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 .
Claims Pending
Applicant's arguments, filed 11/24/2025, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 11/24/2025, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Applicant’s previous cancellation of claim 12 is acknowledged.
Claims 1-11 and 13-20 are the current claims hereby under examination.
Claim Objections - Withdrawn
Applicant’s amendments, filed 01/15/2025, have been fully considered, and the previous objection withdrawn.
Claim Interpretation - Withdrawn
Applicant’s amendments, filed 01/15/2025, have been fully considered, and the previous interpretation withdrawn.
Claim Rejections - 35 USC § 112 - Withdrawn
Applicant’s amendments, filed 01/15/2025, have been fully considered and the previous rejection withdrawn.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 claims are generally directed towards a method of managing the power of a sonar-based monitoring device. The method includes activating low power sonar detection based on the device being stationary and at a low power mode with no sonar, increasing to a high-power sonar in response to detecting a breathing pattern in the data, measuring breathing parameters at the high power mode, and then return to the low power mode with no sonar based on a movement of the device.
Claim(s) 1-6, 8-11, 13-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gollakota (US Pub. No. 20210121096) hereinafter Gollakota, and further in view of Larson (US Pub. No. 20170265781) hereinafter Larson, Shah (US Pub. No. 20190336055) hereinafter Shah, Koufos (US Pub. No. 20210064856) hereinafter Koufos, and Niehaus (US Pub. No. 20170245769) hereinafter Niehaus.
Regarding Claim 1, Gollakota discloses a method for sonar-based respiration monitoring (Par. 16, 17), the method comprising:
capturing, using a sonar sensor of the mobile device (Par. 16-17 (microphone and speaker of mobile device)), sonar data in response to activating the sonar-based movement sensing (Par. 16-17 (breathing parameters measured using sonar)) (Fig. 3, step 332-334)(Par. 36-37 (signals generated and reflected signals received));
detecting, by the mobile device, a breathing pattern in the sonar data (Par. 16, 17 (breathing parameters measured)) (Par. 42 (breathing parameters based on data received));
in response to detecting the breathing pattern in the sonar data and while operating in the sonar detection mode (Fig. 3, step 336) (Par. 42 (motion waveform))(Par. 43 (motion waveform)), measuring (Par. 43 (measuring respiratory rate)), by the mobile device, respiration data of a user (Par. 17, 43 (respiratory rate measured)), using the sonar data collected while operating in the sonar detection mode (Par. 17 (sonar)) (Par. 42 (data from motion waveform)) (Par. 43, (data collection)), wherein the respiration data comprises respiration rate (Par. 42-43, (respiratory rate)).
Gollakota fails to explicitly disclose determining, by a mobile device, that the mobile device is stationary while operating in a low power detection mode in which no sonar sensing is performed.
However, Gollakota does teach in an exemplary embodiment determining, by a mobile device, that the mobile device is stationary while operating in a detection mode in which no sonar sensing is performed (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (low power)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Gollakota with that of Gollakota and Shah to explicitly include determining, by a mobile device, that the mobile device is stationary while operating in a low power detection mode in which no sonar sensing is performed through the combination of references as it would have yielded the predictable result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and conserve power.
However, Gollakota fails to explicitly disclose wherein the determining comprises determining that a magnitude of acceleration of the mobile device is below a threshold magnitude (Examiner's Note: Gollakota makes no indication as to the use of a threshold magnitude of acceleration).
Larson does teach determining that a magnitude of acceleration of the mobile device is below a threshold magnitude (Par. 147, “Alternatively, sections of the circuitry could continue to make measurements while most of the circuitry is in a low power “sleep” mode. The device could “awaken” due to events detected by the portion of the circuit that was not put to sleep. Such events could be if the magnitude of acceleration is above or below some threshold, the direction of acceleration changes by some amount, the ambient light measured by the device rises above or below some threshold, the device detects that physical contact with the patient is lost, or a combination of more than one these or other events.”) (Par. 140 (patient sensor device with accelerometer)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Gollakota and Shah with that of Larson to explicitly include wherein the determining of Gollakota comprises determining that a magnitude of acceleration of the mobile device of Gollakota is below a threshold magnitude through the combination of references as it would have yielded the same or similar result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and predictable result of managing power based on the detection of acceleration events (Larson (Par. 147)).
