DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendments
This Office Action is responsive to the amendment filed 21 October 2025. As directed by the amendment: claims 1, 9, 19, 21, and 31-32 have been amended, claims 4-7, 9, and 19 remain withdrawn, claims 10-18, 23, 25, 27-30, and 33-83 are cancelled, and claims 84-86 have been newly added. Thus, claims 1-3, 8, 20-22, 24, 26, 31-32, and 84-86 are presently pending and under examination.
Response to Arguments
Response to Arguments Regarding 35 U.S.C.§ 112
The amendments to claims 1 and 31-32 have overcome the previously made 35 U.S.C. 112(a) rejection cited in the Non-Final Office Action mailed 05/22/2025.
Response to Arguments Regarding 35 U.S.C. § 102/103
Applicant’s arguments with respect to claim(s) 1-3, 8, 20-26, and 31-32 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Specifically, Applicant argues the use of the Narayanan et al. (US 2023/0148956 A1) is improper due to the cited portions not having a priority date before the priority date of the instant application.
Examiner agrees and has now instead used Phillips (US 2014/0088373 A1), hereinafter Phillips and Kaji (US 2017/0273617 A1), hereinafter Kaji.
Additionally, Examiner would like to note that claims 3, 8, and 84-86 have been indicated as having allowable subject matter.
No additional specific arguments were presented with previous 35 U.S.C. rejections of dependent claims 20-22, 24 and 26, nor specifically with respect to the previously cited Garcia Molina, Huang, Kahn, Arrington, Zigel, Shoeb, and Martinmӓki.
Therefore, claims 1-2, 20-22, 24, 26, and 31-32 are rejected under 35 USC 103, as shown in detail below.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 07/17/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim(s) 1-2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Phillips (US 2014/0088373 A1), hereinafter Phillips in view of Kaji (US 2017/0273617 A1), hereinafter Kaji and further in view of Pardey et al. (EP 0 773 504 A1, previously cited), hereinafter Pardey.
Regarding claim 1, Phillips (US 2014/0088373 A1) discloses a method for monitoring a sleep session of an individual (Abstract: “Methods and apparatus monitor health by detection of sleep stage”, [0002] “The invention relates to the determining of sleep stage of humans using respiration and movement signals”), the method comprising:
Receiving data associated with a current sleep session of the individual ([0025] “detecting one or more signals related to bodily movement and respiration movement of the subject”)
Analyzing at least a portion of the received data to identify one or more sleep stages experienced by the individual during the current sleep session ([0026]-[0027] “analyzing at least a portion of the detected signals to calculate the variability of the respiration rate and/or respiration amplitude; and combining the respiration variability with the bodily movement detection to determine sleep stage.”), the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stage, a wake stage, or any combination thereof ([0058] discusses detecting awake and sleep states, [0059] deep sleep, and N1, N2, AND REM sleep, [0063] light sleep, deep sleep, Figure 9)
Generating a summary of the current sleep session ([0021] “The processor may be used to extract information about breathing and motion, and higher order information such as the sleep stage. A display may be configured to provide feedback to the user, typically at the end of the night, such as displaying a sequence of the overnight sleep stages.”)
Phillips fails to disclose wherein the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data; and the summary including (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).
However, Kaji teaches a device that determines to which of a plurality of sleep stages in a sleep state a subject belongs to wherein the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data ([0019] “the sleep stage determination unit may be configured to easily output a determination that the sleep state of the subject belongs to the sleep stage that tends to appear according to the length of the sleep elapsed time… the sleep stage determination unit may be configured to multiply the sleep stage appearance probability of each of the plurality of sleep stages by a weight according to a tendency of appearance of each of the plurality of sleep stages according to the length of the sleep elapsed time… and to determine as the sleep state of the subject the sleep stage of which the sleep stage appearance probability multiplied by the weight is the highest.”)
Although, Kaji does not explicitly teach receiving temporal data associated with the current sleep session, Kaji does teach that sleep elapsed time is used to determine sleep stage ([0019]) and therefore the data must have been measured/received.
