DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 02/24/2025 have been fully considered but they ARE persuasive.
Applicant remarks on page 11 that Lev (US 20220007950 A1) does not teach any object detection model, Sobel operator, image peak search algorithm, and/or radar peak search algorithm to determine presence and/or vitals information as required by claim 1.
Examiner respectfully disagrees with Applicant’s assertions.
Regarding the objection detection model, [0076] at least suggests object detection, stating that “human motion (intentional and/or unintentional) during the measurement may affect some sensors datasets more than others. For example, motion may affect the reliability of computing the respiratory rate sub-physiological parameter more than that of computing the heartbeat/temperature/oximetry sub-physiological parameter. The dataset may be analyzed to detect motion (e.g., analyzes images outputted by RGB/IR image sensors or other sensors to detect excessive motion of the person). The dataset with motion may be excluded from computation of the respiration parameter sub-physiological parameter”. Lev is not relied upon for the teaching of a Sobel operator. Rather, prior art Sendai is relied upon for its teaching of Sobel filter in [0022].
Regarding the image peak search algorithm and the radar peak search algorithm, newly found prior art, Garn, et al., US 20170215772 A1, has been applied in combination with the teachings of modified Lev. Specifically, Garn, et al., states in [0048] that “A numerically simple filtering of the signal, which largely suppresses interfering noise, provides for the processing unit to subject the signal to a spectral transformation, in particular a Fourier transform, a cosine transform or wavelet transform, and search for the spectral component with the highest signal energy within a predetermined frequency band, in particular from 0.1 Hz to 1 Hz, and use the signal energy of this spectral component to characterize the depth of respiration in this segment”.
Applicant further asserts on page 11 that Lev does not teach “at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information, for at least one second point of interest identified via at least one filter applied to the frequency change of the reflections”.
Newly found prior art teaches the limitation in question as demonstrated above.
Applicant further argues on page 11 that Boric-Lubecke fails to teach any RGB image-based and/or IR image-based presence detection, much less the particular processing techniques, and hence fails to remedy the deficiencies of Lev.
Lev teaches object detection as demonstrated above.
Applicant further argues on page 12 that Strasfield does not teach or suggest any RGB image-based and/or IR image-based presence detection algorithm.
Lev teaches object detection as demonstrated above.
Applicant further argues on page 12 that Sendai does not teach any radar-based vitals detection at all, much less “at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information, for at least one second point of interest identified via at least on filter applied to the frequency change of the reflections”.
Newly found prior art teaches the limitation in question as demonstrated above.
Applicant further argues on page 12 that Schultes fails to teach any RGB image-based and/or IR image-based presence detection to improve radar-based presence and/or vitals detection.
Therefore, the claims stand rejected.
Double Patenting
Examiner acknowledges Applicant’s request to hold the double patenting rejection until a determination of allowability of the claims is made.
Withdrawn Objections
Pursuant of Applicant’s amendments filed 11/04/2025, the objections made to claims 1, 7, and 12 have been withdrawn.
Withdrawn Rejections
Pursuant of Applicant’s amendments filed 11/04/2025, the rejection of claims 1-19 under 35 U.S.C. 112(a) have been withdrawn.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-10, 12-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Lev, et al., US 20220007950 A1 in view of Strasfeld, et al., US 20210228083 A1 and Boric-Lubecke, et al., US 20080119716 A1, Sendai, T., US 20060025672 A1, and Garn, et al., US 20170215772 A1.