Modified Gollakota fails to explicitly disclose in response to determining that the mobile device is stationary, activating, by the mobile device, sonar-based movement sensing in a low power sonar detection mode;
capturing, using a sonar sensor of the mobile device and while operating in the low power sonar detection mode, sonar data in response to activating the sonar-based movement sensing.
However, Gollakota does teach in response to determining that the mobile device is stationary (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”), activating, by the mobile device, sonar-based movement sensing (Par. 17 (sonar)) (Par. 34 (continuation of the method after information is verified from the sensor));
capturing, using a sonar sensor of the mobile device (Par. 16-17 (microphone and speaker of mobile device)), sonar data in response to activating the sonar-based movement sensing (Par. 16-17 (breathing parameters measured using sonar)) (Fig. 3, step 332-334)(Par. 36-37 (signals generated and reflected signals received)).
Koufos teaches sonar-based movement sensing (Par. 70, “the sensor device may comprise a non-image thermal sensor, time-of-flight sensor, movement sensor, sonar and/or sound sensor arranged to,”) in a low power sonar detection mode (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502));
capturing, using a sonar sensor (Par. 70, (sonar sensor)) of the mobile device (Par. 70, (sensor device)) and while operating in the low power sonar detection mode (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502)), sonar data in response to activating the sonar-based movement sensing (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502)) (Par. 70, “low-power type measurements, detect a geometric shape, a local movement or a sound having typically human characteristics in the sense that the shape, local movement or sound typically and predictably accrues as a result of the presence of the person itself and/or of a voluntary or involuntary activity that the person performs”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Gollakota, Shah, and Larson with that of Koufos to include in response to determining that the mobile device is stationary, activating, by the mobile device, sonar-based movement sensing in a low power sonar detection mode; capturing, using a sonar sensor of the mobile device and while operating in the low power sonar detection mode, sonar data in response to activating the sonar-based movement sensing through the combination of references as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of ensuring that the device is optimally positioned (Gollakota (Par. 34)) and conserve power.
Modified Gollakota fails to explicitly disclose in response to detecting the breathing pattern in the sonar data, activating, by the mobile device, a high power sonar detection mode;
in response to detecting the breathing pattern in the sonar data and while operating in the high power sonar detection mode, measuring, by the mobile device, respiration data of a user using the sonar data collected while operating in the high power sonar detection mode.
However, Gollakota does teach the sonar detection mode (As indicated above).
Koufos further teaches in response to detecting the breathing pattern in the sonar data (Par. 80 (detection of user breathing)) (Par. 70, (sonar sensor)), activating, by the mobile device, a high power detection mode (Par. 65, “such maintained presence detection is performed based on the actual presence detection made in step 404 performed by the sensor device 120, 220”)(Fig. 2-3, step 404, step 503);
in response to detecting the breathing pattern in the data (Par. 80 (detection of user breathing)) and while operating in the high power detection mode (Par. 101, Fig. 3, step 503), measuring, by the mobile device (sensor device 120,220), respiration data of a user (Par. 70, “breathing sound may be detected”)(Par. 101, “The detection in step 503, made using a high-power type measurement performed by the sensor device 120, 220...” “…analysis-based detection of human breathing or a pulse, or even blood pressure or blood flow. Such image-based detection is known as such, and will not be described in detail herein. Importantly, however, such facial feature, breathing, pulse, etc. detection may be performed”) using the data collected while operating in the high power detection mode (Par. 101, “The detection in step 503, made using a high-power type measurement performed by the sensor device 120, 220...” “…analysis-based detection of human breathing or a pulse, or even blood pressure or blood flow. Such image-based detection is known as such, and will not be described in detail herein. Importantly, however, such facial feature, breathing, pulse, etc. detection may be performed”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power and high-power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Gollakota, Shah, Larson, and Koufos with that of Koufos to include in response to detecting the breathing pattern in the sonar data, activating, by the mobile device, a high power sonar detection mode of Gollakota; in response to detecting the breathing pattern in the sonar data and while operating in the high power sonar detection mode of Gollakota, measuring, by the mobile device, respiration data of a user using the sonar data of Gollakota collected while operating in the high power sonar detection mode of Gollakota, wherein the respiration data comprises respiration rate of Gollakota through the combination of references and using the sonar detection mode of Gollakota at a higher power as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of optimizing the power consumption of the device.
Modified Gollakota fails to explicitly disclose while operating in the high power sonar detection mode and measuring the respiration data of the user, detecting, by the mobile device, that the mobile device is moving; and
in response to detecting that the mobile device is moving while operating in the high power sonar detection mode, transitioning to the low power detection mode in which no sonar sensing is performed.