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips to incorporate the teachings of Kaji to have the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data, as these prior art references and the instant application are directed to using obtained physiological data to determine sleep stages. One would be motivated to do this as sleep elapsed time affects the probability of a sleep stage occurring, in other words, the non-REM sleep stages appear in the beginning of sleep and the frequency decreases later, thus taking elapsed time into consideration would allow for a more accurate determination of a sleep stage and the movements that may occurs during these stages, as recognized by Kaji ([0019], [0062]-[0063], [0023], [0065]).
Phillips and Kaji, alone or in combination, fail to teach the summary including (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).
However, Pardey teaches an insomnia or vigilance monitor obtaining a signal from a subject to determine the sleep or wakefulness stage type being experienced by the subject wherein the monitor generates a summary of the current sleep session (pg. 2, line 41-42: "generate a summary index of sleep quality over the period of epochs.. means for analysing the hypnogram to display the summary index of sleep quality.") (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii) ("displays a summary index which provides a simple objective indicator of the degree of insomnia suffered by the subject.", pg. 2, lines 47-53: "Insomnia can manifest itself in many forms, and therefore different sleep summary indices may be generated and displayed. For instance a subject may experience a simple lack of sleep. In this case a low Sleep Efficiency Index (which is the ratio of the time asleep to the time in bed) will provide the required indication and is generated and displayed. Alternatively the subject may have a high Sleep Efficiency Index but may sleep "badly". For instance the subject may experience irregular sleep cycles (e.g. alternating long/short periods of REM sleep). Therefore an alternative or additional summary index may comprise an indication of the periodicity of the sleep/wake continuum").
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips in view of Kaji to incorporate the teachings of Pardey to generate a summary of the current sleep session (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii), as both prior art references and the instant application are directed to monitoring a subject's sleep. One would be motivated to do this as providing a summary index can reduce the time taken by a physician or caretaker to make a decision on whether additional treatment is required, and it does not need particular skills, making it more suitable for GPs to use, as recognized by Pardey (pg. 3, lines 3-5)
Regarding claim 2, Phillips in view of Kaji in view of Pardey teaches the method of claim 1 (as shown above). Phillips further discloses wherein the received data further includes (i) respiration data, (ii) motion data indicative of motion of the individual during the current sleep session, ([0019] “The bodily movement and respiration movement may be obtained through a non-invasive sensor such as radio-frequency motion sensor or a pressure sensitive mattress.”) (iii) audio data indicative of sound detected during the current sleep session.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Phillips in view of Kaji in view of Pardey as applied to claim 1 above, and further in view of Garcia Molina et al. (US Patent 12,016,698 B2, previously cited), hereinafter Garcia Molina.
Regarding claim 20, Phillips in view of Kaji in view of Pardey teaches the method of claim 1 (as shown above). Phillips, Kaji, and Pardey, alone or in combination, fail to teach receiving historical data associated with one or more prior sleep sessions of the individual; generating a historical summary of the one or more prior sleep sessions of the individual, the historical summary including a number of atypical REM sleep stages experienced by the individual during the one or more prior sleep sessions, and a time spent in atypical REM sleep stages during the one or more prior sleep sessions; comparing the historical summary of the one or more prior sleep sessions to the summary of the current sleep session, to aid in confirming the number of atypical REM sleep stages experienced by the individual during the current sleep session, and the time spent in atypical REM sleep stages during the current sleep session.
