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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on March 23, 2026 has been entered.
Response to Amendment
The amendment filed March 11, 2026 has been entered. Claims 1-2, 4-5, 8, 10, 13-16, 18-20, 24, 26, 33-34, 37, 39, 41, 43, 47, and 85 remain pending in the application, where claims 3, 6-7, 11-12, 17, 21-23, 27-32, 35-36, 38, 40, 42, 44-46, and 48-84 were cancelled and claim 85 was newly added. Applicant’s amendments to the claims have overcome each and every 102 rejections previously set forth in the Final Office Action mailed December 23, 2025. Applicant’s amendments to the claims necessitate new grounds of rejection, as described in the Response to Arguments, 112 Rejections, and 103 Rejections below.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 4-5, 8, 10, 13-16, 18-20, 24, 26, 33-34, 37, 39, 41, 43, 47, and 85 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "to produce second physiological data" in line 13. It is unclear if this is meant to be the same second physiological data as recited in line 4, as the term is not preceded by “the” or “said”. Is the recitation of “second physiological data” in line 13 meant to refer to different data? Further clarification is required. Claims 2, 4-5, 8, 10, 13-16, 18-20, 24, 26, and 85 are rejected based on their dependence on claim 1.
Claim 33 recites the limitation "to produce second physiological data" In line 18. It is unclear if this is the same second physiological data as recited in line 7, as the term is not preceded by “the” or “said”. Is the recitation of “second physiological data” in line 18 meant to refer to different data? Further clarification is required. Claims 34, 37, 39, 41, 43, and 47 are rejected based on their dependence on claim 33.
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.
Claims 1-2, 4-5, 8, 10, 13-16, 18-19, 24, 26, 33-34, 37, 39, 41, 43, 47, and 85 are rejected under 35 U.S.C. 103 as being unpatentable over US 20180220897 A1 (Meger et al.) in view of US 20180106897 A1 (Shouldice et al.).
Regarding claim 1, Meger teaches a method comprising:
receiving, from a first sensor, first physiological data associated with the sleep session of a user ([0146] “system 10 comprises another type of sensor, such as an acoustic or air-flow sensor attached or directed at the patient's face, neck, chest, and/or back, or placed under the mattress.”; [0148] “Breathing pattern analysis module 22 analyzes changes in breathing patterns, typically during sleep.”; [0205] “one or more contact sensors applied to patient 12, such as a blood oxygen monitor 86 (e.g., a pulse oximeter/photoplethysmograph), an ECG monitor 62, or a temperature sensor 80”);
receiving, from a second sensor, second physiological data associated with a sleep session of a user ([0140] “Motion sensor 30 may comprise a ceramic piezoelectric sensor, vibration sensor, pressure sensor, or strain sensor, for example, a strain gauge, configured to be installed under a resting surface 37, and to sense motion of patient 12. The motion of patient 12 sensed by sensor 30, during sleep, for example, may include regular breathing movement, heartbeat-related movement, and other, unrelated body movements, as discussed below, or combinations thereof”);
determining a first set of sleep-related parameters associated with the sleep session of the user based at least in part on the first physiological data ([0195] “in order to maximize the patient's quality of sleep, pattern analysis module 16 of system 10 (e.g., signal analysis functionality 90 of the pattern analysis module) identifies a sleep condition of the patient (e.g., by identifying that the patient is asleep, or by identifying a current sleep stage of the patient) by analyzing the signal from sensor 30”);
determining a second set of sleep-related parameters associated with the sleep session of the user based at least in part on the second physiological data ([0140] ‘The motion of patient 12 sensed by sensor 30, during sleep, for example, may include regular breathing movement, heartbeat-related movement, and other, unrelated body movement”); and
determining a subsequent first set of sleep-related parameters associated with a subsequent sleep session of the user based in part on the first physiological data collected by the first sensor during the subsequent sleep session, wherein the calibrated second sensor generates the second physiological data to determine a subsequent second set of sleep-related parameters when the first sensor is not generating the first physiological data during the subsequent sleep session, and wherein information provided from the second set of sleep-related parameters is the same as, or similar to, information that would be obtained from the first set of sleep-related parameters ([0205] “Control unit 14 extracts pulse information from the contact sensors. In order to identify the paired motion sensor 30 among several such transmitting motion sensors 30 within wireless range of the control unit, the control unit calculates the pulse data from each wireless signal received from a motion sensor 30 and identifies a signal that has pulse data that correlates with information received from contact sensors. Upon identifying such a match, the control unit records identifying features of the wireless communication module 56 coupled to the identified motion sensor 30 (e.g., a transmitter unique ID), such that from that point onward the identified sensor 30 is paired to control unit 14. For some applications, upon performing such pairing, control unit 14 notifies a clinician that contact sensors are no longer required and that the patient can be monitored with contact-less sensor 30 only, or with fewer contact sensors.”).