Gollakota does teach operating in the sonar detection mode and measuring the respiration data of the user (As indicated above).
However, Niehaus teaches while operating in the detection mode and measuring the data of the user, detecting, by the mobile device, that the mobile device is moving (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate))…”) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)); and
in response to detecting that the mobile device is moving while operating in the detection mode, transitioning to the low power detection mode in which no sonar sensing is performed (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state. In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state.” (placement in a low power state as a result of motion measured by the device)) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (Low power and high-power)).
Gollakota, Shah, Larson, Koufos, and Niehaus are considered to be analogous art to the claimed invention as they all involve the measurement of biological signals.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Gollakota, Shah, Larson, and Koufos with that of Niehaus to include while operating in the high power sonar detection mode of Gollakota and Koufos and measuring the respiration data of the user of Gollakota and Koufos, detecting, by the mobile device, that the mobile device is moving; and in response to detecting that the mobile device is moving while operating in the high power sonar detection mode of Gollakota and Koufos, transitioning to the low power detection mode in which no sonar sensing is performed of Gollakota through the combination of references and implementing the transition to low power as a result of motion as measurements with motion are less reliable (Niehaus (Par. 166)), differing power modes are known in the art (Shah (Par. 242)), and it would have yielded the predictable result of optimizing the power consumption of the device.
Regarding claim 2, modified Gollakota further discloses wherein detecting the breathing pattern in the sonar data comprises separately analyzing data for a plurality of distance ranges (Gollakota (Par. 16)).
Regarding claim 3, modified Gollakota further discloses wherein detecting the breathing pattern in the sonar data further comprises detecting (Gollakota (Par. 16, 17)), within a distance range of the plurality of distance ranges (Gollakota (Par. 15, 16)), a frequency within a defined breathing frequency range (Gollakota (Par. 15, 16)).
Regarding claim 4, modified Gollakota further discloses wherein the sonar-based movement sensing comprises outputting a plurality of ultrasonic chirps (Gollakota (Par. 35)), wherein each ultrasonic chirp of the plurality of ultrasonic chirps comprises multiple frequencies (Gollakota (Par. 35)).
Regarding claim 5, modified Gollakota further discloses wherein each ultrasonic chirp of the plurality of ultrasonic chirps comprises multiple increases and multiple decreases in chirp magnitude (Gollakota (Par. 35)).
Regarding claim 6, modified Gollakota further discloses outputting, by the mobile device (Gollakota (Par. 20)), via a display of the mobile device (Gollakota (Par. 20)), respiration data for the user based at least in part on the collected respiration data of the user (Gollakota (Par. 30)).
Regarding claim 8, modified Gollakota further discloses detecting the breathing pattern in the sonar data comprises outputting a first plurality of sonar chirps at a first frequency of chirps (Gollakota (Fig. 3, Par. 35)); and collecting respiration data of the user comprises outputting a second plurality of sonar chirps at a second frequency of chirps (Gollakota (Par. 35, 42)), wherein the second frequency of chirps is greater than the first frequency of chirps (Gollakota (Par. 35)).
Regarding claim 9, modified Gollakota further discloses wherein determining that the mobile device is stationary is based on acceleration data obtained from an accelerometer of the mobile device (Gollakota (Par. 29, 34)).
Regarding claim 10, modified Gollakota further discloses the mobile device is exclusively powered by battery (Gollakota (Par. 30)); and the mobile device is selected from the group consisting of: a smartphone; a smartwatch; a gaming device; and a tablet computer (Gollakota (Par. 21)).