Regarding claim 1, Lev teaches a system for presence and vitals detection of a living subject (system 200 of paragraph 58), the system comprising:
an infrared (IR) imaging sensor (paragraph 61 discloses RGB sensor, short-wave infrared (SWIR) sensors; paragraph 76 also discloses an RGB/IR image sensor);
a radar (paragraphs 61 and 82 discloses a doppler and/or radar sensor);
a processor (paragraph 58); and
a user interface (user interface of paragraph 65);
wherein the radar (paragraph 82) detects subtle movements from the living subject (paragraph 93 indicates that Graph 502 indicates that the non-contact sensor accurate generates an indication of movement of a chest (e.g., chest displacement) which may be used for computing sub-physiological parameter(s) such as respiratory rate and/or heart rate);
wherein the processor (204 of fig. 2 and paragraph 58) is configured to run an algorithm to perform digital signal processing on data provided by the radar and the RGB imaging sensor (In [0048] the generating of respiratory rate/temperature information is an indication of a presence of the living subject and hence comprises presence information) to:
generate, using at least one object detection model trained to detect the living subject in images ([0028] states that “the extracting and the analyzing and the computing the physiological parameter comprises obtaining an outcome of a classifier trained on a training dataset”, and [0102] stating that “the term classifier may refer, for example, to a statistical classifier and/or machine learning model that maps inputs to an outcome”), presence information comprising an IR imaging-based presence of the living subject based on a detection of the light reflected by the living subject ([0048] indicates generating respiratory rate/temperature [and thus vitals/presence] and heart rate data [vitals] from the RGB sensor and the radar sensor, respectively);
wherein the presence information comprises identification and location of the living subject ([0026] states that “a second of the plurality of remote non-contact sensors comprises a Doppler and/or radar sensor, and further comprising code for: analyzing at least one thermal and/or visual image to identify a target location of the chest and/or head of the person”, where the thermal and/or visual image comprises the presence information for identification and locating of the living subject);
generate, in response to the presence information, vitals information for the living subject ([0026] further states that “wherein a first sub-physiological parameter is extracted from a first dataset acquired by the thermal and/or visual sensor, and a second sub-physiological parameter is extracted from a second dataset acquired by the Doppler and/or radar sensor”, the sub-physiological parameter comprising vitals such as respiratory rate and/or heart rate according to [0043],[0046]) and
output the vitals information and the presence information for communication to the user interface (“Computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 that include a mechanism for entering data and/or viewing data, for example, a touchscreen display used to indicate a new person for analysis, and/or for presenting the computed physiological parameter” [0065]).
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Lev fails to teach wherein the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources.
However, Strasfeld teaches techniques for skin diagnostics based on multispectral images of light reflections from the skin (paragraph 6) using infrared RGB imaging sensors (paragraphs 29-30) wherein the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources (paragraph 50 indicates that the images acquired are reflectance images and further that detection can be based on reflection measurements, meaning that the RGB IR imaging sensors detect reflections from the skin of the patient for the image formation; paragraphs 6-7).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev such that the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources, as taught by Strasfeld, providing a low-cost portable method of skin diagnostics using optical signatures (paragraph 30).
Lev in view of Strasfeld fails to teach that the radar emits a radiofrequency at a specific frequency, and detects a frequency change of reflections of a plurality of targets.
However, Boric-Lubecke teaches systems and methods for determining presence and/or physiological motion of at least one subject using a Doppler radar system having a quadrature receiver (see abstract), wherein the Doppler radar emits a radiofrequency at a specific frequency (paragraph 56 discloses a continuous wave Doppler radar transmitting a single tone signal at a specific frequency), and detects a frequency change of reflections of a plurality of targets which have subtle movements from the living subject (paragraph 56 indicates modulation of the reflected signals from the incident radar due to respiratory and/or heart activity. Paragraph 58 indicates that the observed area is the entirety of a subject’s chest and hence multiple local displacements are measured).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld, such that radar emits a radiofrequency at a specific frequency, and detects a frequency change of reflections of a plurality of targets, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Lev in view of Strasfeld and Boric-Lubecke fail to teach region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via at least one filter applied to the frequency change of the reflections.