Meger does not explicitly teach calibrating the second sensor based at least in part on a comparison between the first set of sleep-related parameters and the second set of sleep-related parameters from the sleep session, wherein the calibrating the second sensor includes modifying one or more parameters of the second sensor to produce second physiological data resulting in the determined second set of sleep-related parameters to match or correspond to the determined first set of sleep-related parameters.
However,
Shouldice teaches calibrating the second sensor based at least in part on a comparison between the first set of sleep-related parameters and the second set of sleep-related parameters from the sleep session, wherein the calibrating the second sensor includes modifying one or more parameters of the second sensor to produce second physiological data resulting in the determined second set of sleep-related parameters to match or correspond to the determined first set of sleep-related parameters ([0031] “a sleep parameter”; [0040] “the system or method may include multiple sensors arranged for detecting the same or different persons, the system may automatically adjust parameters, such as sensing control parameters, of the multiple sensors”; [0216-0218]; [0246-0248]).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the method taught by Meger to include calibrating the second sensor based on the first sensor to match/correspond the second set of sleep-related parameters to the first set of sleep-related parameters. One would have been motivated to make this modification because a sensor can serve as a basis for adjusting parameters of other sensors to reduce interference and achieve good biometric signal quality, as suggested by Shouldice [0247-0248].
Regarding claim 2, Meger teaches the method of claim 1, wherein the first sensor is physically coupled to or integrated in a respiratory therapy system configured to supply pressurized air to a user interface that is configured to engage a portion of the user ([0344] “system 10 controls PAP device 200 or PAP device 202 to selectively activate the device to apply PAP, or to facilitate normal breathing by the subject”; [0346] “Upon detection that PAP is required, system 10 drives an air source 210 to apply air pressure to the mask via an air delivery tube 212”).
Regarding claim 4, Meger teaches the method of claim 2, wherein (i) the first sensor is a
pressure sensor or a flow rate sensor ([0146] “system 10 comprises another type of sensor, such as an acoustic or air-flow sensor attached or directed at the patient's face, neck, chest, and/or back, or placed under the mattress”) and (ii) the second sensor is a motion sensor, an acoustic
sensor, an RF sensor, a PPG sensor ([0061] “the motion sensor is configured to generate a motion signal including (a) a cardiac related component, and (b) a respiration related component”), or any combination thereof.
Regarding claim 5, Meger teaches the method of claim 2, wherein the first sensor is configured to generate the first physiological data when the user interface is engaged with the user ([0111] “sensing a respiratory-related parameter of the subject while the mask is on the face of the subject”) and the second sensor is configured to generate the second physiological data when the user interface is engaged with the user and when the user interface is not engaged with the user ([0188] “a sensor, such as the motion sensor under the patient's mattress, is used to continuously monitor the patient's heart rate”; [0345-0346]).
Regarding claim 8, Meger teaches the method of claim 7.
Meger does not explicitly teach wherein the one or more parameters of the second sensor include a frequency, a phase, a power, an intensity, modulation of signal of the sensor, a beam pattern, on and off of one or more antennas of the sensor, beam forming, a physical position of one or more antennas of the sensor, a physical position of the sensor, or any combination thereof.