Regarding claim 11, Gollakota discloses a mobile device (Par. 17), comprising:
a multipurpose speaker (Par. 15, 31, speaker – 215, “FMCW audio signals that sweep from about 18 kHz to about 22 kHz or higher) and providing the generated audio signals to the speaker 215. The speaker 215 transmits the audio signal”, (transmission of sound at different frequencies));
a multipurpose microphone (Par. 15, 31, microphone - 216);
a movement sensor (Par. 17);
and a processing system (Fig. 2, Par. 26), comprising one or more processors in communication with the multipurpose speaker (Fig. 2, Par. 27, speaker - 215), the multipurpose microphone (Fig. 2, Par. 27, 31, microphone - 216), and the movement sensor (Fig. 2, Par. 29), the processing system is configured to:
activate sonar-based movement sensing using the multipurpose speaker (speaker – 215) (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”), wherein ultrasonic sonar waveforms are output via the multipurpose speaker that is also used for music output (Par. 31, speaker - 215, “audio signals that sweep from about 18 kHz to about 22 kHz or higher”) (Examiners Note: emitting an 18kHz audio signal is considered as music);
while operating in the sonar detection mode (Fig. 3, Steps 332-334) receive sonar data from the multipurpose microphone (Par. 15, 31, microphone – 216) in response to activating the sonar-based movement sensing (Par. 16, 17) ) (Par. 36-37 (signals generated and reflected signals received)), wherein the multipurpose microphone is used for voice communication (Par. 15, 31, microphone – 216, “18 kHz to about 22 kHz or higher) and providing the generated audio signals to the speaker 215…” “... A portion of the sound is reflected or backscattered toward the microphone 216, which converts the sound into electrical audio signals.”);
detect a breathing pattern in the sonar data (Par. 16, 17 (breathing parameters measured)) (Par. 42 (breathing parameters based on data received));
while operating in the sonar detection mode, create respiration data (Par. 43, (respiratory rate)) for a user using the sonar data obtained while operating in the sonar detection mode (Par. 17, 43 (respiratory rate measured)), in response to detecting the breathing pattern in the sonar data (Fig. 3, step 336) (Par. 42 (motion waveform))(Par. 43 (motion waveform)), wherein the respiration data comprises respiration rate (Par. 42-43, (respiratory rate)).
Gollakota fails to explicitly disclose determine that the mobile device is stationary based on data from the movement sensor.
Gollakota does teach in an exemplary embodiment determine that the mobile device is stationary based on data from the movement sensor (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Gollakota with that of Gollakota to include determine that the mobile device is stationary based on data from the movement sensor through the combination of references as it would have yielded the predictable result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)).
Modified Gollakota fails to explicitly disclose wherein the determining comprises determining, from the data from the movement sensor, that a magnitude of acceleration of the mobile device is below a threshold magnitude (Examiner's Note: Gollakota fails to explicitly indicate a threshold magnitude of acceleration).
However, Larson teaches determining, from the data from the movement sensor, that a magnitude of acceleration of the mobile device is below a threshold magnitude (Par. 147, “Alternatively, sections of the circuitry could continue to make measurements while most of the circuitry is in a low power “sleep” mode. The device could “awaken” due to events detected by the portion of the circuit that was not put to sleep. Such events could be if the magnitude of acceleration is above or below some threshold, the direction of acceleration changes by some amount, the ambient light measured by the device rises above or below some threshold, the device detects that physical contact with the patient is lost, or a combination of more than one these or other events.”) (Par. 140 (patient sensor device with accelerometer)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Gollakota with that of Larson to explicitly include wherein the determining of Gollakota comprises determining, from the data from the movement sensor of Gollakota, that a magnitude of acceleration of the mobile device of Gollakota is below a threshold magnitude through the combination of references as it would have yielded the same or similar result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and predictable result of managing power based on the detection of acceleration events (Larson (Par. 147)). Modified Gollakota fails to explicitly disclose activate sonar-based movement sensing using the multipurpose speaker in a low power sonar detection mode in response to determining that the mobile device is stationary, wherein ultrasonic sonar waveforms are output via the multipurpose speaker that is also used for music output;
while operating in the low power sonar detection mode, receive sonar data from the multipurpose microphone in response to activating the sonar-based movement sensing.
Gollakota does teach activate sonar-based movement sensing using the multipurpose speaker (speaker – 215) in response to determining that the mobile device is stationary (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”), wherein ultrasonic sonar waveforms are output via the multipurpose speaker that is also used for music output (Par. 31, speaker - 215, “audio signals that sweep from about 18 kHz to about 22 kHz or higher”) (Examiners Note: emitting an 18kHz audio signal is considered as music);
while operating in the low power sonar detection mode (Fig. 3, step 332-334), receive sonar data from the multipurpose microphone (Fig. 2, Par. 27, 31, microphone - 216) in response to activating the sonar-based movement sensing (Par. 16-17 (microphone and speaker of mobile device)) (Par. 16-17 (breathing parameters measured using sonar)) (Fig. 3, step 332-334)(Par. 36-37 (signals generated and reflected signals received)).