However, Garcia Molina teaches a system and method for facilitating sleep improvement for a user wherein “One or more reference sleep metrics are determined based on prior user data obtained from one or more prior sleep sessions. One or more immediate values related to the sleep session is/are determined based on a comparison of the sleep metrics with the reference sleep metrics.” (Abstract) wherein “The sleep metrics are, in one embodiment, based on prior user data obtained from one or more prior sleep sessions. For example, prior user data associated with prior sleep sessions may be stored by user history database 140. In response to receiving the first user data, sleep score assessment system 120 may request prior user data from user history database 140, which in turn may provide sleep score assessment system 120 with the prior user data. In one embodiment, the reference sleep metrics are alternatively stored by user history database 140, and therefore sleep score assessment system 120 is then provided with the reference sleep metric(s) in response to providing a request to user history database 140” (Column 19, lines 2-14)
Although, Garcia Molina does not explicitly state that the historical summary includes a number of atypical REM sleep stages experienced by the individual during the one or more prior sleep sessions, and a time spent in atypical REM sleep stages during the one or more prior sleep sessions, it would have been obvious to one skilled in the art that the user history database would comprise similar data, as it is well known in the art as shown by Pardey (above in claim 1).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips, Kaji, and Pardey to incorporate the teachings of Garcia Molina to receive historical data associated with one or more prior sleep sessions of the individual; generating a historical summary of the one or more prior sleep sessions of the individual, the historical summary including a number of atypical REM sleep stages experienced by the individual during the one or more prior sleep sessions, and a time spent in atypical REM sleep stages during the one or more prior sleep sessions; comparing the historical summary of the one or more prior sleep sessions to the summary of the current sleep session, to aid in confirming the number of atypical REM sleep stages experienced by the individual during the current sleep session, and the time spent in atypical REM sleep stages during the current sleep session. One would be motivated to do this because to identify trends, track progress, and make informed predictions/diagnostics about current and future sessions.
Claim(s) 21 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Phillips in view of Kaji in view of Pardey as applied to claim 1 above, and further in view of Huang et al. (US Patent 10,964,195 B1, previously cited), hereinafter Huang.
Regarding claim 21, Phillips in view of Kaji in view of Pardey teaches the method of claim 1 (as shown above). Phillips, Kaji, and Pardey, alone or in combination, fail to teach the method further comprising: analyzing, using a trained dream enactment behavior (DEB) algorithm, at least the portion of the received data to determine whether the individual is undergoing DEB during the current sleep session; and in response to a determination that the individual is undergoing DEB, causing an action to be performed.
However, Huang teaches a method and a system of alerting patient with sleep disorder a change in parameters (Abstract) wherein the method includes analyzing, using a trained dream enactment behavior (DEB) algorithm, at least the portion of the received data to determine whether the individual is undergoing DEB during the current sleep session (Column 7, lines 6-12: “For example, the patient and/or caregiver may review the information recorded during the night, and track the severity of sleep disorder, the development of the sleep disorder, and link it to the behavior of the patient at night. The patient and/or caregiver may set the criteria for sounding the alarm according to the analysis of the recorded information.”); and in response to a determination that the individual is undergoing DEB, causing an action to be performed (Claims 1 and 3, Column 3, line 49-Column 5, line 20: shows different parameters that when it passes a threshold indicating a patient is acting out a dream as described in column 3, line 27-34 an alarm is triggered), the action being configured to (i) aid in ending the DEB, (ii) aid in mitigating an impact of the DEB on the individual, (iii) aid in mitigating an impact of the DEB on a bed partner of the individual, or (iv) any combination thereof (Column 1, line 64-Column 2 line 7: “a method of alerting, preventing injury, and/or monitoring of patient(s) with sleep disorder includes: detecting a change in a parameter(s), and if the change is detected, sounding an alarm, wherein the parameter(s) includes sound, motion, heartbeat, blood pressure, breathing frequency, magnitude and/or frequency of movement. This method aids in preventing the patient from injury and/or harm in that it senses parameters indicative of injury-causing actions and alerts the patient before those actions occur (e.g., before the patient leaves the bed).”).
Although, Huang doesn’t explicitly state that the action (i.e. alarm) aid in mitigating an impact of the DEB on a bed partner of the individual, Huang does teach that the actions of DEB can “cause serious injury and/or harm to themselves, and/or disruptions to others nearby (e.g. sleep partners)” (Column 1, lines 23-25), therefore it would have been obvious to one skilled in the art that since the alarm alerts the patient before the injurious actions occurs it will also mitigate the impact on the bed partner.