However,
Shouldice teaches wherein the one or more parameters of the second sensor include a frequency, a phase, a power, an intensity, modulation of signal of the sensor, a beam pattern, on and off of one or more antennas of the sensor, beam forming, a physical position of one or more antennas of the sensor, a physical position of the sensor, or any combination thereof ([0247] “For example, adjustable parameters may include the range gating pulse timing and emitted power levels (within allowable regulatory limits) or RF detection frequency (e.g., center frequency) of the sensors”; [0260] “adjust the orientation of one or more sensors”; [0261]).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the method taught by Meger to include adjusting the frequency, power, and/or position of the sensors. One would have been motivated to make this modification because adjusting these sensor parameters helps to reduce interference and achieve good biometric signal quality, as suggested by Shouldice [0247-0248].
Regarding claim 10, Meger teaches the method of claim 1, wherein first set of sleep related parameters includes a first respiration signal associated with the user during the sleep session and the second set of sleep related parameters includes a second respiration signal associated with the user during the sleep session, wherein prior to the calibration of the second sensor, the second respiration signal does not match the first respiration signal and wherein subsequent to the calibration of the second sensor, the second respiration signal does match the first respiration signal ([0159] “the patterns analyzed by one sensor are used to enhance the accuracy of readings by another. For example, the contact-less semi-rigid piezoelectric sensing plate may be used to measure the heart rate related signal, respiratory related signal, and motion signal, and to detect the patient's posture change as described herein. By identifying that the patient has returned to the same position and only then activating the weight sensors, the system can verify that the weight measurement is always done in a similar body position and a point in time when the patient is not moving, thus increasing the accuracy of the weight measurement”; [0321] “For some applications, pattern analysis module 16 of control unit 14 (e.g., signal analysis functionality 90 of the pattern analysis module) calculates a quality index for the readings from each of the sensors and continuously selects the results with the higher quality index. Additionally, in some situations, one of the sensors may more effectively detect patient motion readings. The motion readings may be used to filter out false readings from both sensors.”).
Regarding claim 13, Meger teaches the method of claim 2, further comprising causing an indication of the first set of sleep related parameters, the second set of sleep related parameters, or both to communicated to the user ([0288-0294] “This alert is generated if one or more of the following indications provide abnormal values: [0289] 1. Nightly average of heart rate (e.g., higher than 100 BPM or lower than 40 BPM). [0290] 2. Nightly average of respiration rate (e.g., higher than 30 Br/min or lower than 8 Br/min). [0291] 3. Sleep irregularity indication, e.g., as described hereinabove. [0292] 4. Fast and/or shallow respiration indication, e.g., as described hereinabove. [0293] 5. Increase in the nightly average of the heart rate as compared to one or more previous nights (e.g., a change of over 15 percent). [0294] 6. Increase in the nightly average of the respiration rate as compared to one or more previous nights (e.g., a change of over 20 percent).”).
Regarding claim 14, Meger teaches the method of claim 13, wherein the indication includes a comparison of at least a portion of the first set of sleep related parameters with at least a portion of the second set of sleep related parameters ([0215] “([0159] “the patterns analyzed by one sensor are used to enhance the accuracy of readings by another”).
Regarding claim 15, Meger teaches the method of claim 14, wherein the indication is indicative of a quality of sleep for the user during a first portion of the sleep session where the user interface is engaged with the user and a quality of sleep for the user during a second portion of the sleep session where the user interface is not engaged with the user ([0334]; [0336] “system 10 is configured to generate an output that indicative of a correlation between an improvement in the patient's condition and compliance of the patient with a protocol”; [0341] “System 10 then identifies changes in quality of sleep and correlates that with the lack of compliance of the patient with the therapy.”; [0347] “When PAP is not required, for example when the system detects that the subject is awake, or when the system does not detect any apnea events, the system keeps mask vents 222 open to facilitate normal and comfortable breathing by the subject, as shown in FIG. 14A. Upon detecting that PAP is required, system 10 activates air source 210, which expands spring 214, pushing a covering element 224 over mask vents 222, and opening vent hole 218, through with PAP is delivered into mask 204 and through it to the subject's airways.”).
