DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 01/02/2025 and 05/20/2026 were filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description:
FIGS. 1 and 2: Although these figures include the label 115, this label does not appear in the specification.
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
[0037]: As written it reads “The code segments may be downloaded via computer networks such as the Internet, an intranet, a LAN, or the like”. However, this is the first instance of the term “LAN”, therefore, the term should be spelled out to provide clarity.
[0038]: As written it reads “For example, functionality referred to herein as a module may be implemented wholly, or partially, as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components”. However, this is the first instance of the term “VLSI” therefore, the term should be spelled out to provide clarity.
Appropriate correction is required.
Claim Objections
Claims 2, 11, 12, 18, and 20 are objected to because of the following informalities:
Regarding claims 2 and 11, as written they read “conducting a power spectral density (PSD) analysis of each time window, in the processing system, to a determine power distribution in each of a plurality of different frequency bands and generate PSD data indicative thereof” (Claims 2 and 11). However, to be grammatically correct, “a determine” should be “determine a”.
Regarding claim 12, as written it reads “further comprising: a display device in operable communication with the processing system, the display device including an display and configured, in response to image rendering display commands, to render one or more images on the display, wherein the processing system is further configured to command the display device to render an image on the display that indicates the blood-alcohol content of the person”. However, to be grammatically correct “an display” should be “a display”.
Regarding claim 18, as written it reads "wherein the mmWave sensor is disposed within a seat of a vehicle”. However, to avoid potential antecedent basis issues, the examiner would recommend amending the claim to recite “the mmWave radar sensor”, as stated in claim 10.
Regarding claim 20, as written it reads “A method for detecting a blood alcohol content of a person, the method comprising the steps of: detecting, using a millimeter-wave (mmWave) radar sensor, at least a heart rate of a person and supplying heart rate data indicative thereof”. However, to avoid potential antecedent basis issues “a person” (underlined above) should be “the person”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim 9 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Regarding claims 9, the claim recites “wherein the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated”. However, claim 9 is a method claim, dependent on claim 1, and this claim appears to be describing system components rather than method steps.
Thus, this creates confusion as to when direct infringement occurs. A single claim which claims both an apparatus and the method steps of using the apparatus is indefinite under 35 U.S.C. 112, second paragraph. See In re Katz Interactive Call Processing Patent Litigation, 639 F.3d 1303 (Fed. Cir. 2011). It is unclear "whether infringement … occurs when one creates a system that allows the user [to use the input means], or whether infringement occurs when the user actually uses the input means." See IPXL Holdings v. Amazon.com, Inc., 430 F.2d 1377, 1384, 77 USPQ2d 1140, 1145 (Fed. Cir. 2005). See MPEP 2173.05(p).
The examiner recommends using language such as “further comprising: predicting, in the processing system, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated in order to clarify that this claim is indeed related to a step of the method described in claim 1.
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.
Claim(s) 1-8, 10-17, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mohanty et al. US 2023/0294514 A1 “Mohanty” and further in view of Schwarz, Chris et al., Heartbeat Measurement with Millimeter Wave Radar in the Driving Environment, 2021, IEEE Radar Conference “Schwarz”.
Regarding claims 1 and 10, Mohanty teaches “A method for detecting a blood-alcohol content of a person, the method comprising the steps of:” (Claim 1) (“Referring to FIGS. 6-9, a method of monitoring 500 overall working flow as a complete framework is specifically depicted in FIG. 6. The method of monitoring 500 can begin at “start” at the step 504. Next, collect all the images/videos at a step 508, collect all the physiological data at a step 512, and collect all the vital data at a step 516. After collecting, the data can be outputted to a tiny DNN model at a step 520. Next, analyze the BAC levels at a step 524. That being done, a query of whether abnormal levels detected is conducted at a step 528. If no, then the step 524 repeated. If yes, then collect all the psychological data is conducted at a step 532.” [0052]. Therefore, FIGS. 6-9 include steps which represent a method for detecting a blood-alcohol content (BAC) of a person.);
“A system for detecting a blood-alcohol content of a person, comprising:” (Claim 10) (“In some embodiments, the system is a component in a vehicle as depicted in FIG. 1. Referring to FIGS. 1-3, a system 100 for determining BAC of a driver, such as an individual 10, includes a vehicle 110 having a steering wheel 112 and an ignition 114, one or more sensors 120, an analysis unit 180, and a communication system 200. A response management unit 216 may be responsive to the system 100, as described hereinafter. The one or more sensors 120 can be configured to measure a physiological parameter of an individual, and can include an image capture sensor 124, a vital data sensor 128, a medical sensor 132, a psychological monitoring sensor 136, or any combination thereof” [0024]. Therefore, FIG. 1 depicts a system for detecting a blood-alcohol content of a person.);