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips, Kaji, and Pardey to incorporate the teachings of Huang to analyze using a trained dream enactment behavior (DEB) algorithm, at least the portion of the received data to determine whether the individual is undergoing DEB the current sleep session; and in response to a determination that the individual is undergoing DEB, causing an action to be performed, the action being configured to (i) aid in ending the DEB, (ii) aid in mitigating an impact of the DEB on the individual, (iii) aid in mitigating an impact of the DEB on a bed partner of the individual, or (iv) any combination thereof as these prior art references are directed to analyze and manage sleep. One would be motivated to do this as people with rapid eye movement sleep behavior disorder that act out their dreams can cause serious injury to themselves, and/or disruptions to others nearby (e.g., sleep partners) therefore by performing an action it can prevent injury, as recognized by Huang (Column 2, lines 4-7 and Column 1, lines 18-25).
Regarding claim 24, Phillips in view of Kaji in view of Pardey further in view of Huang teaches the method of claim 21 (as shown above). Phillips, Kaji, and Pardey, alone or in combination, fail to teach wherein the action includes activating a light source, activating an audible alarm, causing a bed on which the individual is lying to move, or causing the individual to be physically moved.
However, Huang teaches wherein the action includes, activating an audible alarm (Column 3, lines 59-62: “If the detected pitch, frequency, intensity, and/or volume exceeds the set criteria, the patient alert system may sound an alarm to wake the patient.”, Figure 3C), causing a bed on which the individual is lying to move, or causing the individual to be physically moved (Column 5, lines 33-37: “the alarm may be physical vibration, or both physical vibration and sound. The alarm may be included in a wearable device such that when triggered, the physical vibration can provide the stimulation to wake up the patient”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips, Kaji, and Pardey to incorporate the teachings of Huang to have the action includes activating a light source, activating an audible alarm, causing a bed on which the individual is lying to move, or causing the individual to be physically moved, as these prior art references are directed to analyze and manage sleep. One would be motivated to do this as people with rapid eye movement sleep behavior disorder that act out their dreams can cause serious injury to themselves, and/or disruptions to others nearby (e.g., sleep partners) therefore by performing an action to wake the patient one can prevent injury, as recognized by Huang (Column 2, lines 4-7 and Column 1, lines 18-25).
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Phillips in view of Kaji in view of Pardey in view of Huang as applied to claim 21 above, and further in view of Kahn et al. (US Patent 11,883,188 B1, previously cited), hereinafter Kahn.
Regarding claim 22, Phillips in view of Kaji in view of Pardey in view of Huang teaches the method of claim 21 (as shown above). Phillips, Kaji, Pardey, and Huang, alone or in combination, fail to teach receiving historical data associated with one or more prior sleep sessions of the individual, the historical data including data related to confirmed instances of the individual undergoing DEB during at least one or more prior sleep sessions; and comparing the historical data associated with one or more prior sleep sessions to the data associated with the current sleep session to aid in determining whether the individual is undergoing DEB during the current sleep session.
However, Kahn teaches a method for receiving data from a sleep sensor and analyzing the data for sleep analysis wherein “sleep-stage calculator 430 data is compared to the output of sleep stage predictor/inference engine 434 by sleep stage verifier 432… data collected over many users may be used to initially populate inference engine's data set. Sleep stage data store 436 stores the current & past sleep state data. This may be used by the inference engine 434, as well as communicated to server system 480, or mobile device 450… the predictive system utilizes historical data and data from collective user statistics 482 provided by server system 480 to make smart predictions” (Column 6, lines 44-57).