However, Koufos teaches activate (Par. 51, step 401 (start of the method)) sonar-based movement sensing (Par. 70, “the sensor device may comprise a non-image thermal sensor, time-of-flight sensor, movement sensor, sonar and/or sound sensor arranged to,”) using the speaker in a low power sonar detection mode (Par. 70, (sonar sensor)) (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502));
while operating in the low power sonar detection mode (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502)) (Par. 70 (sonar sensor)), receive sonar data in response to activating the sonar-based movement sensing (Par. 70, “low-power type measurements, detect a geometric shape, a local movement or a sound having typically human characteristics in the sense that the shape, local movement or sound typically and predictably accrues as a result of the presence of the person itself and/or of a voluntary or involuntary activity that the person performs”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Gollakota and Larson with that of Gollakota, Koufos, and Shah to include activate sonar-based movement sensing using the multipurpose speaker of Gollakota in a low power sonar detection mode in response to determining that the mobile device is stationary, wherein ultrasonic sonar waveforms are output via the multipurpose speaker that is also used for music output; while operating in the low power sonar detection mode, receive sonar data from the multipurpose microphone of Gollakota in response to activating the sonar-based movement sensing through the combination of references as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and conserve power.
Modified Gollakota fails to explicitly disclose in response to detecting the breathing pattern in the sonar data, activate a high power sonar detection mode; while operating in the high power sonar detection mode, create respiration data for a user using the sonar data obtained while operating in the high power sonar detection mode in response to detecting the breathing pattern in the sonar data, wherein the respiration data comprises respiration rate.
However, Gollakota does teach sonar detection mode (as indicated above).
However, Koufos further teaches in response to detecting the breathing pattern in the sonar data (Par. 80 (detection of user breathing)) (Par. 70, (sonar sensor)), activate a high power detection mode (Par. 65, “such maintained presence detection is performed based on the actual presence detection made in step 404 performed by the sensor device 120, 220”)(Fig. 2-3, step 404, step 503);
while operating in the high power detection mode (Par. 101, Fig. 3, step 503), create respiration data for a user using the data obtained while operating in the high power detection mode in response to detecting the breathing pattern in the data (Par. 101, Fig. 3, step 503) (Par. 101, “The detection in step 503, made using a high-power type measurement performed by the sensor device 120, 220...” “…analysis-based detection of human breathing or a pulse, or even blood pressure or blood flow. Such image-based detection is known as such, and will not be described in detail herein. Importantly, however, such facial feature, breathing, pulse, etc. detection may be performed”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power and high-power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Gollakota, Larson, Koufos, and Shah with that of Koufos to include in response to detecting the breathing pattern in the sonar data, activate a high power sonar detection mode of Gollakota; while operating in the high power sonar detection mode of Gollakota, create respiration data for a user using the sonar data of Gollakota obtained while operating in the high power sonar detection mode of Gollakota in response to detecting the breathing pattern in the sonar data of Gollakota, wherein the respiration data comprises respiration rate of Gollakota through the combination of references and using the sonar detection mode of Gollakota at a higher power as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of optimizing the power consumption of the device.
Modified Gollakota fails to explicitly disclose while operating in the high power sonar detection mode and measuring the respiration data of the user, detect that the mobile device is moving; and
in response to detecting that the mobile device is moving while operating in the high power sonar detection mode, transition to a low power motion detection mode in which no sonar sensing is performed.
However, Gollakota does teach operating in the sonar detection mode and measuring the respiration data of the user (As indicated above).
Niehaus teaches while operating in the detection mode and measuring the data of the user, detect that the mobile device is moving (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate))…”) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)); and
in response to detecting that the mobile device is moving while operating in the detection mode, transition to a low power motion detection mode in which no sonar sensing is performed (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state. In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state.” (placement in a low power state as a result of motion measured by the device)) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (Low power and high-power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Gollakota, Larson, Shah, and Koufos with that of Niehaus to include while operating in the high power sonar detection mode of Gollakota and Koufos and measuring the respiration data of the user of Koufos, detect that the mobile device is moving; and in response to detecting that the mobile device is moving while operating in the high power sonar detection mode of Gollakota and Koufos, transition to the low power detection mode in which no sonar sensing is performed through the combination of references and implementing the transition to low power as a result of motion as measurements with motion are less reliable (Niehaus (Par. 166)), differing power modes are known in the art (Shah (Par. 242)), and it would have yielded the predictable result of optimizing the power consumption of the device.