“detecting, […], at least a heart rate of the person and supplying heart rate data indicative thereof” (Claim 1); “a […] sensor configured to detect at least a heart rate of the person and supply heart rate data indicative thereof” (Claim 10) (“The vital data sensor 128 can be configured to output at least one of a respiration rate, an electroencephalogram output, a temperature reading, a blood pressure reading, a heart rate, a skin conductance reading, a blood oxygen level, a blood sugar level, or a combination thereof” [0024]. As shown in FIG. 6, step 516 involves collecting all the vital data (see [0052]). Furthermore, in step 520, the data (i.e. including the vital data collected by the vital data sensor 128) is outputted to a tiny DNN model (see [0052]). Therefore, the method involves detecting at least a heart rate of a person and supplying heart rate data indicative thereof (i.e. to the tiny DNN model). Additionally, the system includes a sensor (i.e. vital data sensor 128) configured to detect at least a heart rate of the person and supply heart rate data indicative thereof.).;
“supplying the heart rate data to a processing system” (Claim 1); (See [0052] and [0024] above and “In some embodiments, as depicted in FIG. 5, an analysis unit 180, which may include a mental health analyses unit, can include the tiny DNN models with multimodal data 270, which may also or alternatively include the tiny DNN, as described above, a vision data unit 400, a physiological data unit 410, a vital data unit 420, a facial feature data unit 430, a psychological and behavior analysis data unit 440, a MLM 450, a BAC analysis unit 460, the storage unit 290, the help unit 300, and a stability analysis unit 480” [0047]. Thus, since the data collected in steps 508, 512 and 516 is outputted to a tiny DNN model, contained within the analysis unit 180 (i.e. processing system), the method involves supplying the heart rate data to a processing system;
“processing the heart rate data, using a trained model implemented in the processing system, to determine the blood-alcohol content of the person” (Claim 1) (See [0052] above. Therefore, since the data collected in steps 508, 512, and 516, step 516 involving obtaining vital sign data including heart rate data from a vital data sensor 128 (see [0024]), are output to a tiny DNN model such that BAC levels can be analyzed, the method involves processing the heart rate data, using a trained model implemented in the processing system (i.e. analysis unit 180), to determine the blood-alcohol content of the person.);
“a processing system in operable communication with the […] sensor, the processing system coupled to receive the heart rate data and configured, upon receipt thereof, to process the heart rate data, using a trained model implemented in the processing system, to determine the blood-alcohol content of the person” (Claim 10) (See [0052], [0024] and [0047] as discussed above. Therefore, the system includes a processing system (i.e. analysis unit 180) in operable communication with the sensor (i.e. vital data sensor 180), the processing system coupled to receive the heart rate data (i.e. see [0024]) and configured, upon receipt thereof, to process the heart rate data, using a trained model (i.e. tiny DNN model, see FIG. 6, step 520) implemented in the processing system, to determine the blood-alcohol content (i.e. BAC levels, see step 524 in FIG. 6) of the person.).
Mohanty does not teach that the detecting step is performed “using a millimeter-wave (mmWave) radar sensor” (Claim 1) or that the system includes “a millimeter-wave (mmWave) radar sensor” (Claim 10).
Schwarz is within the same field of endeavor as the claimed invention because it involves a millimeter wave radar sensor for use in heartbeat measurement (see [Title] and [Abstract]).
Schwarz teaches that the detecting step is performed “using a millimeter-wave (mmWave) radar sensor” (Claim 1) and that the system includes “a millimeter-wave (mmWave) radar sensor” (“Millimeter wave radar has proven to be an effective method to measure human vital signs in a non-contact manner” [Abstract]; “We compared three heartbeat estimation algorithms: peak spectrum estimation, MISIC, and bootstrapped particle filer” [Page 2, II. Method, Para. 2, Line 1-2]; “The AWR1642BOOST radar was configured from the mmWave Studio application to sweep a 4 GHz bandwidth from 77 to 81 GHz” [Page 2, A. Radar Configuration]; “The peak spectrum is conceptually simple. The PSD returned by Welch’s method covers the heartbeat bandwidth over a fixed time window. The estimate for that window is the frequency corresponding to the maximum PSD magnitude” [Page 3, 1) Peak Spectrum].
Therefore, Schwarz utilizes a millimeter-wave (mmWave) radar sensor to measure human vital signs, specifically a heartbeat.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz in order to effectively measure human vital signs (see Schwarz: [Abstract]). A millimeter-wave (mmWave) radar sensor is one of a finite number of sensor types which can be used to measure human vital signs, such as heartbeat measurements (i.e. heart rate) with a reasonable expectation of success. Thus, modifying the method and system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz would yield the predictable result of effectively measuring human vital signs (see Schwarz: [Abstract]).