Although, Kahn does not explicitly state that the historical data includes data related to confirmed instances of the individual undergoing DEB during at least one or more prior sleep sessions, it would have been known to one skilled in the art that the historical data would include the presence of any sleep disorders as Kahn states that “the processed sleep data which reflects the user's sleep phases and any detected respiratory events, or sleep events such as waking, snoring, etc. This data is used to provide a preliminary analysis of how well the user slept” (Column 7, lines 28-31).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips, Kaji, Pardey, and Huang to incorporate the teachings of Kahn teach receiving historical data associated with one or more prior sleep sessions of the individual, the historical data including data related to confirmed instances of the individual undergoing DEB during at least one or more prior sleep sessions; and comparing the historical data associated with one or more prior sleep sessions to the data associated with the current sleep session to aid in determining whether the individual is undergoing DEB during the current sleep session.. One would be motivated to do this because to identify trends, track progress, and make informed predictions/diagnostics about current and future sessions.
Claim(s) 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Phillips in view of Kaji in view of Pardey as applied to claim 1 above, and further in view of Arrington et al. (US 2019/0223781 A1, previously cited), hereinafter Arrington.
Regarding claim 26, Phillips in view of Kaji in view of Pardey teaches the method of claim 1 (as shown above). Phillips, Kaji, and Pardey, alone or in combination, fail to teach further comprising causing an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the sleep current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii).
However, Arrington teaches a system and method for managing disruptive sleep disorders (Abstract) wherein an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the sleep current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii) ([0061] “the sleep disorder management device 300, the device may be used to monitor a user's sleeping patterns to determine if the user is undergoing a sleep disorder episode and then deliver a physical stimulus to remedy the sleep disorder episode. In some implementations, the sleep disorder management device 300 is triggered by a continued, constant, and/or significant deviation from the user's normal sleeping patterns (e.g., by analyzing the measurable indicators that emanate from the user's body).”, [0072] discloses different types of alerts that are used to remedy the sleep disorder episode, [0083] “More specifically, in some embodiments, the sleep disorder management device 600 triggers the vibrator 606 after detecting continued, constant, and significant deviation from the user's typical REM sleep heart-beat rate ranges.”) .
Although Arrington does not explicitly state that the time spent of the occurrences passing a threshold, it would have been obvious to one skilled in the art to interpret the “continued, constant, and significant deviation” to be equivalent to the performing an action when the time spent is greater than a threshold.
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Phillips, Kaji, and Pardey to incorporate the teachings of Arrington to have an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the sleep current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii), as these prior art references are directed to sleep management. One would be motivated to do this to be able to distinguish between a sleep disorder episode and normal sleeping patterns and to protect/remedy a patient experiencing sleep disorders, ad recognized by Arrington ([0017] and Abstract).
Claim(s) 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shoeb et al. (US Patent 11,147,505 B1, previously cited), hereinafter Shoeb in view of Kaji (US 2017/0273617 A1), hereinafter Kaji, further in view of Pardey et al. (EP 0 773 504 A1, previously cited), hereinafter Pardey.
Regarding claim 31, Shoeb discloses a system (Abstract: "Methods, systems, and devices for identifying abnormal sleep conditions are disclosed") comprising:
An electronic interface (wearable device 110) configured to receive data associated with a sleep session of an individual (Column 41-45: "Each wearable device 110 may capture and/or receive from the sensor(s) 112 a plurality of physiological parameter measurements and a plurality of non-physiological para parameter measurements.", Column 7, lines 40-44: "the server 130 may receive from the wearable devices 110 a plethora of physiological parameter measurements and non-physiological parameter measurements measured over a number of sleep periods")
A memory storing machine-readable instructions (Column 10, lines 35-42: "The data storage 460 may include or take the form of one or more non-transitory, computer-readable storage media that can be read or accessed by at least one processor 450. The one or more computer-readable storage media can include volatile and/or non-volatile storage components, such as optical, magnetic, organic or other memory or disc storage, which can be integrated in whole or in part with at least one of the one or more processors 450")
A control system (controller 440) including one or more processors (processor(s) 450) configured to execute the machine-readable instructions (Column 10, lines 29-34: "The controller 440 may be provided as a computing device that includes one or more processors 450. The one or more processors 450 can be configured to execute computer-readable program instructions 470 that are stored in the data storage 460 and that are executable to provide the functionality of a wearable device 300 described herein.") to:
Analyze at least a portion of the received data to identify one or more sleep stages experiences by the individual during the current sleep session (Column 4, lines 7-15 :" By way of example, the wearable device may receive from a server (or another computing device) data for determining a sleep stage from the plurality of physiological measurements. For instance, the wearable device may receive from a server data indicative of values for physiological parameters and non-physiological parameters, perhaps in the form of one or more vectors, that are indicative of different abnormal sleep conditions."), the one or more sleep stages including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stages, a wake stage, or any combination thereof (Column 4, lines 21-28, Column 17, lines 9-32)
Shoeb fails to disclose wherein the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data; and generate a summary of the current sleep session, the summary including (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).