Regarding claim 13, modified Gollakota further discloses the mobile device further comprising a cellular network interface (Gollakota (Par. 17, 20)), wherein the mobile device is a smartphone that communicates with a cellular network via the cellular network interface (Gollakota (Par. 17, 20)).
Regarding claim 14, modified Gollakota further discloses wherein the processing system being configured to detect the breathing pattern in the sonar data comprises separately analyzing data for a plurality of distance ranges (Gollakota Par. 16, 17)).
Regarding claim 15, modified Gollakota further discloses wherein the processing system being configured to detect the breathing pattern in the sonar data further comprises the processing system being configured to detect (Gollakota (Par. 16, 17)), within a distance range of the plurality of distance ranges, a frequency within a defined permissible breathing range (Gollakota (Par. 15, 16)).
Regarding claim 16, modified Gollakota further discloses wherein the sound emitter outputs a plurality of ultrasonic chirps (Gollakota (Par. 35)), wherein each ultrasonic chirp of the plurality of ultrasonic chirps includes multiple frequencies (Gollakota (Par. 35)).
Regarding claim 17, modified Gollakota further discloses wherein each ultrasonic chirp of the plurality of ultrasonic chirps that is output by the sound emitter comprises multiple increases and multiple decreases in chirp magnitude (Gollakota (Par. 35).
Regarding claim 18, modified Gollakota further discloses further comprising an electronic display (Gollakota (Par. 20)), wherein the processing system is further configured to output the respiration data for the user via the electronic display (Gollakota (Par. 30)).
Regarding claim 20, Gollakota discloses a sonar-based respiration monitoring system (Par. 19), comprising:
a cloud-based server system (Par. 24);
a sound sensor (Par. 15);
a sound emitter (Par. 15);
a movement sensor (Par. 17);
and a processing system (Par. 27), wherein the sonar-based respiration monitoring system is configured to:
activate sonar-based movement sensing using the sound emitter (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”) (Par. 17 (sonar)) (Par. 34 (continuation of the method after information is verified from the sensor));
receive sonar data from the sound sensor in response to activating the sonar-based movement sensing (Par. 16-17 (breathing parameters measured using sonar)) (Fig. 3, step 332-334)(Par. 36-37 (signals generated and reflected signals received));
detect a breathing pattern in the sonar data (Par. 16, 17 (breathing parameters measured)) (Par. 42 (breathing parameters based on data received));
create respiration data for a user (Par. 43, (respiratory data)) using the sonar data obtained while operating in the sonar detection mode in response to detecting the breathing pattern in the sonar data while operating in the sonar detection mode (Fig. 3, step 336) (Par. 42 (motion waveform))(Par. 43 (motion waveform)) (Par. 17 (sonar)), wherein the respiration data comprises respiration rate (Par. 42-43 (respiratory rate)).
Gollakota fails to explicitly disclose determine that the movement sensor is stationary based on data from the movement sensor while operating in a low power detection mode in which no sonar sensing is performed.
However, Gollakota does teach in an exemplary embodiment determine that the movement sensor is stationary based on data from the movement sensor while operating in a low power detection mode in which no sonar sensing is performed (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (low power)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Gollakota with that of Gollakota and Shah to include determine that the movement sensor is stationary based on data from the movement sensor while operating in a low power detection mode in which no sonar sensing is performed through the combination of references as it would have yielded the predictable result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and conserve power.
Modified Gollakota fails to explicitly disclose wherein the determining comprises determining that a magnitude of acceleration of the movement sensor is below a threshold magnitude (Examiner's Note: Gollakota fails to explicitly indicate a threshold magnitude of acceleration).
However, Larson teaches determining that a magnitude of acceleration of the movement sensor is below a threshold magnitude (Par. 147, “Alternatively, sections of the circuitry could continue to make measurements while most of the circuitry is in a low power “sleep” mode. The device could “awaken” due to events detected by the portion of the circuit that was not put to sleep. Such events could be if the magnitude of acceleration is above or below some threshold, the direction of acceleration changes by some amount, the ambient light measured by the device rises above or below some threshold, the device detects that physical contact with the patient is lost, or a combination of more than one these or other events.”) (Par. 140 (patient sensor with accelerometer)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Gollakota and Shah with that of Larson to explicitly include wherein the determining of Gollakota comprises determining that a magnitude of acceleration of the movement sensor of Gollakota is below a threshold magnitude through the combination of references as it would have yielded the same or similar result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and predictable result of managing power based on the detection of acceleration events (Larson (Par. 147)).
