 3648
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