However, Kaji teaches a device that determines to which of a plurality of sleep stages in a sleep state a subject belongs to wherein the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data ([0019] “the sleep stage determination unit may be configured to easily output a determination that the sleep state of the subject belongs to the sleep stage that tends to appear according to the length of the sleep elapsed time… the sleep stage determination unit may be configured to multiply the sleep stage appearance probability of each of the plurality of sleep stages by a weight according to a tendency of appearance of each of the plurality of sleep stages according to the length of the sleep elapsed time… and to determine as the sleep state of the subject the sleep stage of which the sleep stage appearance probability multiplied by the weight is the highest.”)
Although, Kaji does not explicitly teach receiving temporal data associated with the current sleep session, Kaji does teach that sleep elapsed time is used to determine sleep stage ([0019]) and therefore the data must have been measured/received.
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shoeb to incorporate the teachings of Kaji to have the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data, as these prior art references and the instant application are directed to using obtained physiological data to determine sleep stages. One would be motivated to do this as sleep elapsed time affects the probability of a sleep stage occurring, in other words, the non-REM sleep stages appear in the beginning of sleep and the frequency decreases later, thus taking elapsed time into consideration would allow for a more accurate determination of a sleep stage and the movements that may occurs during these stages, as recognized by Kaji ([0019], [0062]-[0063], [0023], [0065]).
Shoeb and Kaji, alone or in combination, fail to teach generate a summary of the current sleep session, the summary including (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii).
However, Pardey teaches an insomnia or vigilance monitor obtaining a signal from a subject to determine the sleep or wakefulness stage type being experienced by the subject wherein the monitor generates a summary of the current sleep session (pg. 2, line 41-42: "generate a summary index of sleep quality over the period of epochs.. means for analysing the hypnogram to display the summary index of sleep quality.") (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii) ("displays a summary index which provides a simple objective indicator of the degree of insomnia suffered by the subject.", pg. 2, lines 47-53: "Insomnia can manifest itself in many forms, and therefore different sleep summary indices may be generated and displayed. For instance a subject may experience a simple lack of sleep. In this case a low Sleep Efficiency Index (which is the ratio of the time asleep to the time in bed) will provide the required indication and is generated and displayed. Alternatively the subject may have a high Sleep Efficiency Index but may sleep "badly". For instance the subject may experience irregular sleep cycles (e.g. alternating long/short periods of REM sleep). Therefore an alternative or additional summary index may comprise an indication of the periodicity of the sleep/wake continuum").
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shoeb in view of Kaji to incorporate the teachings of Pardey to generate a summary of the current sleep session (i) a number of atypical REM sleep stages experienced by the individual during the sleep current sleep session, (ii) a time spent in atypical REM sleep stages during the current sleep session, or (iii) both (i) and (ii), as both prior art references and the instant application are directed to monitoring a subject's sleep. One would be motivated to do this as providing a summary index can reduce the time taken by a physician or caretaker to make a decision on whether additional treatment is required, and it does not need particular skills, making it more suitable for GPs to use, as recognized by Pardey (pg. 3, lines 3-5)
Claim(s) 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shoeb et al. (US Patent 11,147,505 B1, previously cited), hereinafter Shoeb, in view of Kaji, in view of Martinmäki et al. (US 2018/0242902 A1, previously cited), hereinafter Martinmäki and further in view of Arrington (US 2019/0223781 A1), hereinafter Arrington .
