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 .
Request for Continued Examination
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 22 December 2025 has been entered.
DETAILED ACTION
The present Office Action is in response to the Request for Continued Examination dated 22 December 2025.
In the RCE filed 22 December 2025:
Claims 1,4-10, 14-18 are amended
Claims 1-18, 20 are pending
Information Disclosure Statement
The Information Disclosure Statement(s) (lDS) submitted on 10 February 2026 is/are in compliance with the provisions of 37 CFR 1.97 and has/have been fully considered by the Examiner.
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 Examiner notes that the rejection will reference the translated documents (attached) corresponding to any foreign documents recited in the rejection.
Claims 1,5,8,10,14,17,20 is/are rejected under 35 U.S.C. 103(a) as being unpatentable over Cunnington et al (US Publication No. 20190374148) in view of Lyman et al (US Publication No. 20150309484) in view of PINDADO et al (US Publication No. 20200410179).
Regarding Claim 1
Cunnington teaches a method performed by an electronic device for managing physical exertion of an user, comprising:
obtaining user activity data from a plurality of devices including a Virtual Reality (VR) device [Cunnington at Para. 0054 teaches by way of example, controller and headset movements can be tracked using existing virtual reality technology that is widely available in existing virtual/augmented reality systems and devices];
determining, based on the user activity data, at least one physical strain exerted on at least one body part of the user in at least one VR interaction of a VR session using the VR device [Cunnington at Para. 0018 teaches embodiments of the present disclosure may take a dynamic and/or targeted approach to detecting physiological stress on a human body using a virtual reality environment. Body and/or device movements may be detected and monitored as a user interacts with the virtual reality environment, and then information about the detected and/or monitored movements may be used to infer one or more measures of physiological stress of the user's body. The obtained measure(s) of stress may then be mapped to one or more body parts to provide body-part-specific physiological information for the user. For example, by considering a reaction time of a user (e.g. the time taken for the user to move a particular body part in response to an instruction), a measure of physiological stress experienced by the user may be inferred. For instance, a slow reaction time (i.e. a large amount of time elapsing before the user moves in response to an instruction) may be indicative of high physiological stress or strain on the moving body part];
Cunnington does not teach identifying, based on the at least one physical strain, at least one device used by the user after the VR session involving the at least one body part of the user;
identifying a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device;
and controlling by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user.
Lyman teaches identifying, based on the at least one physical strain, at least one device used by the user after the VR session involving the at least one body part of the user [Lyman at Para. 0062 teaches the method 800 may additionally include establishing operation rules for future control of the one or more settings based on the detected patterns. One of the detected user activity patterns may include operating at least one electronic device. The method 800 may include storing information about past detected patterns, and comparing information about current detected patterns to the information about past detected patterns. Method 800 may include correlating the detected user patterns of behavior with date and time of day data, wherein adaptively updating the one or more settings of the home automation system is based at least in part on the date and time of day data];
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine strain of Cunnington with the device of Lyman with the motivation to improve ease of interaction between the user and the home.
Cunnington/Lyman do not teach identifying a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device;
and controlling by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user.
PINDADO teaches identifying a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device [PINDADO at Para. 0086 teaches in accordance with some embodiments of the invention, the system can be used to control high performance aircraft and military aircraft based on sensor data indicating an unsafe condition of the pilot. For example, where the sensor data indicates that the pilot (under the current flight trajectory) will be exposed or is being exposed to a high stress conduction (e.g., excessive G forces as a result of an aerial maneuver) that is likely to cause the pilot to black out or become injured, a control system within the aircraft can modify the flight path and or speed of the aircraft to reduce the stress and avoid harm to the pilot and the aircraft (indicating that pilot will be exposed to high stress interpreted as correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity; interpret to combine with strain data of Cunnington)];
and controlling by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user [PINDADO at Para. 0086 (interpret to combine with strain data of Cunnington)].
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine the references of Cunnington, Lyman with the settings of PINDADO with the motivation to reduce the stress and avoid harm to the pilot and the aircraft.
