DETAILED ACTION
Response to Arguments
Applicant’s arguments filled 11/17/2025 have been fully considered but they are not persuasive. With respect to the rejection under 35 U.S.C. 103 based on Podkamien as modified by Zeng, the Applicant states that the prior art does not disclose or suggest at least “identifying a repeating pattern of Doppler spectrum peaks in a RADAR signal using at least one range bin” or the newly amended “identifying an estimated frequency distance between adjacent peaks of the repeating pattern of Doppler spectrum peaks.” The Examiner respectfully disagrees and maintains the art rejection.
In pages 9 and 10 of their arguments the Applicant states that Zeng “teaches that the radar system can be configured to detect vital sign information, such as respiration or heart rate, by monitoring periodic motion of a surface of the target,” specifically citing that Zeng’s use of slow-time domain features differs from the claimed use of the doppler spectrum itself. The Examiner respectfully disagrees with this assessment. FMCW Slow time measurement merely refers to a received signal organized in an individual chirp manner. Further, Doppler processing is specifically preformed on slow time data. Paragraph [0100] of Seng discloses, “the system 100 generates vital signs features based on the Doppler features.” The aforementioned “Doppler features” are explicitly features in the “doppler spectrum itself.” Zeng discloses using the doppler spectrum of a received signal to detect vital sign information. Further, it is not clear to the Examiner how the Applicant supports the statement that vital sign information of Zeng is acquired by monitoring periodic motion of a surface of the target as this is not stated in the prior art and the use of “slow-time domain features” does not distinguish the prior art from the claimed “Doppler spectrum peaks.”
Referencing paragraph [0100] of Zeng “The system 100 leverages the velocity information, the activity information, or a combination thereof to calculate vital signs features,“ the Applicant states on page 11 of their arguments,“ velocity information is the antithesis of the periodic pattern of doppler/frequency spectrum peaks required by claim 1,” arguing that the use of velocity information distinguished the prior art from the claimed invention. The Examiner further disagrees with this assessment. Velocity estimation may be performed by applying an FFT a set of consecutive chirps from the same range bin. This is the same process as applying a “doppler-FFT” and is pivotal to Doppler-range processing. It is additionally noted that, by the nature of a fast Fourier transform, the “doppler-FFT” places the collected time dependent data into the frequency domain. The “velocity information” disclosed by Zeng is doppler information and explicitly contains information of adjacent peaks in the frequency domain. The disclosed “velocity information” does not distinguish the prior art from the claimed invention
The Applicant further states in page 11 of their arguments, “In short, yes, Zeng must, and does, consider ‘repeating patterns’ in order to arrive at vital sign data, but his proposal is to use velocity information rather than patterns in adjacent peaks in the frequency domain to do so.“ The Examiner respectfully disagrees. As explained in greater detail above, the “velocity information” of Zeng is synonymous to the “peaks in the frequency domain.” Additionally, Zeng states in paragraph [0100] “generates vital signs features based on the Doppler features, the slow-time domain features, or a combination thereof.” As the applicant acquiesces that Zeng considers repeating patterns in the signal, the Examiner maintains that Zeng discloses “identifying a repeating pattern of Doppler spectrum peaks in a RADAR signal using at least one range bin.”
The Applicant further states that the prior art fails to disclose “identifying an estimated frequency distance between adjacent peaks of the repeating pattern of Doppler spectrum peaks.” The Examiner respectfully disagrees. Paragraph [0099] of Zeng discloses, “the system 100 extracts and/or generates Doppler features based on Doppler data from multiple frames 1400. As non-limiting examples, the Doppler features may include FFT energy data, heatmap data, peak features, dimension reduction data, transformation features, any relevant Doppler information, or any number and combination thereof.” Paragraph [0098] of Zeng further discloses that the generated doppler features include dynamic target features. The dynamic behavior of a target embodied in Doppler data is expressed as variation in a doppler range map. It is well known in the art that rhythmic changes in target velocity with a relatively constant position are represented in a doppler range map by repeated peaks at separate frequencies in a constant range bin. This is the same behavior exhibited by breathing or heartrate data. Paragraph [0100] of Zeng additionally discloses, “The Doppler features provide velocity information of a target or radar subject. The system 100 leverages the velocity information to derive the vital signs features.” As Zeng’s disclosed vital signs include breathing and heart rates, Zeng necessary discloses the above limitation.