Regarding claims 2 and 11, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty discloses “supplying the […] data to the trained model” (Claims 2 and 11) (See [0052] as discussed in claim 1 and step 520 in FIG. 6. In this case, since images/videos, physiological data and vital data (i.e. see steps 508, 512, 516) are outputted to a tiny DNN model (i.e. see step 520) such that BAC levels are analyzed (i.e. see step 524) the method involves supplying the data to the trained model (i.e. tiny DNN).);
Schwarz further teaches the “PSD data” and “wherein the step of processing the heart rate data comprises: continuously segmenting the heart rate data, in the processing system, into a predetermined number of time windows” (Claim 2); “wherein the processing system is configured to process the heart rate data by: continuously segmenting the heart rate data into a predetermined number of time windows” (Claim 11) (“The three estimation algorithms presented here are peak spectrum (PS), MUSIC, and particle filter (PF)” [Page 3, C. Heartbeat Estimation, Para. 1, Lines 1-2]; “Welch’s method is a smoothed estimate of power spectral density (PSD) that splits a window into smaller segments, possibly overlapping, and averages the periodograms of each segment. We used a fixed segment length of 8 seconds and constructed longer window lengths using 50% overlap. By combining 1, 3, 5, 7, 9, 11 and 13 segments, we were able to analyze window lengths of 8, 16, 24, 32, 40, 48 and 56 seconds respectively. A Hanning window was applied to each segment before computing the periodogram” [Page 3, Heartbeat Estimation: Para. 3, Lines 1-9]. Therefore, the method carried out by the system involves continuously segmenting the heart rate data, in the processing system, into a predetermined number of time windows (i.e. 13 segments).);
“conducting a power spectral density (PSD) analysis of each time window, in the processing system, to a determine power distribution in each of a plurality of different frequency bands and generate PSD data indicative thereof” (Claims 2 and 11) (See [Page 3, Heartbeat Estimation: Para. 3, Lines 1-9]. Therefore, the method involves conducting a power spectral density (PSD) analysis (i.e. Welch’s method) of each time window, in the processing system, to determine a power distribution in each of a plurality of different frequency bands and generate PSD data indicative thereof.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Mohanty such that it involves supplying PSD data to the trained model, the PSD data being obtained by processing the heart rate data comprises: continuously segmenting the heart rate data, in the processing system, into a predetermined number of time windows and conducting a power spectral density (PSD) analysis of each time window, in the processing system, to a determine power distribution in each of a plurality of different frequency bands and generate PSD data indicative thereof as disclosed in Schwarz in order to effectively measure human vital signs (see Schwarz: [Abstract]). Segmenting heart-rate data into a predetermined number of time windows and conducting a power spectral density (PSD) analysis of each time window is one of a finite number of techniques which can be used to assess features of heart-rate data with a reasonable expectation of success. Thus, modifying the method the method of Mohanty such that it involves supplying PSD data to the trained model, the PSD data being obtained by processing the heart rate data comprises: continuously segmenting the heart rate data, in the processing system, into a predetermined number of time windows and conducting a power spectral density (PSD) analysis of each time window, in the processing system, to a determine power distribution in each of a plurality of different frequency bands and generate PSD data indicative thereof as disclosed in Schwarz, would yield the predictable result of effectively measuring human vital signs (see Schwarz: [Abstract]).
Regarding claims 3 and 12, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty further teaches “further comprising: commanding a display device, using the processing system, to render an image on a display that indicates the blood-alcohol content of the person” (Claim 3); “further comprising: a display device in operable communication with the processing system, the display device including an display and configured, in response to image rendering display commands, to render one or more images on the display, wherein the processing system is further configured to command the display device to render an image on the display that indicates the blood-alcohol content of the person” (Claim 12) (“The psychological monitoring sensor 136 can be incorporated into an infotainment counsel 138 of the vehicle 110 and configured to output at least one of a movement output, an accelerometer output, a gyroscopic output, a pressure output, a body position output, a light detection and ranging (LIDAR) output, a location reading, a blood alcohol reading, or a movement of a chest or abdomen of the individual 10.” [0024]. Therefore, the method further comprises commanding a display device (i.e. infotainment counsel 138), using the processing system to render an image on a display that includes the blood-alcohol content of the person (i.e. blood alcohol reading). Furthermore, the system includes a display device in operable communication with the processing system (i.e. analysis unit 180), the display device including a display and configured, in response to image rendering display commands, to render one or more images on the display, wherein the processing system is further configured to command the display device to render an image on the display that indicates the blood-alcohol content of the person.).
