Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on11/19/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Election/Restrictions
Applicant’s election with traverse of species (3) drawn to claims 1-18 and 20, and withdrawn claim 19 directed to non-elected species in the reply filed on 01/06/2026 is acknowledged.
Applicant's arguments regarding no distinct species and Examiner failed to demonstrate a serious search burden have been fully considered but they are not persuasive, because the species are directed to different embodiments using distinct wearable devices to monitor physical activity. Independent claims 1 and 20 does not necessarily require the wearable device to be wrist-wearable device, as required by independent claim 19.
Claim Objections
Claim 5 is objected to because of the following informalities: the phrase “the other” in line 2 should be amended to read –the another--. Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8, 13, 15-17 and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Matsuura et al (US 2021/0084999).
As to claims 1 and 20, Matsuura teaches a method for determining an adaptive adjustment to a physical activity being performed by a user wearing a wearable electronic device (wearable garment/ platform in fig.1-2 and 7, abstract, the wearable garment/platform having controller 14 is in communication with at least one effector 16, for providing proprioceptive feedback and/or adjusting a physical parameter of the garment such as resistance to movement, compression or other parameter that will be perceptible to the wearpar.23), and a non-transitory computer-readable storage medium, comprising instructions that, when executed by a computing device (Controller 14 is in communication with at least one effector 16, for providing proprioceptive feedback and/or adjusting a physical parameter of the garment such as resistance to movement, compression or other parameter that will be perceptible to the wear, par.23), cause the computing device to perform operations for:
in conjunction with detecting, using one or more sensors located at the wearable electronic device (sensors 12 connected to controller 14, wherein sensors may be incorporated in a permanent manner into the fabric of the form-fitting interactive garment itself or in a detachable manner, par.23-25 and par.43), that the user is performing the physical activity at a particular activity rate (visual, audio or other tactile feedback can be provided to the wearer to signal to the wearer that they should adjust their posture, or adjust a performance parameter such as increase or decrease stride length or repetition rate, realignment of stride, modify arm swing such as bring the elbows in or other streamlining adjustment, or adjust their spine (core) such as to bring it into alignment with a preset data set, or initiate other motion or body position correction, par.26, least one or two or more on board sensors can be used to detect the signals of the user's performance such as speed, torque, force, training time etc., and/or the signals of the user's physical conditions such as oxygen level, breathing rate and heart rate, par.75, method steps 208-212, par.83-85, fig.6):
detecting, using a neuromuscular-signal sensor located at the wearable electronic device, a level of exertion of the user (using electromyography/EMG sensors to determine to measure muscle exertion intensity, par.24 and par.31-32 and par.43); and
based on a determination that the level of exertion is different than a baseline level of exertion by at least a threshold amount (comparing the exertion level of individual muscles (e.g., obtained from the muscle activation data from the sensors 104A-104C) with the reference exertion level of those muscles, par.83-84, fig.6)., determining an adjustment to the particular activity rate while the user is performing the physical activity (visual, audio or other tactile feedback can be provided to the wearer to signal to the wearer that they should adjust their posture, or adjust a performance parameter such as increase or decrease stride length or repetition rate, realignment of stride, modify arm swing such as bring the elbows in or other streamlining adjustment, or adjust their spine (core) such as to bring it into alignment with a preset data set, or initiate other motion or body position correction, par.26, at least one or two or more on board sensors can be used to detect the signals of the user's performance such as speed, torque, force, training time etc., and/or the signals of the user's physical conditions such as oxygen level, breathing rate and heart rate, par.75, method steps 208-212, par.83-85, feedback at the stage 210 may also include recommendations in the form of audio, visual (e.g., lights, text) or proprioceptic (e.g., push more with the left arm; increase or decrease stride length; increase or decrease stride rate; adjust body position) or status or warning (e.g., move elbows medially; crossing anaerobic threshold; body temperature exceeding or falling below a preset alarm limit; pulse exceeding a preset alarm limit; hydration status falling below a preset alarm limit; etc.) or other coaching information while the human subject is performing the exercise, par.88, fig.6).
As to claim 2, Matsuura teaches the method, further comprising: before determining that the level of exertion is different than the baseline level of exertion by at least the threshold amount: detecting, using the neuromuscular-signal sensor, another level of exertion, separately from the detecting of the level of exertion; and based on determining that the other level of exertion is different than the baseline level of exertion by at least another threshold amount, causing a notification to be provided to the user (obtaining reference data, par.78, continues monitoring of the subject’s performance, par.26, par.75, obtaining additional or accumulated data, par.83-85 and par.88, fig.6).