Regarding claim 16, Meger teaches the method of claim 13, further comprising causing a recommendation to adjust one or more sleeping habits to be communicated to the user, wherein the recommendation to adjust one or more sleeping habits of the user includes a recommendation to modify a time that the user goes to bed, a time that the user wakes up, a duration of the sleep session, an amount of time the user wears the mask during the sleep session, or any combination thereof ([0334] “system 10 is used to monitor compliance of the patient with a protocol of use of a continuous positive airway pressure (CPAP) device, and/or a similar device, that is used to prevent sleep apnea. The system is typically configured to remind patients to use the device if the number of apneas detected increases versus a baseline. Sleep apnea is known to affect cardiac function. Therefore, for some applications, system 10 is used to encourage a patient to use a CPAP device, or a similar device, by showing the patient the changes in cardiac condition that take place when the CPAP device is not used and how that increases the patient's risk of undergoing a severe cardiac deterioration”).
Regarding claim 18, Meger teaches the method of claim 14, the indication includes a quality of sleep metric that is indicative of a quality of sleep for the user during the sleep session and a recommendation to adjust one or more sleeping habits of the user to aid in improving the quality of sleep metric ([0195] “in order to maximize the patient's quality of sleep, pattern analysis module 16 of system 10 (e.g., signal analysis functionality 90 of the pattern analysis module) identifies a sleep condition of the patient (e.g., by identifying that the patient is asleep, or by identifying a current sleep stage of the patient) by analyzing the signal from sensor 30. In response thereto, the pattern analysis module (e.g., signal analysis functionality 90 of the pattern analysis module) automatically changes a parameter of the intervention mechanism, such as to optimize sleep quality by sleep stage”).
Regarding claim 19, Meger teaches the method of claim 18, wherein the indication further includes a predicted quantitative improvement in the quality of sleep metric corresponding to the user implementing the recommended adjustment to the one or more sleeping habits ([0341] “system 10 calculates a quality of sleep index based on the measured respiratory, cardiac and motion parameters. System 10 then identifies changes in quality of sleep and correlates that with the lack of compliance of the patient with the therapy”).
Regarding claim 20, Meger teaches the method of claim 19, wherein the recommended adjustment to the one or more sleeping habits includes a recommendation to increase an average amount of time of use of the respiratory therapy system ([0257] “In response thereto, the pattern analysis module generates an output indicating that the patient is not ready to be weaned off the ventilator, or indicating that the patient may require further respiratory therapy. In some applications, this detection is done by identifying an unstable respiration pattern”).
Regarding claim 24, Meger teaches the method of claim 2, further comprising modifying one or more parameters of the respiratory therapy system based at least in part on the first set of sleep-related parameters, the second set of sleep-related parameters, or both, wherein the modifying the one or more parameters includes a modification of a ramp time of the respiratory device, a modification of a pressure setting of the respiratory device, a modification of a pressure setting responsive to a determination that the user has awaken from the sleep session, or any combination thereof ([0347] “When PAP is not required, for example when the system detects that the subject is awake, or when the system does not detect any apnea events, the system keeps mask vents 222 open to facilitate normal and comfortable breathing by the subject, as shown in FIG. 14A.”).
Regarding claim 26, Meger teaches the method of claim 1, wherein the first set of sleep related parameters and the second set of sleep related parameters include a sleep score, a flow signal, a respiration signal, a respiration rate, an inspiration amplitude, an expiration amplitude, an inspiration-expiration ratio, a number of events per hour, a pattern of events, a sleep state, pressure settings of the respiratory therapy system, a heart rate, a heart rate variability, movement of the user, or any combination thereof ([0341] “system 10 calculates a quality of sleep index based on the measured respiratory, cardiac and motion parameters”; [0152]), wherein the events include central apneas, obstructive apneas, mixed apneas, hypopneas, snoring, periodic limb movement, restless leg syndrome, or any combination thereof ([0343] “techniques of this embodiment are used to treat a subject suffering from obstructive sleep apnea (OSA), without preventing the subject from falling asleep.”).