Regarding claims 4 and 13, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty further teaches “further comprising: determining, in the processing system, when the blood-alcohol content of the person meets or exceeds a predetermined value; and when the blood-alcohol content of the person meets or exceeds the predetermined value, supplying an inhibit signal, from the processing system to a subsystem within a vehicle, that will at least inhibit operability of the vehicle” (Claim 4); “wherein the processing system is further configured to: determine when the blood-alcohol content of the person meets or exceeds a predetermined value; and when the blood-alcohol content of the person meets or exceeds the predetermined value, supply an inhibit signal to a subsystem within a vehicle that will at least inhibit operability of the vehicle” (Claim 13) (“The physical state can include a BAC of the individual. In some embodiments, the analysis unit 180 can be configured to lock an ignition of a vehicle when the blood alcohol content of the individual 10 is above a threshold” [0027]; “Next, analyze the BAC levels at a step 524. That being done, a query of whether abnormal levels detected is conducted at a step 528. If no, then the step 524 repeated. If yes, then collect all the psychological data is conducted at a step 532. Next, analyze the driver's behavior is conducted at a step 536. Another query is made whether the driver is unstable at a step 540. If no, step 536 is repeated, and if yes, the response management unit 216 is notified at a step 216” [0052]; “The step 524 analyze the BAC levels can receive the output from the step 620 and physiological and vital signal monitoring unit 282 to, in turn, output to a query of abnormal levels detected at a step 528. If no, return to step 524, otherwise if yes, proceed to psychological analysis unit at a step 440. Another query can be made of the driver unstable at a step 540. If no, return to the step 440, otherwise if yes, the response management unit 216 can be notified at a step 216.” [0054]; “A tenth aspect can include the system of any of the preceding aspects, wherein the analysis unit is further configured to lock an ignition of a vehicle when the blood alcohol content of the individual is above a threshold” [0069].
Therefore, since the analysis unit 180 is configured to lock an ignition of a vehicle when the blood alcohol content of the individual is above a threshold, the method carried out by the analysis unit 180 involves determining, in the processing system, when the blood-alcohol content of the person meets or exceeds a predetermined value (i.e. threshold); and when the blood-alcohol content of the person meets or exceeds the predetermined value, supplying an inhibit signal, from the processing system to a subsystem within a vehicle, that will at least inhibit operability of the vehicle (i.e. lock the ignition). Additionally, the processing system is further configured to: determine when the blood-alcohol content of the person meets or exceeds a predetermined value (i.e. threshold); and when the blood-alcohol content of the person meets or exceeds the predetermined value, supply an inhibit signal to a subsystem within a vehicle that will at least inhibit operability of the vehicle.).
Regarding claims 5 and 14, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty further teaches “further comprising: transmitting the determined blood-alcohol content of the person to one or more predetermined receivers for review by another person” (Claim 5); “further comprising: a transmitter in operable communication with the processing system, wherein the processing system is further configured to command the transmitter to transmit the determined blood-alcohol content of the person to one or more predetermined receivers for review by another person” (Claim 14) (See [0054] as discussed in claims 4 and 13 above, “The response management unit 216 in the system 100 has pre-stored contact numbers of the family or friends, has an ability to contact the nearest emergency service, has an ability to book a cab or call for a taxi automatically. This response system also has the access to the video recordings of the driver and can transfer it to the nearby emergency when in need in case of driver unconsciousness” [0027]; and “Afterwards, another query can be made, namely, driver unstable at a step 540. If no, then step 410 is repeated, if yes, then the response management unit 216 can be contacted at a step 216” [0055].
Therefore, since the response management unit 216 can be contacted when the driver is unstable (see step 540 in FIG. 6, for example), the response management unit 216 having pre-stored contact numbers of family and friends, the ability to contact the nearest emergency service, the ability to book a cab or call for a taxi and to access video recordings of the driver and transfer them to a nearby emergency service, the method further comprises: transmitting the determined blood-alcohol content of the person to one or more predetermined receivers for review by another person (i.e. family, friend, emergency personnel). Additionally, the system further comprises a transmitter in operable communication with the processing system, wherein the processing system is further configured to command the transmitter to transmit the determined blood-alcohol content of the person to one or more predetermined receivers for review by another person (i.e. family, friend, emergency personnel).).