However, within the same field of endeavor, Sendai teaches that a test subject having a contour that varies with the respiration is optically imaged continuously by the optical image obtaining section to sequentially obtain optical images of the subject, and respiratory phases of the subject are detected simultaneously with the optical imaging by the respiratory phase detecting section based on the contour of the subject on the optical images. (see abstract), [0019] stating that “a respiratory phase detecting means for sequentially receiving optical images of a test subject having a geometric feature that varies at least partially with respiration of the subject obtained by imaging the subject continuously, and sequentially detecting respiratory phases of the test subject based on the geometric feature of the subject on the optical images” and [0022] stating that “If the "geometric feature" is a "shadow region of a test subject" (e.g. a shadow region formed by a collarbone, rib or the like), the shadow region is detected as an edge within the subject image region on an optical image using an edge detecting filter (e.g. Sobel filter, Laplacian filter or the like), and respiratory phases of the subject are detected based on the changes in the position of the detected edge on the image arising from respiration of the subject. In order to know the changes in the position of the edge, it is necessary to identify which edges correspond with each other between two temporally successive optical image frames obtained continuously”. Of note, the optical image data is obtained by optically detecting visible light rays reflected from a subject, according to [0024]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld and Boris-Lubecke, to perform the region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via a second Sobel operator applied to the frequency change of the reflections, as taught by Sendai, as such modification would provide stable accuracy for detecting respiratory phases of the subject according to paragraph 9.
Lev in view of Strasfeld, Boric-Lubecke and Sendai fail to teach generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified.
However, within the same field of endeavor, Garn teaches a method and a device determine a time curve of the depth of breath of a sleeping person (see abstract). [0047] discloses extracting “at least one maximum and at least one minimum from the signal for the purposes of characterizing the depth of respiration in a segment” and [0048] discloses that “A numerically simple filtering of the signal, which largely suppresses interfering noise, provides for the processing unit to subject the signal to a spectral transformation, in particular a Fourier transform, a cosine transform or wavelet transform, and search for the spectral component with the highest signal energy within a predetermined frequency band, in particular from 0.1 Hz to 1 Hz, and use the signal energy of this spectral component to characterize the depth of respiration in this segment”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev as modified by Strasfeld, Boric-Lubecke and Sendai, for generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified, as taught by Garn, for low noise extraction of respiratory movement ([0049]).
Regarding claim 2, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 1.
Lev further teaches wherein the subtle movements are caused by the respiration and/or ballistocardiography from the living subject (paragraph 93).
Regarding claim 3, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 1.
Lev in view of Strasfeld fails to teach wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar.
However, Boric-Lubecke further teaches wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar (paragraph 56 indicates that the Doppler radar is a continuous wave (CW) radar system).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld, wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Regarding claim 4, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 1.
Lev further teaches wherein the user interface comprises a second communication module for receiving data from a first communication module in communication with the processor (paragraph 65 indicates that computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 via network interface 222 of paragraph 62. While not explicitly disclosed as a first communication module and a second communication module, communication between the physical user interface 224 and the computing device 204 would inherently and necessarily include hardware and instructions for the stated communication between a first communication module or feature and a second communication module or feature in order to perform the communication).
Regarding claim 5, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 1.
Lev further teaches wherein the IR imaging sensor is one of a red-green-blue (RGB) IR imaging sensor or short-wave (SW) IR imaging sensor ([0076] discloses RGB/IR image sensors).
Regarding claim 6, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 1.
Lev further teaches wherein the user interface presents data using a light emitting diode (LED), a display or a speaker ([0065] discloses a display).
Regarding claim 7, Lev teaches a method for presence and vitals detection of a living subject(fig. 1 and paragraph 58), the method comprising:
detecting at a radar(paragraph 82 discloses a doppler and/or radar sensor), subtle movements from the living subject (paragraph 93 indicates that Graph 502 indicates that the non-contact sensor accurate generates an indication of movement of a chest (e.g., chest displacement) which may be used for computing sub-physiological parameter(s) such as respiratory rate and/or heart rate).