Regarding Claim 5
Cunnington/Lyman/PINDADO teach the method of claim 1,
Cunnington/Lyman/PINDADO further teach further comprising:
identifying the at least one device to perform the upcoming real-world activity using at least one of an upcoming real-world activity effort data, an upcoming schedule, and upcoming Internet of Things (IoT) automations [Lyman at Para. 0061 teaches at block 805, the method 800 includes continuously detecting at least one of user location patterns, user movement patterns, and user activity patterns with the home automation system. Block 810 of method 800 includes adaptively updating one or more settings of the home automation system based on the detected patterns.; Lyman at Para. 0062 (see Claim 1 for explanation)];
and obtaining at least one of the upcoming real-world activity effort data, the upcoming schedule, or the upcoming IoT automations from a database [Lyman at Para. 0053 teaches settings module 110-a may include more or fewer modules and capabilities than other embodiments such as, for example, a database module that includes storage of proposed settings, rules, past data, etc. that may be considered by analysis module 510 or other aspects of settings module 110-a.].
Regarding Claim 8
Cunnington/Lyman/PINDADO teach the method of claim 1,
Cunnington/Lyman/PINDADO further teach wherein the at least one operational setting is implemented by sending a notification to the user via a user device [PINDADO at Para. 0050 teaches as shown in FIG. 3, the control module 120 can be connected to and communicate with the communications module 130 and the analytics module 140. The communications module 130 facilitates the communication of sensor data and commands between the sensing device 110 and control module 120 and/or the analytics module 140. The communications module 130 also facilitates the communication of messages and/or commands between the control module and/or the analytics module 140 and one or more target devices 150 and/or one or more controllers 160].
Regarding Claim 10
Cunnington teaches an electronic device for managing physical exertion of an user, comprising:
at least one memory storing at least one instruction [Cunnington at Para. 0072 teaches the components of computer system 70 may include, but are not limited to, one or more processing arrangements, for example comprising processors or processing units 71, a system memory 74, and a bus 90 that couples various system components including system memory 74 to processing unit 71];
and at least one processor operatively connected to the at least one memory and configured to execute the at least one instruction to [Cunnington at Para. 0072]:
obtain user activity data from a plurality of devices including at least one of a Virtual Reality (VR) device [Cunnington at Para. 0054 (see Claim 1 for explanation)];
determine, based on the user activity data, at least one physical strain exerted on at least one body part of the user in at least one VR interaction of a VR session [Cunnington at Para. 0018 (see Claim 1 for explanation)];
Cunnington does not teach identify, based on the at least one physical strain, at least one device used by the user after the VR session involving the at least one body part of the user;
identify a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device;
and control, by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user.
Lyman teaches identify, based on the at least one physical strain, at least one device used by the user after the VR session involving the at least one body part of the user [Lyman at Para. 0062 (see Claim 1 for explanation)];
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine strain of Cunnington with the device of Lyman with the motivation to improve ease of interaction between the user and the home.
Cunnington/Lyman do not teach identify a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device;
and control, by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user.
PINDADO teaches identify a correlation between the at least one physical strain of the user and at least one physical effort required by the user to perform an upcoming real-world activity on the at least one device [PINDADO at Para. 0086 (see Claim 1 for explanation)];
and control, by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user [PINDADO at Para. 0086 (see Claim 1 for explanation)].
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine the references of Cunnington, Lyman with the settings of PINDADO with the motivation to reduce the stress and avoid harm to the pilot and the aircraft.
Regarding Claim 14
Claim(s) 14 is/are analogous to Claim(s) 5, thus Claim(s) 14 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 5.
Regarding Claim 17
Claim(s) 17 is/are analogous to Claim(s) 8, thus Claim(s) 17 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 8.
Regarding Claim 20
Cunnington/Lyman/PINDADO teach a non-transitory computer-readable recording medium having recorded thereon a program for executing the method of claim 1 on a computer [Cunnington at Para. 0079 teaches the present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention].