Regarding claim 33, Meger teaches a system comprising:
a respiratory device configured to (i) supply pressurized air ([0343] “system 10 comprises a Positive Airway Pressure (PAP) device”) and (ii) generate first physiological data associated with a user of the respiratory device during a sleep session ([0146] “system 10 comprises another type of sensor, such as an acoustic or air-flow sensor attached or directed at the patient's face, neck, chest, and/or back, or placed under the mattress.”);
a user interface coupled to the respirator device via a conduit, the user interface being configured to engage the user during the sleep session to aid in directing the supplied pressurized air to an airway of the user ([0346] “Upon detection that PAP is required, system 10 drives an air source 210 to apply air pressure to the mask via an air delivery tube 212, a distal end of which is positioned within a tubular cavity 213 of the mask.”);
a sensor configured to generate second physiological data associated with the user of the respiratory device during the sleep session ([0140] “Motion sensor 30 may comprise a ceramic piezoelectric sensor, vibration sensor, pressure sensor, or strain sensor, for example, a strain gauge, configured to be installed under a resting surface 37, and to sense motion of patient 12. The motion of patient 12 sensed by sensor 30, during sleep, for example, may include regular breathing movement, heartbeat-related movement, and other, unrelated body movements, as discussed below, or combinations thereof”);
a memory storing machine-readable instructions ([0148-0149] “a dual port RAM”); and
a control system ([0144] “control unit 14”) including one or more processors (Figs. 2-3; [0148] “modules 23, 26, 28, 29, and 31 may include a digital signal processor”) configured to execute the machine-readable instructions to:
analyze the first physiological data to determine a first set of sleep related parameters for the user during the sleep session ([0146] “system 10 comprises another type of sensor, such as an acoustic or air-flow sensor attached or directed at the patient's face, neck, chest, and/or back, or placed under the mattress.”; [0148] “. Breathing pattern analysis module 22 analyzes changes in breathing patterns, typically during sleep.”; [0195] “in order to maximize the patient's quality of sleep, pattern analysis module 16 of system 10 (e.g., signal analysis functionality 90 of the pattern analysis module) identifies a sleep condition of the patient (e.g., by identifying that the patient is asleep, or by identifying a current sleep stage of the patient) by analyzing the signal from sensor 30”);
analyze the second physiological data to determine a second set of sleep related parameters for the user during the sleep session ([0140] ‘The motion of patient 12 sensed by sensor 30, during sleep, for example, may include regular breathing movement, heartbeat-related movement, and other, unrelated body movement”); and
determine a subsequent first set of sleep-related parameters associated with a subsequent sleep session of the user based in part on the first physiological data collected by the first sensor during the subsequent sleep session, wherein the calibrated sensor generates the second physiological data to determine a subsequent second set of sleep-related parameters when the respiratory device is not generating the first physiological data during the subsequent sleep session, and wherein information provided from the second set of sleep-related parameters is the same as, or similar to, information that would be obtained from the first set of sleep-related parameters ([0205] “Control unit 14 extracts pulse information from the contact sensors. In order to identify the paired motion sensor 30 among several such transmitting motion sensors 30 within wireless range of the control unit, the control unit calculates the pulse data from each wireless signal received from a motion sensor 30 and identifies a signal that has pulse data that correlates with information received from contact sensors. Upon identifying such a match, the control unit records identifying features of the wireless communication module 56 coupled to the identified motion sensor 30 (e.g., a transmitter unique ID), such that from that point onward the identified sensor 30 is paired to control unit 14. For some applications, upon performing such pairing, control unit 14 notifies a clinician that contact sensors are no longer required and that the patient can be monitored with contact-less sensor 30 only, or with fewer contact sensors.”).