Regarding claims 6 and 15, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty further teaches “wherein: the processing system is located remote from the […] sensor; and the step of supplying the heart rate data comprises wirelessly transmitting the heart rate data to the processing system” (Claim 6); “wherein: the processing system is located remote from the […] sensor; and the […] sensor is configured to wirelessly transmit the heart rate data to the processing system” (Claim 15) (See [0024] as discussed in claims 1 and 10 above and “The analysis unit 180 can include a vital signal data monitoring unit, a response management unit 216, and a blood alcohol concentration detection unit” [0027]; “The communication system 200 can be in signal communication with the analysis unit 180. The communication system 200 may be configured to send an indication of the mental state or the physical state of the individual 10 to a remote device” The communication system 200 can be configured for two-way responses, and can include equipment and systems such as up and down links, fog computing using edge devices and peripherals in a plane traffic, edge data center or router, at least one of a router, a gateway, or a combination thereof, one or more local area networks, one or more cloud services, and the Internet [0028].
As shown in FIGS. 1 and 2, the response management unit 216 (i.e. located within the analysis unit 180/processing system) is located in a remote location from the vital data sensor 128, the vital data sensor being configured to output a heart rate (See [0024]). These components interact through the use of the communication system 200 shown in FIG. 2. Therefore, the processing system (i.e. analysis unit 180) is located remote from the […] sensor (i.e. vital data sensor 128); and the step of supplying the heart rate data comprises wirelessly transmitting the heart rate data to the processing system (i.e. using communication system 200, see FIG. 2). Additionally, the sensor (i.e. vital data sensor 128) is configured to wirelessly transmit the heart rate data to the processing system (i.e. analysis unit 180).).
Schwarz further teaches that the sensor is “the mmWave radar sensor” (See [Abstract]; [Page 2, II. Method, Para. 2, Line 1-2]; [Page 2, A. Radar Configuration]; and [Page 3, 1) Peak Spectrum] as discussed in claims 1 and 10 above. Therefore, Schwarz utilizes a millimeter-wave (mmWave) radar sensor to measure human vital signs, specifically a heartbeat.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz in order to effectively measure human vital signs (see Schwarz: [Abstract]). A millimeter-wave (mmWave) radar sensor is one of a finite number of sensor types which can be used to measure human vital signs, such as heartbeat measurements (i.e. heart rate) with a reasonable expectation of success. Thus, modifying the method and system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz would yield the predictable result of effectively measuring human vital signs (see Schwarz: [Abstract]).
Regarding claims 7 and 16, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, and Mohanty further teaches “further comprising: sensing, using one or more physiological sensors, one or more sets of physiological data associated with the person; supplying the one or more sets of physiological data to the processing system; and processing the one or more sets of physiological data and the heart rate data, using the trained model implemented in the processing system, to determine the blood-alcohol content of the person” (Claim 7); “further comprising: one or more physiological sensors in operable communication with, and configured to supply one or more sets of physiological data associated with the person to, the processing system; wherein the processing system is further configured to receive and process the one or more sets of physiological data and the heart rate data, using the trained model, to determine the blood-alcohol content of the person” (See [0052] as discussed in claims 1 and 10 above, and “The one or more sensors 120 can be configured to measure a physiological parameter of an individual, and can include an image capture sensor 124, a vital data sensor 128, a medical sensor 132, a psychological monitoring sensor 136, or any combination thereof. The image capture sensor 124 can be configured to output at least one of an image or a video. The medical sensor 132 can be a physiological sensor. The vital data sensor 128 can be configured to output at least one of a respiration rate, an electroencephalogram output, a temperature reading, a blood pressure reading, a heart rate, a skin conductance reading, a blood oxygen level, a blood sugar level, or a combination thereof. The psychological monitoring sensor 136 can be incorporated into an infotainment counsel 138 of the vehicle 110 and configured to output at least one of a movement output, an accelerometer output, a gyroscopic output, a pressure output, a body position output, a light detection and ranging (LIDAR) output, a location reading, a blood alcohol reading, or a movement of a chest or abdomen of the individual 10. The one or more sensors 120 can include an input unit for receiving stimulus. The one or more sensors 120 can provide an output to the analysis unit 180 configured to receive one or more outputs of the one or more sensors 120.” [0024]; “As the driver starts the car, the cameras attached can capture all the image and video data along with physiological and vital signal data. The complete data will be sent to the tiny DNN model where the BAC levels can be detected. Based on how the driver responds, the psychological data is taken and is analyzed to monitor the driver's ability to drive the vehicle. The process of taking the images and converting them to analyze the BAC is listed in Algorithm 2 below” [0053].