Claims 2-4,11-13,18 rejected under 35 U.S.C. 103(a) as being unpatentable over Cunnington, Lyman, PINDADO as applied to claim 1,10 above, and further in view of GALASSO et al (US Publication No. 20200357300).
Regarding Claim 2
Cunnington/Lyman/PINDADO teach the method of claim 1,
Cunnington/Lyman/PINDADO do not teach further comprising monitoring the at least one VR interaction based on at least one VR context data.
GALASSO teaches teach further comprising monitoring the at least one VR interaction based on at least one VR context data [GALASSO at Para. 0027 teaches System 100 may monitor any or all of the mountain biker's speed, location, elevation, distance traveled, power output and heart rate. System 100 may take measurements of any or all selected parameters at a user selected frequency or frequencies. Optionally, system 100 may calculate a rate of change of a given parameter and adjust a measurement and recording (sampling rate) frequency in response to the calculated rate of change. In one embodiment, system 100 increases measurement and recording frequency of a given parameter in response and proportion to a higher rate of change of that given parameter. Such increased frequency affords the increased data resolution required to represent the characteristic behavior of a parameter].
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine the references of Cunnington, Lyman, PINDADO with the interaction of GALASSO with the motivation to improve performance of an activity.
Regarding Claim 3
Cunnington/Lyman/PINDADO/GALASSO teach the method of claim 2,
Cunnington/Lyman/PINDADO/GALASSO further teach further comprising determining the at least one physical strain based on at least one of: the user activity data, the at least one VR context data, and at least one historical strain data of the user based on at least one of a machine learning model or indexing [Cunnington at Para. 0060 teaches further, use of predetermined measures of physiological stress may enable embodiments to provide a comparison of how the user is performing against a previous situation or a baseline “normal” measure. This may employ a comparison of the newly-obtained measure against the historical data. A result of the comparison may then be communicated to the user (e.g. “We notice that your left arm appears more stressed than what it is normally expected for a user of your height, weight, age, etc.”). Additionally, or alternatively, historical data regarding the user's physiological stress information may be to show progress or improvements for body parts. This may be useful for rehabilitation applications].
Regarding Claim 4
Cunnington/Lyman/PINDADO/GALASSO teach the method of claim 3,
Cunnington/Lyman/PINDADO/GALASSO further teach further comprising obtaining the at least one VR context data by collecting content related information from at least one of a streamed media and a type of a VR activity [GALASSO at Para. 0027 (see Claim 2 for explanation)].
Regarding Claim 11
Claim(s) 11is/are analogous to Claim(s) 2, thus Claim(s) 11is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 2.
Regarding Claim 12
Claim(s) 12 is/are analogous to Claim(s) 3, thus Claim(s) 12 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 3.
Regarding Claim 13
Claim(s) 13 is/are analogous to Claim(s) 4, thus Claim(s) 13 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 4.
Regarding Claim 18
Claim(s) 18 is/are analogous to Claim(s) 9, thus Claim(s) 18 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 9.
Claims 6-7, 15-16 rejected under 35 U.S.C. 103(a) as being unpatentable over Cunnington, Lyman, PINDADO, GALASSO as applied to claim 2, 11 above, and further in view of TOFF et al (US Publication No. 20180157344).
Regarding Claim 6
Cunnington/Lyman/PINDADO/GALASSO teach the method of claim 2,
Cunnington/Lyman/PINDADO/GALASSO do not teach wherein the at least one operational setting is implemented by predicting the at least one physical effort related to the upcoming real-world activity based on a termination of the VR session.
TOFF teaches wherein the at least one operational setting is implemented by predicting the at least one physical effort related to the upcoming real-world activity based on a termination of the VR session [TOFF at Para. 0029 teaches as shown in FIGS. 4D and 4E, when the user ends the virtual session, or when the user temporarily disengages from the virtual environment, the user may move the HMD 100 out of his line of sight, and/or may remove the HMD 100 from his head. This movement/removal of the HMD 100 may be considered a movement, or gesture, or action, associated with the end of a virtual session, which may be detected by the system (interpret to combine with physical effort data of GALASSO)].