receiving at a processor(204 of fig. 2 and paragraph 58) of the monitoring device the data from the radar and the IR imaging sensor(paragraph 48 indicates computing physiological parameters such as respiratory rate and/or heart rate from the thermal sensors, that is IR camera and Doppler and/or radar sensor);
running on the processor an algorithm to perform digital signal processing on the data provided by the radar and the IR imaging sensor to:
generate, using at least one object detection model trained to detect the living subject in images ([0028] states that “the extracting and the analyzing and the computing the physiological parameter comprises obtaining an outcome of a classifier trained on a training dataset”, and [0102] stating that “the term classifier may refer, for example, to a statistical classifier and/or machine learning model that maps inputs to an outcome”), presence information comprising an IR imaging-based presence of the living subject based on a detection of the light reflected by the living subject ([0048] indicates generating respiratory rate/temperature [and thus vitals/presence] and heart rate data [vitals] from the RGB sensor and the radar sensor, respectively); and
output the vitals information and the presence information for communication to the user interface (“Computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 that include a mechanism for entering data and/or viewing data, for example, a touchscreen display used to indicate a new person for analysis, and/or for presenting the computed physiological parameter” [0065]);
communicating from a first communication module of the monitoring device the presence and vitals information for the living subject to a second communication module of an interface device(paragraph 65 indicates that computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 via network interface 222 of paragraph 62. While not explicitly disclosed as a first communication module and a second communication module, communication between the physical user interface 224 and the computing device 204 would inherently and necessarily include hardware and instructions for the stated communication between a first communication module or feature and a second communication module or feature in order to perform the communication); and
presenting on a user interface module of the interface device the presence and vitals information for the living subject(paragraph 65 indicates that the user interface 224 allows viewing of the data).
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Lev fails to teach detecting at an infrared (IR) imaging sensor of a monitoring device, light reflected by a living subject from ambient or controlled light sources.
However, Strasfeld teaches techniques for skin diagnostics based on multispectral images of light reflections from the skin (paragraph 6) using infrared RGB imaging sensors (paragraphs 29-30) wherein the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources (paragraph 50 indicates that the images acquired are reflectance images, meaning that the RGB IR imaging sensors detect reflections from the skin of the patient for the image formation).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev such that the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources, as taught by Strasfeld, providing a low-cost portable method of skin diagnostics using optical signatures (paragraph 30).
Lev in view of Strasfeld fail to teach emitting from a radar of the monitoring device a radiofrequency at a specific frequency, and detecting the frequency change of reflections of a plurality of targets.
However, Boric-Lubecke teaches systems and methods for determining presence and/or physiological motion of at least one subject using a Doppler radar system having a quadrature receiver (see abstract), including emitting from a radar of the monitoring device a radiofrequency at a specific frequency (paragraph 56 discloses a continuous wave Doppler radar transmitting a single tone signal at a specific frequency), and detecting the frequency change of reflections of a plurality of targets which have subtle movements from the living subject (paragraph 56 indicates modulation of the reflected signals from the incident radar due to respiratory and/or heart activity).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld for emitting from a radar of the monitoring device a radiofrequency at a specific frequency, and detecting the frequency change of reflections of a plurality of targets which have subtle movements from the living subject, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Lev in view of Strasfeld and Boric-Lubecke fail to teach region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via a second Sobel operator applied to the frequency change of the reflections.
However, within the same field of endeavor, Sendai teaches that a test subject having a contour that varies with the respiration is optically imaged continuously by the optical image obtaining section to sequentially obtain optical images of the subject, and respiratory phases of the subject are detected simultaneously with the optical imaging by the respiratory phase detecting section based on the contour of the subject on the optical images. (see abstract), [0019] stating that “a respiratory phase detecting means for sequentially receiving optical images of a test subject having a geometric feature that varies at least partially with respiration of the subject obtained by imaging the subject continuously, and sequentially detecting respiratory phases of the test subject based on the geometric feature of the subject on the optical images” and [0022] stating that “If the "geometric feature" is a "shadow region of a test subject" (e.g. a shadow region formed by a collarbone, rib or the like), the shadow region is detected as an edge within the subject image region on an optical image using an edge detecting filter (e.g. Sobel filter, Laplacian filter or the like), and respiratory phases of the subject are detected based on the changes in the position of the detected edge on the image arising from respiration of the subject. In order to know the changes in the position of the edge, it is necessary to identify which edges correspond with each other between two temporally successive optical image frames obtained continuously”. Of note, the optical image data is obtained by optically detecting visible light rays reflected from a subject, according to [0024]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld and Boris-Lubecke, to perform the region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via a second Sobel operator applied to the frequency change of the reflections, as taught by Sendai, as such modification would provide stable accuracy for detecting respiratory phases of the subject according to paragraph 9.