Regarding claim 32, Shoeb teaches a method for monitoring a sleep session of an individual (Abstract: "Methods, systems, and devices for identifying abnormal sleep conditions are disclosed"), the method comprising:
Receiving data associated with a sleep session of an individual (Column 41-45: "Each wearable device 110 may capture and/or receive from the sensor(s) 112 a plurality of physiological parameter measurements and a plurality of non-physiological para parameter measurements.", Column 7, lines 40-44: "the server 130 may receive from the wearable devices 110 a plethora of physiological parameter measurements and non-physiological parameter measurements measured over a number of sleep periods");
identifying, using one or more trained algorithms, one or more sleep stages experienced by the individual during the sleep session (Column 4, lines 15-21: “data may be generated by a server-implemented machine-learning algorithm that receives a plurality of physiological parameter measurements from each of a plurality of wearable devices. Using the received data, the wearable device may determine from the plurality of physiological parameter measurements a sleep stage cycle”), the one or more sleep stages of the individual including a light sleep stage, a deep sleep stage, a typical rapid eye movement (REM) stage, an atypical REM stages, a wake stage, or any combination thereof (Column 4, lines 21-28, Column 17, lines 9-32)
Shoeb fails to disclose the data including temporal data associated with the current sleep session; the identification of the one or more sleep stages being based at least in part on the temporal data; determining a total number of atypical REM sleep stages experienced by the individual during the sleep session; determining a total amount of time the individual experienced the atypical REM sleep stages during the sleep session; and in response to (i) the total number of atypical REM sleep stages satisfying a first threshold, causing an action to be performed, (ii) the total amount of time satisfying a second threshold, causing the action to be performed, or (iii) both (i) and (ii).
However, Kaji (US 2017/0273617 A1) teaches a device that determines to which of a plurality of sleep stages in a sleep state a subject belongs to wherein the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data ([0019] “the sleep stage determination unit may be configured to easily output a determination that the sleep state of the subject belongs to the sleep stage that tends to appear according to the length of the sleep elapsed time… the sleep stage determination unit may be configured to multiply the sleep stage appearance probability of each of the plurality of sleep stages by a weight according to a tendency of appearance of each of the plurality of sleep stages according to the length of the sleep elapsed time… and to determine as the sleep state of the subject the sleep stage of which the sleep stage appearance probability multiplied by the weight is the highest.”)
Although, Kaji does not explicitly teach receiving temporal data associated with the current sleep session, Kaji does teach that sleep elapsed time is used to determine sleep stage ([0019]) and therefore the data must have been measured/received.
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shoeb to incorporate the teachings of Kaji to have the data includes temporal data associated with the current sleep session, the identification of the one or more sleep stages being based at least in part on the temporal data, as these prior art references and the instant application are directed to using obtained physiological data to determine sleep stages. One would be motivated to do this as sleep elapsed time affects the probability of a sleep stage occurring, in other words, the non-REM sleep stages appear in the beginning of sleep and the frequency decreases later, thus taking elapsed time into consideration would allow for a more accurate determination of a sleep stage and the movements that may occurs during these stages, as recognized by Kaji ([0019], [0062]-[0063], [0023], [0065]).
Shoeb and Kaji, alone or in combination, fail to teach determining a total number of atypical REM sleep stages experienced by the individual during the sleep session; determining a total amount of time the individual experienced the atypical REM sleep stages during the sleep session; and in response to (i) the total number of atypical REM sleep stages satisfying a first threshold, causing an action to be performed, (ii) the total amount of time satisfying a second threshold, causing the action to be performed, or (iii) both (i) and (ii).