Meger does not explicitly teach based at least in part on a comparison of the first set of sleep related parameters with the second set of sleep related parameters from the sleep session, calibrate the sensor by modifying one or more parameters of the sensor to produce second physiological data resulting in the determined second set of sleep-related parameters to match or correspond to the determined first set of sleep-related parameters.
However,
Shouldice teaches based at least in part on a comparison of the first set of sleep related parameters with the second set of sleep related parameters from the sleep session, calibrate the sensor by modifying one or more parameters of the sensor to produce second physiological data resulting in the determined second set of sleep-related parameters to match or correspond to the determined first set of sleep-related parameters ([0040] “the system or method may include multiple sensors arranged for detecting the same or different persons, the system may automatically adjust parameters, such as sensing control parameters, of the multiple sensors”; [0216-0218]; [0246-0248]).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the system taught by Meger to include calibrating the sensor to match/correspond the second set of sleep-related parameters to the first set of sleep-related parameters. One would have been motivated to make this modification because sensor data can serve as a basis for adjusting parameters of other sensors to reduce interference and achieve good biometric signal quality, as suggested by Shouldice [0247-0248].
Regarding claim 34, Meger teaches the system of claim 33, wherein the first set of sleep related parameters and the second set of sleep related parameters include a sleep score, a flow signal, a respiration signal, a respiration rate, an inspiration amplitude, an expiration amplitude, an inspiration-expiration ratio, a number of events per hour, a pattern of events, a sleep state, pressure settings of the respiratory device, a heart rate, a heart rate variability, movement of the user, or any combination thereof ([0341] “system 10 calculates a quality of sleep index based on the measured respiratory, cardiac and motion parameters”; [0152]), wherein the events include central apneas, obstructive apneas, mixed apneas, hypopneas, snoring, periodic limb movement, restless leg syndrome, or any combination thereof ([0343] “techniques of this embodiment are used to treat a subject suffering from obstructive sleep apnea (OSA), without preventing the subject from falling asleep.”).
Regarding claim 37, Meger teaches the system of claim 33, wherein the first set of sleep related parameters includes a first pattern of events of the user during the sleep session and the second set of sleep related parameters includes a second pattern of events of the user during the sleep session, wherein prior to the calibration of the sensor, the second pattern of events does not match the first pattern of events and wherein subsequent to the calibration of the sensor, the second pattern of events does match the first pattern of events ([0159] “the patterns analyzed by one sensor are used to enhance the accuracy of readings by another. For example, the contact-less semi-rigid piezoelectric sensing plate may be used to measure the heart rate related signal, respiratory related signal, and motion signal, and to detect the patient's posture change as described herein. By identifying that the patient has returned to the same position and only then activating the weight sensors, the system can verify that the weight measurement is always done in a similar body position and a point in time when the patient is not moving, thus increasing the accuracy of the weight measurement”; [0321] “For some applications, pattern analysis module 16 of control unit 14 (e.g., signal analysis functionality 90 of the pattern analysis module) calculates a quality index for the readings from each of the sensors and continuously selects the results with the higher quality index. Additionally, in some situations, one of the sensors may more effectively detect patient motion readings. The motion readings may be used to filter out false readings from both sensors.”).
Regarding claim 39, Meger teaches the system of claim 33, wherein the first set of sleep related parameters includes a first sleep score that indicates a first average number of events per hour of the user during the sleep session and the second set of sleep related parameters includes a second sleep score that indicates a second average number of events per hour of the user during the sleep session, wherein prior to the calibration of the sensor, the second average number of events per hour does not match the first average number of events per hour and wherein subsequent to the calibration of the sensor, the second average number of events per hour does match the first average number of events per hour ([0304] “the alert is generated in response to identifying one or more of the following for a substantial period of time (e.g., 20 minutes to 12 hours, for example 1 hour): [0305] 1. Low detection rate of the heart rate of the patient versus a baseline, during time periods during which large body movement is not detected (e.g. detection rate of less than 60 percent when the patient is not showing large body motion but is in bed) while simultaneously having normal respiratory rate detection rates (e.g. over 70 percent) as measured versus a baseline. [0306] 2. Abnormally large range of heart rate results suggesting unstable heart rate, for example, a range of readings that is over 50 percent of a defined average, or standard deviation that is over 35 percent of a defined average, and/or an increase in standard deviation by more than 75 percent versus the average standard deviation based on the previous 24 hours. [0307] 3. Abnormal heart rate reading patterns, such as changes in a heart rate average baseline (for example, an increase in the baseline from 80 beats per minute to 120 beats per minute, where the baseline is defined as the median reading over the last 1 hour, or alternatively the median reading over the last 1 hour but only for those minutes during which patient large body motion was not detected).”).