Lev in view of Strasfeld, Boric-Lubecke and Sendai fail to teach generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified.
However, within the same field of endeavor, Garn teaches a method and a device determine a time curve of the depth of breath of a sleeping person (see abstract). [0047] discloses extracting “at least one maximum and at least one minimum from the signal for the purposes of characterizing the depth of respiration in a segment” and [0048] discloses that “A numerically simple filtering of the signal, which largely suppresses interfering noise, provides for the processing unit to subject the signal to a spectral transformation, in particular a Fourier transform, a cosine transform or wavelet transform, and search for the spectral component with the highest signal energy within a predetermined frequency band, in particular from 0.1 Hz to 1 Hz, and use the signal energy of this spectral component to characterize the depth of respiration in this segment”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev as modified by Strasfeld, Boric-Lubecke and Sendai, for generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified, as taught by Garn, for low noise extraction of respiratory movement ([0049]).
Regarding claim 8, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 7.
Lev further teaches wherein the subtle movements are caused by the respiration and/or ballistocardiography from the living subject(paragraph 93).
Regarding claim 9, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 7.
Lev in view of Strasfeld fails to teach wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar.
However, Boric-Lubecke further teaches wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar (paragraph 56 indicates that the Doppler radar is a continuous wave (CW) radar system).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld, wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Regarding claim 10, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 7.
Lev further teaches wherein the IR imaging sensor is one of an red-green-blue (RGB) IR imaging sensor or short-wave (SW) IR imaging sensor (paragraph 76 discloses RGB/IR image sensors).
Regarding claim 12, Lev teaches a system for presence and vitals detection of a living subject(system 200 of paragraph 58), the system comprising:
a monitoring device comprising an imaging sensor(paragraph 61 discloses RGB sensor, short-wave infrared (SWIR) sensors; paragraph 76 also discloses an RGB/IR image sensor),
a radar(paragraph 82 discloses a doppler and/or radar sensor), a processor (paragraph 58), and a first communication module (paragraph 65 indicates that computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 via network interface 222 of paragraph 62. While not explicitly disclosed as a first communication module and a second communication module, communication between the physical user interface 224 and the computing device 204 would inherently and necessarily include hardware and instructions for the stated communication between a first communication module or feature and a second communication module or feature in order to perform the communication ); and
an interface device (user interface 224 of paragraph 65) comprising a second communication module and a user interface module(paragraph 65 indicates that computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 via network interface 222 of paragraph 62. While not explicitly disclosed as a first communication module and a second communication module, communication between the physical user interface 224 and the computing device 204 would inherently and necessarily include hardware and instructions for the stated communication between a first communication module or feature and a second communication module or feature in order to perform the communication );
wherein the radar (paragraph 82) detects subtle movements from the living subject (paragraph 93 indicates that Graph 502 indicates that the non-contact sensor accurate generates an indication of movement of a chest (e.g., chest displacement) which may be used for computing sub-physiological parameter(s) such as respiratory rate and/or heart rate);
wherein the processor (204 of fig. 2 and paragraph 58) is configured to run an algorithm to perform digital signal processing on data provided by the radar and the RGB imaging sensor (paragraph 48 indicates computing physiological parameters such as respiratory rate and/or heart rate from the thermal sensors, that is RGB sensor and Doppler and/or radar sensor) to:
generate, using at least one object detection model trained to detect the living subject in images ([0028] states that “the extracting and the analyzing and the computing the physiological parameter comprises obtaining an outcome of a classifier trained on a training dataset”, and [0102] stating that “the term classifier may refer, for example, to a statistical classifier and/or machine learning model that maps inputs to an outcome”), presence information comprising an IR imaging-based presence of the living subject based on a detection of the light reflected by the living subject ([0048] indicates generating respiratory rate/temperature [and thus vitals/presence] and heart rate data [vitals] from the RGB sensor and the radar sensor, respectively);
generate, in response to the presence information, vitals information for the living subject based at least in part on: at least one image peak search algorithm for at least one first point of interest identified and at least one radar peak search algorithm for at least one second point of interest identified; ([0096]-[0097] disclose that one or more of the sub-physiological parameters are computed based on time interval from maximal to minimal or peak to peak time intervals, the sub-physiological parameters being obtained from thermal images (figs. 3-4 and [0091]-[0092] and radar signal (fig. 5 and [0093]) and
output the vitals information and the presence information for communication to the user interface (“Computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 that include a mechanism for entering data and/or viewing data, for example, a touchscreen display used to indicate a new person for analysis, and/or for presenting the computed physiological parameter” [0065]).