However, Martinmäki teaches a computer-implemented method that estimates the sleep quality of a user by determining a total number of atypical REM sleep stages experienced by the individual during the sleep session (Figure 7: monitor number of restless sleep signal patterns 700, [0048] “the number of restless sleep periods”) ; determining a total amount of time the individual experienced the atypical REM sleep stages during the sleep session (Figure 7: monitor rate of restless sleep signal patterns 700, [0065] “monitoring the number or rate of the restless sleep signal patterns”,) ; and in response to (i) the total number of atypical REM sleep stages satisfying a first threshold, causing an action to be performed, (ii) the total amount of time satisfying a second threshold, causing the action to be performed, or (iii) both (i) and (ii) ([0028] “The number of restless sleep intervals and the duration of the continuous sleep are both indicators of the overall sleep quality during a night, for example, and the processing circuitry may use both metrics in block 210 to obtain the sleep quality metric. In an embodiment, blocks 206 and 208 comprise using at least two thresholds in the detection of the restless sleep signal patterns (block 206) and the continuous sleep signal patterns (block 208). One of the thresholds is used for a quantity of the measurement data provided by the at least one sensor device, e.g. heart rate, acceleration or speed or another degree of motion, respiratory rate, bioimpedance, or a frequency of a signal pattern (in the heart rate variability, for example). Another one of the thresholds is a temporal threshold associated with time or duration.”, Figure 6: action performed is calculating overall sleep quality metric).
Although Martinmäki doesn’t explicitly state atypical REM sleep stages, it would have been obvious to one skilled in the art that one would extend the restless sleep intervals to indicate restless sleep intervals.
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shoeb, Kaji, and Martinmäki to incorporate the teachings of determining a total number of atypical REM sleep stages experienced by the individual during the sleep session; determining a total amount of time the individual experienced the atypical REM sleep stages during the sleep session and in response to (i) the total number of atypical REM sleep stages satisfying a first threshold, causing an action to be performed, (ii) the total amount of time satisfying a second threshold, causing the action to be performed, or (iii) both (i) and (ii), as these prior art references are directed to sleep management. One would be motivated to do this to determine the extent of the disruptive REM stages.
Shoeb, Kaji, and Martinmäki, alone or in combination, fails to explicitly teach an action to be performed.
Alternatively, Arrington teaches a system and method for managing disruptive sleep disorders (Abstract) wherein an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the sleep current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii) ([0061] “the sleep disorder management device 300, the device may be used to monitor a user's sleeping patterns to determine if the user is undergoing a sleep disorder episode and then deliver a physical stimulus to remedy the sleep disorder episode. In some implementations, the sleep disorder management device 300 is triggered by a continued, constant, and/or significant deviation from the user's normal sleeping patterns (e.g., by analyzing the measurable indicators that emanate from the user's body).”, [0072] discloses different types of alerts that are used to remedy the sleep disorder episode, [0083] “More specifically, in some embodiments, the sleep disorder management device 600 triggers the vibrator 606 after detecting continued, constant, and significant deviation from the user's typical REM sleep heart-beat rate ranges.”) .
Although Arrington does not explicitly state that the time spent of the occurrences passing a threshold, it would have been obvious to one skilled in the art to interpret the “continued, constant, and significant deviation” to be equivalent to the performing an action when the time spent is greater than a threshold.
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Shoeb, Kaji, and Martinmäki to incorporate the teachings of Arrington to have an action to be performed in response to the summary indicating that (i) the number of atypical REM sleep stages experienced by the individual during the sleep current sleep session satisfies a threshold number, (ii) a time spent in atypical REM sleep stages during the current sleep session is greater than a threshold time, or (iii) both (i) and (ii), as these prior art references are directed to sleep management. One would be motivated to do this to be able to distinguish between a sleep disorder episode and normal sleeping patterns and to protect/remedy a patient experiencing sleep disorders, ad recognized by Arrington ([0017] and Abstract).
Allowable Subject Matter
Claims 3, 8, and 84-86 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, in view of prior arts made of record.
Conclusion
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/ATTIYA SAYYADA HUSSAINI/Examiner, Art Unit 3792
/NIKETA PATEL/Supervisory Patent Examiner, Art Unit 3792