Regarding claim 41, Meger teaches the system of claim 33, wherein the first set of sleep related parameters includes a first respiration signal of the user during the sleep session and the second set of sleep related parameters includes a second respiration signal of the user during the sleep session, wherein prior to the calibration of the sensor, the second respiration signal does not match the first respiration signal and wherein subsequent to the calibration of the sensor, the second respiration signal does match the first respiration signal ([0159] “the patterns analyzed by one sensor are used to enhance the accuracy of readings by another. For example, the contact-less semi-rigid piezoelectric sensing plate may be used to measure the heart rate related signal, respiratory related signal, and motion signal, and to detect the patient's posture change as described herein. By identifying that the patient has returned to the same position and only then activating the weight sensors, the system can verify that the weight measurement is always done in a similar body position and a point in time when the patient is not moving, thus increasing the accuracy of the weight measurement”; [0321] “For some applications, pattern analysis module 16 of control unit 14 (e.g., signal analysis functionality 90 of the pattern analysis module) calculates a quality index for the readings from each of the sensors and continuously selects the results with the higher quality index. Additionally, in some situations, one of the sensors may more effectively detect patient motion readings. The motion readings may be used to filter out false readings from both sensors.”).
Regarding claim 43, Meger teaches the system of claim 33, wherein the first physiological data is derived from measurements of pressure, air flow, or both within the respiratory device, the mask, the tube, or any combination thereof ([0146] “system 10 comprises another type of sensor, such as an acoustic or air-flow sensor attached or directed at the patient's face, neck, chest, and/or back, or placed under the mattress.”; Abstract “Positive airway pressure (PAP) is applied to the subject via a mask placed on a face of the subject. A respiratory-related parameter of the subject is sensed, while the mask is on the face of the subject”; Figs. 13A-13B).
Regarding claim 47, Meger teaches the system of claim 33.
Meger does not explicitly teach wherein the calibrating the sensor includes modifying one or more parameters of the sensor, the one or more parameters including a frequency, a phase, a power, an intensity, modulation of signal of the sensor, a beam pattern, on and off of one or more antennas of the sensor, beam forming, a physical position of one or more antennas of the sensor, a physical position of the sensor, or any combination thereof.
However,
Shouldice teaches wherein the calibrating the sensor includes modifying one or more parameters of the sensor, the one or more parameters including a frequency, a phase, a power, an intensity, modulation of signal of the sensor, a beam pattern, on and off of one or more antennas of the sensor, beam forming, a physical position of one or more antennas of the sensor, a physical position of the sensor, or any combination thereof ([0040]; [0247] “For example, adjustable parameters may include the range gating pulse timing and emitted power levels (within allowable regulatory limits) or RF detection frequency (e.g., center frequency) of the sensors”; [0260] “adjust the orientation of one or more sensors”; [0261]).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the system taught by Meger to include adjusting the frequency, power, and/or position of the sensors. One would have been motivated to make this modification because adjusting these sensor parameters helps to reduce interference and achieve good biometric signal quality, as suggested by Shouldice [0247-0248].
Regarding claim 85, Meger teaches the method of claim 1.
Meger does not explicitly teach wherein the calibrating the second sensor includes repeating the modifying one or more parameters of the second sensor, the receiving the first physiological data, the receiving the second physiological data, the determining the first set of sleep-related parameters, the determining the second set of sleep-related parameters, and comparing the first set of sleep-related parameters with the second set of sleep-related parameters, until the second set of sleep-related parameters matches or corresponds to the first set of sleep-related parameters.