Modified Gollakota fails to explicitly disclose activate sonar-based movement sensing in a low power sonar detection mode using the sound emitter in response to determining that the movement sensor is stationary; receive sonar data from the sound sensor while operating in the low power sonar detection mode in response to activating the sonar-based movement sensing.
However, Gollakota does teach activate sonar-based movement sensing in a low power sonar detection mode using the sound emitter in response to determining that the movement sensor is stationary (Par. 17 (sonar)) (Par. 34 (continuation of the method after information is verified from the sensor)) (Par. 34, “The routine 330 can be configured to determine an orientation of the measurement device using, for example, one or more sensing mechanisms (e.g., one or more gyroscopes, accelerometers, compass sensors, cameras). In some embodiments, for example, the one or more sensing mechanisms include one or more of the sensors 217 discussed above with reference to FIG. 2”) (Par. 29, “One or more sensors 217 are configured to provide additional data for use in motion detection and/or identification. The one or more sensors 217 may include, for example, one or more ECG sensors, blood pressure monitors, galvanometers, accelerometers”);
receive sonar data from the sound sensor (Par. 16-17 (microphone and speaker of mobile device)) while operating in the low power sonar detection mode in response to activating the sonar-based movement sensing (Par. 16-17 (breathing parameters measured using sonar)) (Fig. 3, step 332-334) (Par. 36-37 (signals generated and reflected signals received)).
However, Koufos teaches activate (Par. 51, step 401 (start of the method)) sonar-based movement sensing (Par. 70, “the sensor device may comprise a non-image thermal sensor, time-of-flight sensor, movement sensor, sonar and/or sound sensor arranged to,”) in a low power sonar detection mode using the sound emitter (Par. 70, (sonar sensor)) (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502));
receive sonar data (Par. 70, “low-power type measurements, detect a geometric shape, a local movement or a sound having typically human characteristics in the sense that the shape, local movement or sound typically and predictably accrues as a result of the presence of the person itself and/or of a voluntary or involuntary activity that the person performs”) from the sound sensor (Par. 70, (sonar sensor)) while operating in the low power sonar detection mode in response to activating the sonar-based movement sensing (Par. 52, Fig. 2-3, step 402, step 502 (the device is operating in a low power mode at step 402/502)).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Gollakota, Shah, and Larson with that of Gollakota and Koufos to include activate sonar-based movement sensing in a low power sonar detection mode using the sound emitter in response to determining that the movement sensor is stationary; receive sonar data from the sound sensor while operating in the low power sonar detection mode in response to activating the sonar-based movement sensing combination of references as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of ensuring that the device is optimally positioned for use (Gollakota (Par. 34)) and conserve power.
Modified Gollakota fails to explicitly disclose in response to detecting the breathing pattern in the sonar data, activate a high power sonar detection mode; create respiration data for a user using the sonar data obtained while operating in the high power sonar detection mode in response to detecting the breathing pattern in the sonar data while operating in the high power sonar detection mode, wherein the respiration data comprises respiration rate.
However, Gollakota does teach the sonar detection mode (As indicated above).
However, Koufos further teaches in response to detecting the breathing pattern in the sonar data (Par. 80 (detection of user breathing)) (Par. 70, (sonar sensor)), activate a high power detection mode (Par. 65, “such maintained presence detection is performed based on the actual presence detection made in step 404 performed by the sensor device 120, 220”)(Fig. 2-3, step 404, step 503);
create respiration data (Par. 101, “The detection in step 503, made using a high-power type measurement performed by the sensor device 120, 220...” “…analysis-based detection of human breathing or a pulse, or even blood pressure or blood flow. Such image-based detection is known as such, and will not be described in detail herein. Importantly, however, such facial feature, breathing, pulse, etc. detection may be performed”) for a user using the data obtained while operating in the high power detection mode in response to detecting the breathing pattern in the data while operating in the high power detection mode (Par. 101, Fig. 3, step 503) (Par. 101, “The detection in step 503, made using a high-power type measurement performed by the sensor device 120, 220...” “…analysis-based detection of human breathing or a pulse, or even blood pressure or blood flow. Such image-based detection is known as such, and will not be described in detail herein. Importantly, however, such facial feature, breathing, pulse, etc. detection may be performed”).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (normal power and high-power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Gollakota, Larson, Shah, and Koufos with that of Koufos to include in response to detecting the breathing pattern in the sonar data, activate a high power sonar detection mode of Gollakota; and create respiration data for a user using the sonar data of Gollakota obtained while operating in the high power sonar detection mode of Gollakota in response to detecting the breathing pattern in the sonar data while operating in the high power sonar detection mode of Gollakota, wherein the respiration data comprises respiration rate of Gollakota through the combination of references and using the sonar detection mode of Gollakota at a higher power as differing power modes are known in the art (Shah (Par. 242)) and it would have yielded the predictable result of optimizing the power consumption of the device.