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Lev fails to teach wherein the RGB imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources.
However, Strasfeld teaches techniques for skin diagnostics based on multispectral images of light reflections from the skin (paragraph 6) using infrared RGB imaging sensors (paragraphs 29-30) wherein the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources (paragraph 50 indicates that the images acquired are reflectance images, meaning that the RGB IR imaging sensors detect reflections from the skin of the patient for the image formation).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev such that the IR imaging sensor is utilized to detect light reflected by a living subject from ambient or controlled light sources, as taught by Strasfeld, providing a low-cost portable method of skin diagnostics using optical signatures (paragraph 30).
Lev in view of Strasfeld fails to teach wherein the radar emits a radiofrequency at a specific frequency, and detects the frequency change of reflections of a plurality of targets.
However, Boric-Lubecke teaches systems and methods for determining presence and/or physiological motion of at least one subject using a Doppler radar system having a quadrature receiver (see abstract), wherein the radar emits a radiofrequency at a specific frequency (paragraph 56 discloses a continuous wave Doppler radar transmitting a single tone signal at a specific frequency), and detects the frequency change of reflections of a plurality of targets which have subtle movements from the living subject (paragraph 56 indicates modulation of the reflected signals from the incident radar due to respiratory and/or heart activity).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld, such that radar emits a radiofrequency at a specific frequency, and detects the frequency change of reflections of a plurality of targets, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Lev in view of Strasfeld and Boric-Lubecke fail to teach region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via a second Sobel operator applied to the frequency change of the reflections.
However, within the same field of endeavor, Sendai teaches that a test subject having a contour that varies with the respiration is optically imaged continuously by the optical image obtaining section to sequentially obtain optical images of the subject, and respiratory phases of the subject are detected simultaneously with the optical imaging by the respiratory phase detecting section based on the contour of the subject on the optical images. (see abstract), [0019] stating that “a respiratory phase detecting means for sequentially receiving optical images of a test subject having a geometric feature that varies at least partially with respiration of the subject obtained by imaging the subject continuously, and sequentially detecting respiratory phases of the test subject based on the geometric feature of the subject on the optical images” and [0022] stating that “If the "geometric feature" is a "shadow region of a test subject" (e.g. a shadow region formed by a collarbone, rib or the like), the shadow region is detected as an edge within the subject image region on an optical image using an edge detecting filter (e.g. Sobel filter, Laplacian filter or the like), and respiratory phases of the subject are detected based on the changes in the position of the detected edge on the image arising from respiration of the subject. In order to know the changes in the position of the edge, it is necessary to identify which edges correspond with each other between two temporally successive optical image frames obtained continuously”. Of note, the optical image data is obtained by optically detecting visible light rays reflected from a subject, according to [0024]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld and Boris-Lubecke, to perform the region of interest determinations via a first Sobel operator applied to the light reflected by the living subject and via a second Sobel operator applied to the frequency change of the reflections, as taught by Sendai, as such modification would provide stable accuracy for detecting respiratory phases of the subject according to paragraph 9.
Lev in view of Strasfeld, Boric-Lubecke and Sendai fail to teach generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified.