As to claim 3, Matsuura teaches the method, wherein: the notification is caused to be provided at an electronic workout device (sensor reading provides the feedback to the control system from MR damper unit, incorporated here by reference, par.76 and par.88); the notification includes a selectable user interface element; and in response to the user selecting the selectable user interface element, the electronic workout device is caused to adjust the activity rate (the device may be programmed so that the resistive force of the MR unit is adjusted in response to the level of a sensed value or a degree of deviation of the sensed value from a predetermined target value. The device may also allow for the user to modify various settings, such as the level of difficulty, purpose of exercise (e.g. strength training, rehabilitation, etc.), and other variables that will allow the user to customize the manner in which the MR damper responds to their physical activity, par.76, result of the analysis at the stage 208 may be immediately communicated to the user at a stage 210 via a display 112a of device 112 (e.g., a smartphone, table, pad, eyeglasses 182, etc.) or an auxiliary feedback device such as devices 114 including any of the effectors disclosed elsewhere, providing recommendations to adjust or change performance, par.88).
As to claim 4, Matsuura teaches the method, further comprising: after determining that the other level of exertion is different than the baseline level of exertion by at least the other threshold amount, and before determining that the level of exertion is different than the baseline level of exertion by at least the threshold amount: detecting, using the neuromuscular-signal sensor of the one or more sensors located at the wearable electronic device, yet another level of exertion, separately from the detecting of the level of exertion and the detecting of the other level of exertion; and based on determining that the yet another level of exertion is different than the baseline level of exertion by yet another threshold amount, determining another adjustment to the particular activity rate, distinct from the adjustment (continues monitoring of the subject’s performance, par.26, par.75, obtaining additional or accumulated data, par.83-85 and par.88, fig.6, obtaining reference data, par.78)(Examiner respectfully notes that every monitoring at a different time point requires new measuring/analysis and recommendations).
As to claim 5, Matsuura teaches the method, wherein: the other adjustment to the particular activity rate is a decrease in the activity rate; and the adjustment to the particular activity rate is a cessation of the physical activity (obtaining additional or accumulated data, par.83-85, data analysis provides recommendation to adjust activity, such as, decrease stride length or decrease stride rate, par.88).
As to claim 6, Matsuura teaches the method, wherein: the user is performing the physical activity at an electronic workout device; and the determining that the level of exertion is different than the baseline level of exertion is further based on data from the electronic workout device (the device may be programmed so that the resistive force of the MR unit is adjusted in response to the level of a sensed value or a degree of deviation of the sensed value from a predetermined target value. The device may also allow for the user to modify various settings, such as the level of difficulty, purpose of exercise (e.g. strength training, rehabilitation, etc.), and other variables that will allow the user to customize the manner in which the MR damper responds to their physical activity, par.76, result of the analysis at the stage 208 may be immediately communicated to the user at a stage 210 via a display 112a of device 112 (e.g., a smartphone, table, pad, eyeglasses 182, etc.) or an auxiliary feedback device such as devices 114 including any of the effectors disclosed elsewhere, providing recommendations to adjust or change performance, par.88).
As to claim 7, Matsuura teaches the method, wherein the data from the electronic workout device is generated by one or more of (i) a photoplethysmography (PPG) sensing device, (ii) an electrocardiogram (ECG) sensing device, and (iii) a gyroscope sensor (gyroscopes, par.24, par.43 and par.53).
As to claim 8, Matsuura teaches the method, wherein: the one or more sensors at the wearable electronic device includes an inertial measurement unit (IMU) sensor (accelerometers and gyroscopes, par.24, par.43 and par.53); and the determination that the level of exertion is different than the baseline level of exertion is further based on data from the IMU sensor (adjusting activity based on measured data from sensors, par.24-26, par.83-85 and par.88).
As to claim 13, Matsuura teaches the method, wherein: the activity rate is a first activity rate; the level of exertion is lower than the baseline level of exertion by the threshold amount; and automatically increasing the first activity rate to a second activity rate that is higher than the first activity rate (feedback at the stage 210 may also include recommendations to increase or decrease stride length; increase or decrease stride rate; adjust body position) or status or warning (e.g., move elbows medially; crossing anaerobic threshold, par.26 and par.88).