On Pages 13-17 the Applicant additionally argues the prior art fails to teach or disclose the claimed examination of the doppler spectrum for “periodic or repeating patterns” limitations with respect to independent claim 10. In response the Examiner points to the arguments above as this limitation has been addressed with respect to independent claim 1. The Examiner maintains the art rejection.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6, 10, 11-5, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Podkamien(US20230168364A1) in view of Zeng(US20240069185A1).
Regarding claim 1, Podkamien discloses
A method for identification of a vehicle occupant within a vehicle cabin, the method comprising the steps of: identifying a vehicle occupant within a vehicle using electromagnetic signals (“ Aspects of the present disclosure relate to systems and methods for determining seat occupancy information in a vehicle using a radar sensor.”[0087]) by detecting a vital sign of the vehicle occupant, wherein the vital sign comprises a breathing rate of the vehicle occupant (“Various systems and methods may be used for monitoring vital signs, such as breathing rates and heart-rates of passengers.”[0116]),[…]; assigning the vehicle occupant to a location within the vehicle by processing electromagnetic signals (“The processing unit may be coupled to an indicator for indicating to a driver that a seat is occupied”[0166]); and extracting one or more features about the vehicle occupant by processing electromagnetic signals (“The movements, breathing and heart-rate of each passenger may also be monitored”[0153]) […] and classifying the vehicle occupant by processing electromagnetic signals (FIG.13, FIG.22 & “Additionally or alternatively, a neural network may be trained to identify and categorize passengers, mapping them to classifications such as age category and in-position/out-of position states.”[0111]).
Podkamien does not explicitly disclose nor limit wherein the method includes range doppler processing. Zeng discloses the method comprising
and wherein the breathing rate is calculated by: identifying a repeating pattern of Doppler spectrum peaks in a RADAR signal using at least one range bin (“At phase 1106, according to an example, the system 100 generates Doppler data (e.g., “Doppler-FFT data”) using the range data (e.g., the range-FFT data)”[0066]);identifying an estimated frequency distance between adjacent peaks of the repeating pattern of Doppler spectrum peaks (“the system 100 is configured to select and use one or more target bins that correspond to one or more peaks (local or global maximum values) of range-FFT amplitude values. The system 100 is configured to select and use one or more target bins based on variation levels of one or more peaks of range-FFT amplitude values”[0097]); and calculating an estimated breathing rate using the estimated frequency distance (“The vital signs features include breathing rate data, heart rate data “ [0100]).
Zeng teaches in the same field of endeavor of radar based in vehicle classification systems. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien with the teachings of Zeng to incorporate the features of Doppler Range processing the received radar signal in order to identify breathing rate so as to gain the advantage of increasing radar sensitivity to small or quick movements. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 6, Podkamien as modified by Zeng teaches all of the limitations of claim 1. Podkamien discloses the method further comprising, identifying a scene change within the vehicle (“ The central radar sensor can also determine changes to the cabin apart from the position of passengers. For example, if a door is opened.”[0167]).
Regarding claim 10, Podkamien discloses
A method for classification of an object within a vehicle using RADAR signal processing, the method comprising the steps of: identifying an object within a vehicle using RADAR signals (“Aspects of the present disclosure relate to systems and methods for determining seat occupancy information in a vehicle using a radar sensor.”[0087]); assigning the object to a location within the vehicle by processing RADAR signals(“The processing unit may be coupled to an indicator for indicating to a driver that a seat is occupied”[0166]); […] identifying a scene change within the vehicle (“ The central radar sensor can also determine changes to the cabin apart from the position of passengers. For example, if a door is opened.”[0167]); and in response to identifying the scene change, changing at least one processing parameter of the vehicle (“The sensor chip 160 and processing may be operated only for short periods following an event, such as a door closing, the vehicle accelerating or stopping, etc.”[0120]).
Podkamien does not explicitly disclose nor limit wherein the method includes range doppler processing. Zeng discloses the method comprising extracting one or more features about the object by processing RADAR signals by identifying a repeating pattern of Doppler spectrum peaks in a RADAR signal (“the system 100 is configured to select and use one or more target bins that correspond to one or more peaks (local or global maximum values) of range-FFT amplitude values. The system 100 is configured to select and use one or more target bins based on variation levels of one or more peaks of range-FFT amplitude values”[0097]).
Zeng teaches in the same field of endeavor of radar based in vehicle classification systems. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien with the teachings of Zeng to incorporate the features of Doppler Range processing the received radar signal in order to identify breathing rate so as to gain the advantage of increasing radar sensitivity to small or quick movements. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 11, Podkamien as modified by Zeng teaches all of the limitations of claim 10. Podkamien discloses the method further comprising, classifying the object by processing RADAR signals (FIG.13, FIG.22 & “Additionally or alternatively, a neural network may be trained to identify and categorize passengers, mapping them to classifications such as age category and in-position/out-of position states.”[0111]).