However, within the same field of endeavor, Garn teaches a method and a device determine a time curve of the depth of breath of a sleeping person (see abstract). [0047] discloses extracting “at least one maximum and at least one minimum from the signal for the purposes of characterizing the depth of respiration in a segment” and [0048] discloses that “A numerically simple filtering of the signal, which largely suppresses interfering noise, provides for the processing unit to subject the signal to a spectral transformation, in particular a Fourier transform, a cosine transform or wavelet transform, and search for the spectral component with the highest signal energy within a predetermined frequency band, in particular from 0.1 Hz to 1 Hz, and use the signal energy of this spectral component to characterize the depth of respiration in this segment”.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev as modified by Strasfeld, Boric-Lubecke and Sendai, for generating vitals information based at least in part on: at least one image peak search algorithm for at least one first point of interest, associated with the location of the living subject and at least one radar peak search algorithm, on a portion of a radar sensitivity pattern associated with the location of the living subject based on the presence information for at least one second point of interest identified, as taught by Garn, for low noise extraction of respiratory movement ([0049]).
Regarding claim 13, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev further teaches a memory (data storage device 220 of paragraph 64) configured to store sensor output from the RGB imaging sensor, the radar, or both (paragraph 64 indicates that the data storage stores datasets acquired by the sensors 212, which includes the long IR range thermal sensor of paragraph 61).
Regarding claim 14, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev further teaches wherein the subtle movements are caused by the respiration and/or ballistocardiography from the living subject (paragraph 93).
Regarding claim 15, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev further teaches wherein the user interface presents data using a light emitting diode (LED), a display or a speaker (paragraph 65 discloses a display).
Regarding claim 16, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev further teaches wherein the user interface comprises the second communication module for receiving data from a first communication module in communication with the processor (paragraph 65 indicates that computing device 204 and/or client terminal(s) 208 include and/or are in communication with one or more physical user interfaces 224 via network interface 222 of paragraph 62. While not explicitly disclosed as a first communication module and a second communication module, communication between the physical user interface 224 and the computing device 204 would inherently and necessarily include hardware and instructions for the stated communication between a first communication module or feature and a second communication module or feature in order to perform the communication).
Regarding claim 18, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev further teaches wherein the infrared (IR) imaging sensor is one of an RGB IR imaging sensor or an RGB short-wave (SW) IR imaging sensor ([0076] discloses RGB/IR image sensors).
Regarding claim 19, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 12.
Lev in view of Strasfeld fails to teach wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar.
However, Boric-Lubecke further teaches wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar (paragraph 56 indicates that the Doppler radar is a continuous wave (CW) radar system).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev, as modified by Strasfeld, wherein the Doppler radar is a pulsed Doppler radar or a continuous wave Doppler radar, as taught by Boric-Lubecke, which would allow accurate respiratory and/or cardiographic measurements (paragraph 8) with having less noise (paragraphs 7-9).
Claims 11 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Lev, et al., US 20220007950 A1 in view of Strasfeld, et al., US 20210228083 A1 and Boric-Lubecke, et al., US 20080119716 A1, Sendai, and Garn as applied to claim 13 above, and further in view of Schultes, et al., US 20220167850 A1.
Regarding claims 11 and 17, Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn teaches all the limitations of claim 7 and 12, respectively, above.
Lev in view of Strasfeld, Boric-Lubecke, Sendai, and Garn fail to teach wherein the first communication module and the second communication module operate on a WiFi communication protocol, a BLUETOOTH communication protocol, a frequency modulation (FM) communication protocol, or a frequency hopping spread spectrum (FHSS) communication protocol.
However, Schultes teaches a 3D body scanner of a body (abstract) using radar and infrared cameras and providing first (paragraph 31) and second interfaces (paragraph 34) for communicating acquired data (paragraph 54) wherein the first communication module and the second communication module operate on a WiFi communication protocol, a BLUETOOTH communication protocol, a frequency modulation (FM) communication protocol, or a frequency hopping spread spectrum (FHSS) communication protocol (paragraph 31 and 34).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Lev as modified by Strasfeld, Boric-Lubecke, Sendai, and Garn wherein the first communication module and the second communication module operate on a WiFi communication protocol, a BLUETOOTH communication protocol, a frequency modulation (FM) communication protocol, or a frequency hopping spread spectrum (FHSS) communication protocol, as taught by Schultes, as such modification would improve the communication of data across the devices (paragraph 8).
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.
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/FAROUK A BRUCE/ Examiner, Art Unit 3797
/CHRISTOPHER KOHARSKI/ Supervisory Patent Examiner, Art Unit 3797