Therefore, the method further comprises: sensing, using one or more physiological sensors, one or more sets of physiological data associated with the person (i.e. one or more sensors 120 configured to measure physiological parameters, the one or more sensors including an image capture sensor 124, a vital data sensor 128, a medical sensor 132, a psychological monitoring sensor 136,); supplying the one or more sets of physiological data to the processing system (i.e. analysis unit 180); and processing the one or more sets of physiological data and the heart rate data, using the trained model implemented in the processing system (i.e. tiny DNN, see 520 in FIG. 6), to determine the blood-alcohol content of the person. Additionally, the system further comprises: one or more physiological sensors (i.e. sensors 120, including an image capture sensor 124, a vital data sensor 128, a medical sensor 132, a psychological monitoring sensor 136) in operable communication with, and configured to supply one or more sets of physiological data associated with the person to, the processing system (i.e. analysis unit 180); wherein the processing system is further configured to receive and process the one or more sets of physiological data and the heart rate data, using the trained model (i.e. tiny DNN, see 520 in FIG. 6), to determine the blood-alcohol content of the person.).
Regarding claims 8 and 17, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 7 and 16 above, and Mohanty further teaches “further comprising: processing, in the processing system, video data supplied from a video source to extract a plurality of physical features from the video data, the video data being representative of detected video images of the person; and processing the extracted physical features, the one or more sets of physiological data, and the heart rate data, using the trained model implemented in the processing system, to determine the blood-alcohol content of the person” (Claim 8); “further comprising: a video source in operable communication with, and configured to supply video data representative of detected video images of the person to, the processing system, wherein in the processing system is further configured to: extract a plurality of physical features from the video data, and process the extracted physical features, the one or more sets of physiological data, and the heart rate data, using the trained model, to determine the blood-alcohol content of the person” (Claim 17) (See [0024] and [0053] as discussed in claims 7 and 16 above; “The automatic flow of the psychological data to analyze the stability of the driver is represented in FIG. 9. All the multimodal data—physiological, vital, image and video—are considered to analyze the BAC levels of the person” [0056].
Therefore, since the one or more sensors includes an image capture sensor 124 which is configured to output at least one of an image or a video and video data along with physiological and vital signal data are sent to the tiny DNN model in order to detect BAC levels, the method involves processing, in the processing system, video data supplied from a video source (i.e. image capture sensor 124) to extract a plurality of physical features from the video data, the video data being representative of detected video images of the person; and processing the extracted physical features, the one or more sets of physiological data, and the heart rate data, using the trained model (i.e. tiny DNN model, see step 520) implemented in the processing system, to determine the blood-alcohol content of the person. Additionally, the system involves a video source (i.e. image capture sensor 124) in operable communication with, and configured to supply video data representative of detected video images of the person to, the processing system (i.e. analysis unit 180), wherein in the processing system is further configured to: extract a plurality of physical features from the video data (i.e. through analysis of all multimodal data—physiological, vital, image and video—to analyze the BAC levels), and process the extracted physical features, the one or more sets of physiological data, and the heart rate data, using the trained model, to determine the blood-alcohol content of the person (see step 524 in FIG. 6).).
Regarding claim 20, Mohanty teaches “A method for detecting a blood alcohol content of a person, the method comprising the steps of:” (See [0052] as disclosed with respect to claim 1 above. Therefore, FIGS. 6-9 include steps which represent a method for detecting a blood-alcohol content (BAC) of a person.);
“detecting, using a […] sensor, at least a heart rate of a person and supplying heart rate data indicative thereof” (See [0024] as discussed in claim 1 above. As shown in FIG. 6, step 516 involves collecting all the vital data (see [0052]). Furthermore, in step 520, the data (i.e. including the vital data collected by the vital data sensor 128) is outputted to a tiny DNN model (see [0052]). Therefore, the method involves detecting, using a sensor, at least a heart rate of a person and supplying heart rate data indicative thereof.);
“supplying the heart rate data to a processing system; processing the heart rate data, using a first trained model implemented in the processing system, to determine the blood-alcohol content of the person” (See [0052] and [0024] as discussed in claim 1 above. Therefore, the method involves supplying the heart rate data (i.e. from the vital data sensor 128) to a processing system (i.e. analysis unit 180); and processing the heart rate data, using a first trained model (i.e. tiny DNN model, see FIG. 6, step 520) implemented in the processing system, to determine the blood-alcohol content of the person.); and
“processing the heart rate data, using a second trained model implemented in the processing system, to determine if the person is incapacitated” (“The analysis unit 180 can include a microcontroller and a machine learning model (MLM), including one or more MLMs, such as a neural network (e.g., a tiny deep neural network model), configured to accept the one or more outputs of the one or more sensors 120, and predict a physical state of the individual 10” [0025]; “Next, analyze the driver's behavior is conducted at a step 536. Another query is made whether the driver is unstable at a step 540. If no, step 536 is repeated, and if yes, the response management unit 216 is notified at a step 216. Moreover, the step 900 of monitoring at least one of a physiological parameter, a facial feature, or a psychological parameter of a driver using one or more sensors disposed within a vehicle can include steps 508, 512, 516, and 532. Furthermore, the steps receiving, by an analysis unit 180, at least one output of the one or more sensors 910 and inputting the at least one output into a MLM 930 can be done at the step 520 for using the tiny DNN model. What is more, the steps of determining, by the analysis unit, a mental state or a physical state of the driver based on the at least one output 920 can include steps 524 and 536” [0052].