Modified Gollakota fails to explicitly disclose while operating in the high power sonar detection mode and measuring the respiration data of the user, detect that the movement sensor is moving; and
in response to detecting that the movement sensor is moving while operating in the high power sonar detection mode, transition to the low power detection mode in which no sonar sensing is performed.
Gollakota does teach operating in the sonar detection mode and measuring the respiration data of the user (As indicated above).
However, Niehaus teaches while operating in the detection mode and measuring the respiration data of the user, detect that the movement sensor is moving (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate))…”) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)); and
in response to detecting that the movement sensor is moving while operating in the detection mode, transition to the low power detection mode in which no sonar sensing is performed (Par. 166, “In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state. In one embodiment, when the motion sensor(s) indicate user activity or motion (for example, motion that is not suitable or optimum to trigger, acquire and/or obtain desired heart rate measurement or data (for example, data used to determine a user's resting heart rate)), the biometric monitoring device and/or the sensor(s) employed to acquire and/or obtain desired heart rate measurement or data may be placed or remain in a low power state.” (placement in a low power state as a result of motion measured by the device)) (Par. 159 (accelerometers))(Par. 163 (physiological sensors and biometric sensors)).
Shah teaches managing the power of a device to operate in three modes (Par. 242, “the system may determine using stored information whether to operate in a low power operating mode, normal operating mode (e.g., default), or high-power operating mode…” (Low power and high-power)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the system of Gollakota, Larson, Shah, and Koufos with that of Niehaus to include while operating in the high power sonar detection mode of Gollakota and Koufos and measuring the respiration data of the user of Koufos, detect that the movement sensor is moving; and in response to detecting that the movement sensor is moving while operating in the high power sonar detection mode of Gollakota and Koufos, transition to the low power detection mode in which no sonar sensing is performed of Gollakota through the combination of references and implementing the transition to low power as a result of motion as measurements with motion are less reliable (Niehaus (Par. 166)), differing power modes are known in the art (Shah (Par. 242)), and it would have yielded the predictable result of optimizing the power consumption of the device.
Claim(s) 7 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gollakota in view of Shah, Larson, Koufos, and Niehaus as applied to claims 1 and 11 above, and further in view of Tiron (US Pub. No. 20220007965) hereinafter Tiron.
Gollakota, Larson, Shah, Koufos, and Niehaus teach the method of claim 1 and device of claim 11 above.
Regarding claim 7, modified Gollakota fails to explicitly disclose wherein an average power of the mobile device used for sensing and collection of respiration data is between 0.1 mW and 0.4 mW.
However, Tiron teaches wherein an average power of the mobile device used for sensing and collection of respiration data is between 0.1 mW and 0.4 mW (Par. 29 (Power consumption is less than 1 mW)).
Gollakota, Shah, Larson, Koufos, Niehaus, and Tiron are considered to be analogous art to the claimed invention as they all involve the measurement of biological signals.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Gollakota, Shah, Larson, Koufos, and Niehaus with that of Tiron to explicitly have the power consumed by the device in the range of 0.1 mW to 0.4 mW as this is a power consumption variation that would have yielded the predictable result of reducing total power consumption (Tiron (Par. 29)).
Regarding claim 19, modified Gollakota fails to explicitly disclose the limitations of the claim.
However, Tiron teaches wherein an average power of the mobile device consumed to perform sensing and collection of respiration data is between 0.1 mW and 0.4 mW (Par. 29 (Power consumption is less than 1 mW)).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Gollakota, Larson, Shah, Koufos, and Niehaus with that of Tiron for the reasons indicated in claim 7 above.
Response to Arguments
Applicant's arguments filed 11/24/2025, regarding the 103 rejection have been fully considered, but are moot in view of the newly applied rejection as a result of the applicant’s amendments to the claims. As a result, the 103 rejection as indicated above has been modified with the use of Larson.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARI SINGH KANE PADDA whose telephone number is (571)272-7228. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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/ARI S PADDA/Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791