As to claim 15, Matsuura teaches the method, wherein: the user is wearing a head-wearable electronic device (eyeglasses 182, and head set 180, par.88-90, fig.2); the head-wearable electronic device is presenting a user interface to the user, the user interface corresponding to an interactive workout; and based on the determination that the level of exertion is different than the baseline level of exertion by the threshold amount, the adjustment to the physical activity includes causing an adjustment to the user interface presented by the head-wearable electronic device (feedback at the stage 210 may also include recommendations in the form of audio, visual (e.g., lights, text) or proprioceptic (e.g., push more with the left arm; increase or decrease stride length; increase or decrease stride rate; adjust body position) or status or warning (e.g., move elbows medially; crossing anaerobic threshold; body temperature exceeding or falling below a preset alarm limit, par.88).
As to claim 16, Matsuura teaches the method, wherein the determination that the level of exertion is different than the baseline level of exertion by the threshold amount is further based on a number of identified repetitions of the physical activity that the user has performed at the activity rate (analysis may include, alternatively or additionally, comparing the number of exertion repetitions in a set (obtained from the muscle activation data from the sensors 104A-104C) with the reference exertion repetitions for those muscles, par.84, feedback at the stage 210 may, for example, include a representation of the body and visually depict the muscles being exerted, along with a color gradient or an overlay with relative exertion or other data depiction scheme to communicate the intensity level and/or duration and/or number of repetitions associated with each muscle, par.88).
As to claim 17, Matsuura teaches the method, wherein the determination that the level of exertion is different than the baseline level of exertion by the threshold amount is further based on a number of identified repetitions that the user has performed of another physical activity, distinct from the physical activity currently being performed by the user (analysis may include, alternatively or additionally, comparing the number of exertion repetitions in a set (obtained from the muscle activation data from the sensors 104A-104C) with the reference exertion repetitions for those muscles, par.84, recommendations recommends performing different type of activity, such as, push more with the left arm; increase or decrease stride length; increase or decrease stride rate; adjust body position) or status or warning (e.g., move elbows medially; crossing anaerobic threshold, par.88).
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.
Claim(s) 9-12, 14 and 18 is/are rejected under 35 U.S.C. 103 as being obvious over Matsuura et al (US 2021/0084999), in view of Huijbregts et al (US 2019/0183412).
As to claims 9-12 and 18, Matsuura teaches using algorithms to calibrate the measured signal (par.33 and par.39), but failed to explicitly teach applying a first weighting to data from the neuromuscular-signal sensor; and applying a second weighting to the data from the IMU sensor, wherein the first weighting and the second weighting are based on a calibration performed by the user before performing the physical activity at the activity rate.
However, Huijbregts teaches an analogous activity monitoring system (abstract, fig.1-3), wherein the determination that the level of exertion is different than the baseline level of exertion further comprises: applying a first weighting to data from the neuromuscular-signal sensor; and applying a second weighting to the data from the IMU sensor, wherein the first weighting and the second weighting are based on a calibration performed by the user before performing the physical activity at the activity rate, and based on a type of physical activity being performed, wherein: the first weighting is higher than the second weighting in accordance with a determination that the neuromuscular-signal sensor is configured to sense a primary muscle group associated with the physical activity (the fatigue level determination unit is adapted to provide the fatigue level based on a weighted sum of differences between each set of corresponding parameters among the reference exercise state parameter set and the exercise state parameter set, par.51-55), and wherein: the threshold amount is based on a plurality of contextual criterion associated with the user; and the threshold amount is determined based on inputting one or more of the plurality of contextual criterion into a machine-learning model (the fatigue level determination unit is adapted to process the past exercise states of the subject with machine learning algorithms,par.51-55).
Since applying weight to measured signals to determine fatigue level is well-known in the art, so it would have been obvious to one having an ordinary skill in the art before the filing date of the invention to apply weight to measured signals using machine-learning model in Matsuura’s invention, as taught by Huijbregts’ invention, to provide more accurate and reliable data to the user, as taught by Huijbregts’ invention (par.51-55).
As to claim 14, Matsuura teaches adjusting activity performance to prevent injury (par.41), but failed to explicitly teach the level of exertion is higher than the baseline level of exertion by the threshold amount; and the adjusting causes an electronic workout device to stop operations causing the physical activity.
However, Huijbregts’ teaches the user notification unit notifies the user upon reaching the fatigue level threshold such that the subject can stop exercising to achieve the most beneficial exercise effect, without suffering from long recovery or muscle pain, or the like (par.63, par.86 and par.108). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to recommend stopping the exercise/activity and/or stop exercising on a device in Matsuura’s invention, as taught by Huijbregts’ invention, to prevent injury or muscle pain (par.86 and par.108).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAY A ABOUELELA whose telephone number is (571)270-7917. The examiner can normally be reached 8-5.
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/MAY A ABOUELELA/Primary Examiner, Art Unit 3791