Therefore, since the analysis unit can include a machine learning model (MLM), including one or more MLMs to predict a physical state of an individual (see [0025]) and the driver’s behavior is analyzed by monitoring at least one of a physiological parameter, a facial feature, or a psychological parameter using one or more sensor and inputting the output of the one or more sensors 910 into a MLM 930, the method involves processing the heart rate data, using a second trained model implemented in the processing system, to determine if the person is incapacitated (i.e. if the driver is unstable).).
However, Mohanty does not teach “using a millimeter-wave (mmWave) radar sensor”.
Schwarz teaches “using a millimeter-wave (mmWave) radar sensor” (See Schwarz: [Abstract]; [Page 2, II. Method, Para. 2, Line 1-2]; [Page 2, A. Radar Configuration]; [Page 3, 1) Peak Spectrum] as discussed in claim 1 above. Therefore, Schwarz utilizes a millimeter-wave (mmWave) radar sensor to measure human vital signs, specifically a heartbeat.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz in order to effectively measure human vital signs (see Schwarz: [Abstract]). A millimeter-wave (mmWave) radar sensor is one of a finite number of sensor types which can be used to measure human vital signs, such as heartbeat measurements (i.e. heart rate) with a reasonable expectation of success. Thus, modifying the method of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz would yield the predictable result of effectively measuring human vital signs (see Schwarz: [Abstract]).
Claim(s) 9 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mohanty et al. US 2023/0294514 A1 “Mohanty” and further in view of Schwarz, Chris et al., Heartbeat Measurement with Millimeter Wave Radar in the Driving Environment, 2021, IEEE Radar Conference “Schwarz” as applied to claims 1 and 10 above, and further in view of Visconti US 2017/0000344 A1 “Visconti”.
Regarding claims 9 and 19, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claims 1 and 10 above, however, Mohanty and Schwarz does not teach “wherein the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated” (Claims 9 and 19).
Visconti is within a related field of endeavor to the claimed invention because it involves a system and method for optical detection of cognitive impairment of a person using a portable video capture video (PVCD) (see [Abstract]).
Visconti teaches “wherein the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated” (Claims 9 and 19) (“The present disclosure is directed generally to a system and method for testing for cognitive impairment due to the influence of alcohol, drugs, an injury or fatigue. […] In one embodiment, the system and method uses a free-hand portable testing apparatus to detect involuntary eye movement or reflex that are affected by fatigue, the consumption of alcohol, drugs, or trauma, and to inform users of the impairment level and an estimated recovery time before they may decide to operate, or not, a moving vehicle and decide or not to contact a transportation or emergency service or a trusted personal contact” [0030]; “FIG. 14 is a flowchart illustrating a method to perform a correlation and prediction process according to one embodiment of the present disclosure. Referring to FIG. 14, the method begins with acquiring measurement data (1402). Next, the system interacts with user (1404). By interact with the user it is meant that the user interface may request additional information from the user, like activities performed before the test, if alcohol or any other substance has been consumed. This additional information is used to correlate the impairment level to other impairment measurements. For example, in case of impairment due to alcohol consumption, a Blood Alcohol Concentration (BAC) value may be estimated. A reference set including reference parameters is built and/or updated (1406). Next, the level of impairment of the person undergoing test is determined by comparing calculated parameters to the reference parameters (1408), a significant variation of pupil reflex is always an indication of some sort of impairment, subsequently with or without the additional information provided by the user, the correlation to other impairment measures is evaluated (1410). Where the impairment is due to intoxication, a recovery time can be estimated (1412) or for some other kind of impairment a recommendation of seeking immediate medical help can be provided. Finally, the results are displayed to a user (1414)” [0061].