Regarding claim 12, Podkamien as modified by Zeng teaches all of the limitations of claim 10. Podkamien discloses the method wherein, the object comprises a human (“FIG. 10A is a plot of radial displacement as a function of time, as measured for a human subject, in accordance with an embodiment of the invention;”[0064]), and wherein the step of extracting one or more features about the object by processing RADAR signals comprises estimating a rate associated with a vital sign of the human within the vehicle (“Various systems and methods may be used for monitoring vital signs, such as breathing rates and heart-rates of passengers.”[0116]).
Regarding claim 13, Podkamien as modified by Zeng teaches all of the limitations of claim 12. Podkamien discloses the method wherein the step of extracting one or more features about the object by processing RADAR signals (“The movements, breathing and heart-rate of each passenger may also be monitored”[0153])
Podkamien does not explicitly disclose nor limit wherein the method includes range doppler processing. Zeng discloses the method comprising calculating a variance of a frequency difference between Doppler peaks associated with the RADAR signals (“, the system 100 is configured to select and use one or more target bins that correspond to one or more peaks (local or global maximum values) of range-FFT amplitude values. The system 100 is configured to select and use one or more target bins based on variation levels of one or more peaks of range-FFT amplitude values”[0097]).
Zeng teaches in the same field of endeavor of radar based in vehicle classification systems. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien with the teachings of Zeng to incorporate the features of Doppler Range processing the received radar signal in order to identify breathing rate so as to gain the advantage of increasing radar sensitivity to small or quick movements. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 14, Podkamien as modified by Zeng teaches all of the limitations of claim 12. Podkamien discloses the method wherein, the object comprises an occupant of the vehicle, and wherein the step of extracting one or more features about the object by processing RADAR signals comprises: identifying a repeating pattern (“Identify oscillating patterns within a target region such as the vehicle cabin indicative of the vital signs”[0016]) […] and calculating an estimated rate of a repeating vital sign of the occupant within a cabin of the vehicle using the estimated frequency distance(“and process the oscillating signals to isolate breathing signals, heart rate signals and the like”[0116]).
Podkamien does not explicitly disclose nor limit wherein the method includes range doppler processing. Zeng discloses the method comprising, Doppler spectrum peaks in a RADAR signal (“ At phase 1106, according to an example, the system 100 generates Doppler data (e.g., “Doppler-FFT data”) using the range data (e.g., the range-FFT data)”[0066]) using one or more range bins (“Referring to FIG. 14, as a non-limiting example, the system 100 generates Doppler data (e.g., Doppler data of Doppler bin 1408) by performing FFT on a set of range data (e.g., range data of range bin 1404) “[0066]); identifying an estimated frequency distance between adjacent peaks of the repeating pattern (“, the system 100 is configured to select and use one or more target bins that correspond to one or more peaks (local or global maximum values) of range-FFT amplitude values. The system 100 is configured to select and use one or more target bins based on variation levels of one or more peaks of range-FFT amplitude values”[0097]);
Zeng teaches in the same field of endeavor of radar based in vehicle classification systems. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien with the teachings of Zeng to incorporate the features of Doppler Range processing the received radar signal in order to identify breathing rate so as to gain the advantage of increasing radar sensitivity to small or quick movements. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 15, Podkamien discloses
A system for classification of a vehicle occupant using electromagnetic signal processing, comprising: an electromagnetic sensor positioned within a cabin of a vehicle (“For monitoring passengers within a vehicle cabin by a single sensor, a possible position for the sensor may be central to the cabin such that as much as possible of the cabin is within the target range of the sensor.”[0084]);a location detection module configured to process reflected electromagnetic signals to estimate a location of a vehicle occupant within the cabin of the vehicle (“The processing unit 212 is thus able to determine the presence of passengers in each direction”[0105]); and a feature extraction module configured to extract one or more features about the vehicle occupant by processing reflected electromagnetic signals (“The pre-processing unit 312 is thus able to determine the presence of passengers in each direction and to differentiate between adults, children and babies, pets and inanimate objects by determining the size of the occupant, the height, whether the occupant is breathing or displaying a heartbeat and so on”[0112]), wherein the feature extraction module is configured to identify a vital sign associated with the vehicle occupant (“Various systems and methods may be used for monitoring vital signs, such as breathing rates and heart-rates of passengers.”[0116]),
Podkamien does not explicitly disclose nor limit wherein the method includes range doppler processing. Zeng discloses the system wherein, the feature extraction module is configured to use a Doppler signal repetition frequency to estimate a rate associated with a vital sign of the vehicle occupant (“At phase 1106, according to an example, the system 100 generates Doppler data (e.g., “Doppler-FFT data”) using the range data (e.g., the range-FFT data)”[0066]).