However,
Shouldice teaches wherein the calibrating the second sensor includes repeating the modifying one or more parameters of the second sensor, the receiving the first physiological data, the receiving the second physiological data, the determining the first set of sleep-related parameters, the determining the second set of sleep-related parameters, and comparing the first set of sleep-related parameters with the second set of sleep-related parameters, until the second set of sleep-related parameters matches or corresponds to the first set of sleep-related parameters ([0246] “For the case of a plurality of sensors cooperating, such as communicating over a wired or wireless link (either continuously or as part of a pairing process) such in a system with a control processor either remotely located or co-located with a sensor, characteristic biometric parameters can be used to dynamically adjust the performance of one or more sensors in order to optimise the physiological recognition of independent human sources, and to reject other sources.”; [0251] “Sensor_b upon detection of biometrics recognized to be associated with its initialized user and biometrics not recognized to be associated with its initialized user, the sensor_b may reduce (e.g., incrementally) its detection range (e.g. via power or range gating adjustments) until it detects only biometrics recognized to be associated with its initialized user”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the system taught by Meger to include repeating calibration of the second sensor until the second set of sleep-related parameters matches or corresponds to the first set of sleep-related parameters. One would have been motivated to make this modification because adjusting these sensor parameters ensures that the sensors are receiving the same biometric signals from the user and that those signals achieve good biometric quality, as suggested by Shouldice [0247-0248, 0251].
Response to Arguments
Applicant's arguments filed March 11, 2026 have been fully considered. With respect to the 102 Rejections in the Final Office Action (See Pages 8-11 of Applicant’s Response “Rejection based on 35 U.S.C. § 102”), Applicant argues that Meger does not teach calibration of the second sensor, or modifying one or more parameters of the second sensor to change the resulting output in claims 1 and 33. There are new grounds of claim rejections that were necessitated by the claim amendments. Meger in view of Shouldice teaches the calibration of the second sensor, as described above in the 103 rejection of claims 1 and 33.
Applicant also argues that Meger does not disclose determining first sleep-related parameters for a subsequent sleep session because the first sensor (contact sensor) is not used in sessions once the contactless sensor is selected. Examiner respectfully disagrees, as [0205] of Meger specifically discloses that “upon performing such pairing, control unit 14 notifies a clinician that contact sensors are no longer required and that the patient can be monitored with contact-less sensor 30 only, or with fewer contact sensors”. Therefore, a contact sensor (first sensor) can be used to detect sleep-related parameters after calibration of the second sensor. Meger teaches that the calibrated contact-less sensor can be used with or without the contact sensors for subsequent sleep sessions, which reads on the claim language of claims 1 and 33 under broadest reasonable interpretation (BRI) (MPEP § 2111 discusses proper claim interpretation, including giving claims their broadest reasonable interpretation in light of the specification during examination).
Applicant argues that Meger does not teach the elements of amended claims 8 and 47 reciting the parameters of the second sensor that may be adjusted. There are new grounds of claim rejections that were necessitated by the claim amendments. Meger in view of Shouldice teaches the calibration of the second sensor, as described above in the 103 rejection of claims 1 and 33.
Applicant argues that Meger does not disclose adjusting the parameters of the motion sensor to change the output pulse data, and thus, there is no disclosure in Meger of repeating the physiological data collection, parameter determination, and comparison steps multiple time until the second set of parameters matches or corresponds to the first set of parameters recited in new claim 85. There is a new ground of claim rejections necessitated by the claim amendment. Claim 85 is rejected over Meger in view of Shouldice, as described in the 103 rejections above.
Claims 2, 4-5, 8, 10, 13-16, 18-20, 24, 26, 34, 37, 39, 41, 43, 47, and 85 are rejected because the rejections of claims 1 and 33 are proper and the prior art teaches or suggests all the features of these claims for the reasons described in the 103 Rejections.
Conclusion
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/EVELYN GRACE PARK/Examiner, Art Unit 3791
/TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791