Therefore, since the method shown in FIG. 14 involves acquiring information from a user to determine the impairment level due to alcohol consumption, estimating a blood alcohol concentration and estimating a recovery time (See [0061]), the recovery time representing a time before they may decide to operate, or not, a moving vehicle and decide or not to contact a transportation or emergency service or a trusted personal contact (see [0030]), the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method and system of Mohanty in view of Schwarz such that the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated (i.e. a recovery time) as disclosed in Visconti in order to protect a person experiencing intoxication through warning them: 1) when it is safe to operate a moving vehicle and/or 2) whether they should contact transportation, an emergency service or a trusted personal contact (see Visconti: [0030]). When a person is cognitively impaired as a result of the influence of alcohol, is it important that the person not engage in risky behaviors such as operating a motor vehicle, in order to protect themselves and others. Predicting a recovery time (i.e. an amount of time until the person is not intoxicated) and providing that information to an intoxicated person is one of a finite number of techniques which can be used to protect the intoxicated person and others with a reasonable expectation of success. Thus, modifying the method and system of Mohanty in view of Schwarz such that the processing system is further configured to predict, based at least in part on the blood-alcohol content of the person, an amount of time until the person is not intoxicated (i.e. a recovery time) as disclosed in Visconti would yield the predictable result of protecting the person experiencing intoxication (i.e. and consequently other people) through warning them 1) when it is safe to operate a moving vehicle and/or 2) whether they should contact transportation, an emergency service or a trusted personal contact (see Visconti: [0030]).
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mohanty et al. US 2023/0294514 A1 “Mohanty” and further in view of Schwarz, Chris et al., Heartbeat Measurement with Millimeter Wave Radar in the Driving Environment, 2021, IEEE Radar Conference “Schwarz” as applied to claim 10 above, and further in view of Kawamoto US 2018/0284774 A1 “Kawamoto”.
Regarding claim 18, Mohanty in view of Schwarz discloses all features of the claimed invention as discussed with respect to claim 10 above, and Schwarz further teaches “the mmWave radar sensor” (See [Abstract]; [Page 2, II. Method, Para. 2, Line 1-2]; [Page 2, A. Radar Configuration]; and [Page 3, 1) Peak Spectrum] as discussed in claim 10 above. Therefore, Schwarz utilizes a millimeter-wave (mmWave) radar sensor to measure human vital signs, specifically a heartbeat.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz in order to effectively measure human vital signs (see Schwarz: [Abstract]). A millimeter-wave (mmWave) radar sensor is one of a finite number of sensor types which can be used to measure human vital signs, such as heartbeat measurements (i.e. heart rate) with a reasonable expectation of success. Thus, modifying the method and system of Mohanty such that the sensor is a millimeter-wave (mmWave) radar sensor as disclosed in Schwarz would yield the predictable result of effectively measuring human vital signs (see Schwarz: [Abstract]).
However, the combination of Mohanty and Schwarz does not teach "wherein the […] sensor is disposed within a seat of a vehicle”.
Kawamoto is within a related field of endeavor to the claimed invention because it involves a driving control apparatus (see [Abstract]) with an in-vehicle information detection unit 2500 (See [0353]).
Kawamoto teaches "wherein the […] sensor is disposed within a seat of a vehicle” (“The in-vehicle information detection unit 2500 detects in-vehicle information. For example, a driver state detection section 2510 that detects the driver's state is connected to the in-vehicle information detection unit 2500. The driver state detection section 2510 may be a camera that images the driver, a biological sensor that detects biological information of the driver, a microphone that collects audio in the compartment, or other apparatus. A biological sensor is provided, for example, on a seat surface, the steering wheel, or other location to detect biological information of a passenger sitting on the seat or the driver holding the steering wheel. The in-vehicle information detection unit 2500 may calculate fatigue level or concentration level of the driver based on detection information input from the driver state detection section 2510. Whether the driver is drowsing may be decided” [0353].
Therefore, the biological sensor is provided on the seat surface to detect biological information of a passenger sitting on the seat.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Mohanty and Schwarz such that the mmWave sensor is disposed within a seat of a vehicle as disclosed in Kawamoto in order to effectively detect biological information from a passenger sitting on the seat (see Kawamoto: [0353]). Disposing a sensor within a seat of a vehicle is one of a finite number of techniques which can be used to detect a signals from a person sitting thereon with a reasonable expectation of success. Thus, modifying the system of Mohanty and Schwarz such that the mmWave sensor is disposed within a seat of a vehicle as disclosed in Kawamoto would yield the predictable result of effectively detecting biological information from a passenger sitting on the seat (see Kawamoto: [0353]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nothacker et al. US 2021/0113153 A1 “Nothacker” is pertinent to the applicant’s disclosure because it discloses “a method for monitoring intoxication of a user” which involves “providing a notification to the user based on the intoxication metric” (see [Abstract]).
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/KAITLYN E SEBASTIAN/Examiner, Art Unit 3797
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