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 .
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-2, 4-6, 8-10, 14 & 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. (US 2020/0406035) in view of Dernebo et al. (US 2020/0197689).
Claim 1.
A wearable stimulation array comprising configurable electrodes contacting different portions of a user’s body…
E.G. Sharma discloses wearable sleeve 10 carrying spaced skin-contacting electrodes 12 with individually controlled stimulation channels ([0020], [0022]).
E.G. Dernebo further teaches selectively configuring each electrode electrical role [0031].
…a power source…
E.G. Dernebo discloses a master control unit having a power source supplying the garment’s sub-control units [0115].
…a memory storing a machine-learned movement model configured to determine actuation instructions likely to stimulate a set of movements…
E.G. Sharma discloses storage medium 24, pretrained movement classifiers, and determination of FES signals for identified movements ([0026], [0031]-[0032].
E.G. Dernebo further teaches an algorithm that learns from actual versus intended movements which stimulation signals best accomplish an intended movement and adjusts stimulation parameters accordingly [0215].
Incorporating this learned stimulation-response relationship into Sharma’s stored control software would provide the claimed model-based determination of actuation instructions.
…each actuation instructions specifying an electrical signal transmitted from a given electrode to a different electrode:
E.G. Dernebo teaches instructions specifying electrode combination and activation order, with current routed between selected positive and negative electrodes ([0131], [0138], [0140]).
…a controller coupled to the electrodes, memory, and power source and configured to stimulate movements by configuring current flow between electrodes…
E.G. Sharma discloses controller 20, processor 22, storage medium 24, and pulse generator 28 delivering movement-producing stimulation ([0022], [0026], [0032]).
E.G. Dernebo supplies the powered electrode-routing arrangement ([0115], [0131], [0140]).
…each electrode configured to operate as an anode or cathode depending on an operating mode…
E.G. Dernebo expressly teaches selectable anode, cathode, and disconnected states and switching electrode-pair polarity ([0031], [0043]).
It would have been obvious to one of ordinary skill to incorporate Dernebo’s response-based learning and powered, selectable electrode routing into Sharma’s wearable FES system to tailor stimulation to measured movement responses and permit electrode reuse across muscle targets ([0032], [0215]). Implementing the learning function in Sharma’s processor and memory and applying the resulting commands through Dernabo’s electrode-selection circuitry would predictably provide movement-responsive stimulation through selectable current paths. This applies known techniques to improve a similar stimulation device in the same way. KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417 (2007).
Claim 2.
…determining each movement based on one or more EMG data, IMU data, foot plantar pressure signals, or movement context.
E.G. Sharma identifies intended movements using EMG-derived features and trained movement classifiers ([0027]-[0031]). The EMG alternative satisfies the recited “one or more” limitation.
Claim 4.
…electrodes alternating between providing stimulation and measuring EMG data…
E.G. Sharma expressly discloses time-multiplexed sensing and stimulation and switching between EMG and FES modes on the same electrode ([0022], [0024]).
Claim 5.
…a movement representing a phase of a gait cycle…
E.G. Dernebo discloses real-time gait analysis and stimulation adjustment to improve walking [0206].
Claim 6.
…a plurality of controller-coupled sensors including one or more heart-rate, IMU, or pressure sensors…
E.G. Dernebo discloses multiple garment sensors, including pressure sensors, supplying measurements for stimulation control [0205], and sensors 1308, 1310, and 1312 providing movement and pressure-related feedback [0215]. The pressure-sensor alternative satisfies the recited sensor type.
Claim 9.
…an IMU sensor or foot-pressure sensor measuring movement:
E.G. Dernebo discloses stimulation socks measuring plantar pressure for gait analysis [0206].
…storing data characterizing the movement for application to the movement model or characterization of a movement profile…
E.G. Dernebo teaches saving movement-response information in a database to develop stimulation criteria [0215]. Applying that storage and learning technique to its plantar-pressure gait measurements would provide stored movement data for stimulation control.
Applying Dernebo’s disclosed movement-data storage and learning to its foot-pressure gait measurements would permit stimulation to be tailored using recorded walking responses, consistent with its stated gait-improvement purpose ([0206], [0215]).
Claim 10.
…creating a training set comprising measured movement data associated with respective actuation instructions:
E.G. Dernebo associates measured movement responses with the stimulation signals that produced them saves information for statistical stimulation criteria [0215].
E.G. Sharma expressly teaches labeled training data [0031].
…training the machine-learned movement model using the training set...
E.G. Sharma trains movement classifiers using labeled examples [0031], while Dernebo learns which stimulation signals accomplish intended movements [0215].
Organizing Dernebo’s associated stimulation-response observations as training examples, using Sharma’s disclosed training approach, would permit the stored model to learn stimulation instructions from measured results.
Claim 14.
…adjusting one or more of electrical-signal frequency, amplitude, or pulse width:
E.G. Dernebo expressly discloses adjusting stimulation strength, frequency and duration, as well as frequency and pulse length ([0046], [0215]).
Claim 17.