Zeng teaches in the same field of endeavor of radar based in vehicle classification systems. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien with the teachings of Zeng to incorporate the features of Doppler Range processing the received radar signal in order to identify breathing rate so as to gain the advantage of increasing radar sensitivity to small or quick movements. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 18, Podkamien as modified by Zeng teaches all of the limitations of claim 15. Podkamien discloses the system wherein, the rate comprises at least one of a breathing rate and a heart rate (“Various systems and methods may be used for monitoring vital signs, such as breathing rates and heart-rates of passengers.”[0116]).
Regarding claim 19, Podkamien as modified by Zeng teaches all of the limitations of claim 15. Podkamien discloses the system wherein, the electromagnetic sensor comprises a RADAR sensor (“Aspects of the present disclosure relate to systems and methods for determining seat occupancy information in a vehicle using a radar sensor.”[0087]).
Regarding claim 20, Podkamien as modified by Zeng teaches all of the limitations of claim 15. Podkamien discloses the system wherein, a classification module configured to classify the vehicle occupant using features extracted using the feature extraction module (FIG.13, FIG.22 & “Additionally or alternatively, a neural network may be trained to identify and categorize passengers, mapping them to classifications such as age category and in-position/out-of position states.”[0111]), wherein the classification module is configured to classify the vehicle occupant according to an estimated age group using a rate associated with a vital sign of the vehicle occupant obtained from the electromagnetic sensor (“This classification is done by examining both the spatial pattern and the temporal displacement data for each element within the target.”[0268] & “The separated components characterize the spatial movement modes associated with each type of movement, e.g. the spatial movement mode associated with respiration and the spatial movement mode associated with heartbeat.”[0283]).
Claims 7 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Podkamien(US20230168364A1) as modified by Zeng(US20240069185A1) in view of Han(US20220113371A1).
Regarding claim 7, Podkamien as modified by Zeng teaches all of the limitations of claim 6. Podkamien discloses the method wherein, the scene change comprises at least one of:
identifying a change in a number of vehicle occupants within the vehicle using electromagnetic signals (“This data may be used by fleet operators to monitor the number of passengers in a vehicle,”[0114]); identifying a change in a location of vehicle occupants within the vehicle using electromagnetic signals (“The memory 326 also stores the previous readings and the spatial components of the detected signals, and changes over time, i.e. their temporal components, and/or possibly also includes a library of standard responses indicative of drivers and passengers of various sizes sitting in the various seats.”[0111]); identifying movement in a door of the vehicle (“The central radar sensor can also determine changes to the cabin apart from the position of passengers. For example, if a door is opened.”[0167])
Podkamien as modified by Zeng does not explicitly disclose nor limit wherein the method includes threshold vehicle velocity detection. Han discloses the method comprising identifying a threshold change in velocity of the vehicle (“event-triggered measurement (for example, performing measurement based on a specified event, where the event may be, for example, that a vehicle speed change exceeds a specified threshold)”[0081])
Han teaches in the same field of endeavor of vehicle sensor systems including vehicle radar detection. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Podkamien as modified by Zeng with the teachings of Han to incorporate the features of threshold vehicle velocity detection so as to gain the advantage of improving event based processing and implementing vehicle safety features. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 9, Podkamien as modified by Zeng and further modified by Han teaches all of the limitations of claim 7. Podkamien discloses the method further comprising, in response to identifying the scene change, changing at least one processing parameter associated with at least one of the steps of extracting one or more features about the vehicle occupant and classifying the vehicle occupant (“The sensor chip 160 and processing may be operated only for short periods following an event, such as a door closing, the vehicle accelerating or stopping, etc.”[0120] & “he information of occupancy, age class and out-of-position thus determined may be transferred to the rules database 320 which determine actions for each seat based on the received information.”[0212])
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 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 CLAYTON PAUL RIDDER whose telephone number is (571)272-2771. The examiner can normally be reached Monday thru Friday ET.
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/C.P.R./Examiner, Art Unit 3646
/JACK W KEITH/Supervisory Patent Examiner, Art Unit 3646