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine the references of Cunnington/Lyman/PINDADO/GALASSO with the end of session of TOFF with the motivation to improve the user's experience.
Regarding Claim 7
Cunnington/Lyman/PINDADO/GALASSO teach the method of claim 6,
Cunnington/Lyman/PINDADO/GALASSO further teach wherein the predicting of the at least one physical effort comprises predicting the at least one physical effort for performing the upcoming real-world activity based on at least one of the upcoming real-world activity effort data, an upcoming schedule, or the upcoming IoT automations [PINDADO at Para. 0056 teaches in accordance with some embodiments, the raw sensor data or the processed sensor data can be further processed to extract specific features or characteristics of the signal like the dominant frequency, range, root mean square value, correlation coefficient, heart rate, respiration rate, cadence etc. The features can be further processed using one or more algorithms (e.g. decision tree, state machine, and/or linear/logistic regression) to detect or predict events (e.g. falls, activity type, seizure, tremor) or to detect or predict status (e.g., state of mind, mental condition and/or attitude) (interpret to combine with activity of Cunnington)].
Regarding Claim 15
Claim(s) 15 is/are analogous to Claim(s) 6, thus Claim(s) 15 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 6.
Regarding Claim 16
Claim(s) 16 is/are analogous to Claim(s) 7, thus Claim(s) 16 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 7.
Claim 9 rejected under 35 U.S.C. 103(a) as being unpatentable over Cunnington, Lyman, PINDADO as applied to claim 1,10 above, and further in view of HAVAS et al (US Publication No. 20200410179).
Regarding Claim 9
Cunnington/Lyman/PINDADO teach the method of claim 1,
Cunnington/Lyman/PINDADO do not teach wherein the at least one operational setting is implemented by delaying the upcoming real-world activity.
HAVAS teaches wherein the at least one operational setting is implemented by delaying the upcoming real-world activity [HAVAS at Para. 0107 teaches in one variation of the reminder flow method 70 in FIG. 6, even if the result at step 78 is YES, reminder needed, the user may, under certain circumstances delay the scheduled activity. Like a snooze button on an alarm clock, the reminder method 70 may be modified with such a “remind-me-later” input that stops or postpones the reminder alert signal (step 82) and instead schedules the actions of step 82 after the snooze or reminder period has passed].
It would have been prima facie obvious skill in the art, at the time of effective filing, to combine the references of Cunnington/Lyman/PINDADO with the delay of HAVAS with the motivation to improve drug adherence.
Response to Arguments
Rejection under 35 U.S.C. § 101
Regarding the rejection of Claim 1-18, 20, the Examiner has reconsidered the rejection in light of the 2019 Revised Patent Subject Matter Eligibility Guidance dated January 7, 2019 and withdraws the rejection. The claimed invention is subject matter eligible because the claims provide an improvement to other technology or technical field by “controlling by the electronic device via wireless communication, the at least one identified device to implement at least one operational setting to alter the at least one physical effort related to the upcoming real-world activity to mitigate the at least one physical strain of the user.”
Rejection under 35 U.S.C. § 102/103
Regarding the rejection of Claims 1-18, the Examiner has considered the Applicant’s arguments; however, these arguments are moot given the new grounds of rejection as afforded by the present RCE.
Conclusion
The prior art made of record and not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Sundaram et al (Foreign Publication WO-2019075185-A1) discloses devices, systems, and methods for monitoring musculoskeletal (MSK) health conditions of an individual.
Kinnunen et al (US Publication No. 20220110547) discloses methods, systems, and devices for providing guidance during rest and recovery.
Lin et al (US Publication No. 20180287812) discloses method for a home automation system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN C EDOUARD whose telephone number is (571)270-0107. The examiner can normally be reached M-F 730 - 430.
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/JONATHAN C EDOUARD/Examiner, Art Unit 3683
/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683
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