…the array coupled to a legging with electrodes contacting the leg:
E.G. Dernebo discloses leg modules 110/112 with connected electrodes as portions of the wearable garment ([0117], [0123]-[0124]; Fig. 4). These support the legging limitation under a construction encompassing its leg-enclosing garment modules.
Claim 18.
…the array coupled to a sock or shoe insole with electrodes contacting the foot…
E.G. Dernebo discloses sock module 1006/1008 carrying electrodes for foot stimulation ([0177], [0180]-[0182]; Fig. 21).
Claim 19.
Wearable stimulation array, configurable electrodes, power source, stored machine-learned movement model, actuation instructions, and controller with selectable electrode polarity: These limitations correspond to those mapped in claim 1; the explanations, citations, and combination rationale provided for claim 1 are incorporated herein.
…initializing the wearable stimulation array…
E.G. Dernebo teaches setting stimulation parameters, selecting a stimulation program, selecting a stimulation program, and initiating its operation [0175]. Under BRI encompassing configuration and startup, these operations teach the claimed initialization.
Claim 20.
Non-transitory computer-readable storage medium storing instructions executed by one or more processor:
E.G. Sharma discloses processor 22 executing software or firmware stored on non-transitory storage 24 [0026].
…processor-executed initialization of the recited wearable stimulation array…
E.G. The array limitations are mapped as explained for claim 1, and initialization is mapped as explained for claim 19. Implementing Dernebo’s configuration and startup operations [0175] through Sharma’s stored instructions [0026] would predictably enable the processor to configure and initiate the combined stimulation syste,
The claim 1 combination rationale is incorporated. Implementing the combined system’s configuration and startup through Sharma’s programmable controller would have been obvious to enable software-controlled operation, with each component performing its established function.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. in view of Dernebo et al., as applied to claims 1-2, 4-6, 8-10, 14 & 17-20 above, and further in view of De Sapio et al. (US 2017/0303849).
…receiving kinematic signals from a plurality of wearable sensors…
E.G. De Sapio discloses distributed sensors incorporated into a wearable suit, including IMU measurements used to determine joint angle variability and kinematic state ([0094], [0102]).
…using the kinematic signals and movement model to determine that the user is likely to perform movements…
E.G. De Sapio discloses an individualized musculoskeletal model that uses sensor information for state estimation and prediction and runs forward in time to predict elevated fall risk ([0098], [0103]). This supports model-based prediction of impeding movement if the claimed movements reasonably encompass the predicted loss-of-balance movement.
It would have been obvious before the effective filing date to incorporate De Sapio’s wearable kinematic sensing and predictive modeling into the Sharma-Dernebo system to anticipate instability and time corrective stimulation, predictably improving assisted-movement control.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. in view of Dernebo et al., as applied to claims 1-2, 4-6, 8-10, 14 & 17-20 above, and further in view of Chahine et al. (US 2020/0367823).
…the movement represents a phrase of a gait cycle…
E.G. Chahine discloses detecting step progression and selectively stimulating the dorsiflexors and calf muscles to assist foot lifting, with stimulation discontinued at step completion ([0063]-[0066]). Under BRI, the disclosed foot-lifting movement represents a phase of the gait cycle.
It would have been obvious before the effective filing data to implement Chahine’s gait-phase-responsive stimulation in the Sharma-Dernebo system to synchronize assistance with the portion of the gait cycle requiring muscle activation, predictably improving the timing of assisted movement.
Claim(s) 7-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sharma et al. in view of Dernebo et al., as applied to claims 1-2, 4-6, 8-10, 14 & 17-20 above, and further in view of Coleman et al. (US 2018/0015284).
…receiving sensor measurements and detecting the user is wearing the array…
E.G. Coleman discloses biological-feedback sensors incorporated into a wearable brace, including proximity/contact sensos that determine whether the brace is worn and electrical sensors that measure impedance to determine skin attachment [0192]. These measurements provide the claimed indication that the wearable device is worn.\
…determining fatigue and adjusting current based on fatigue…
E.G. Coleman discloses heart-rate sensors, including using heart-rate sensors in order to determine activity level during exercise or therapy and adjusting feedback based on fatigue ([0192]-[0193]).
It would have been obvious to one having ordinary skill in the art at the time the invention was made to incorporate Coleman’s sensor-based wear detection into the Sharma-Dernebo system to verify body attachment before stimulation, predictably improving reliable delivery of stimulation.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter: The prior art of record does not teach or suggest, in the claimed combinations, retraining the movement model based on neurotypical movement scoring, user approval that strengths or weakens movement-actuation association or user-selected electrode configuration.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Hamner et al. disclose wearable gait sensors, evaluation of deviations from desired gait parameters, and responsive electrical stimulation ([0088], [0140], [0160]), but do not disclose the particular feedback-based model-retraining relationships recited in claims 11-13.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICOLE F JOHNSON whose telephone number is (571)270-5040. The examiner can normally be reached Monday-Friday 8:00am-5:00pm EST.
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/NICOLE F JOHNSON/Primary Examiner, Art Unit 3796
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