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 .
Priority
This application is a continuation of US Application no. 17/397,674, now US Patent no. 11,931,571 filed 8 August 2021.
Claim Rejections - 35 USC § 102
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 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, 4-7, 13, 14, 19, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hamilton et al. (US Publication no. 2013/0123568 – disclosed by Applicant).
In regard to claim 1, Hamilton et al. disclose a method comprising:
measuring movement stimulated by electrodes of a wearable stimulation array, wherein stimulation is determined using a model trained to identify electrical stimulation corresponding to respective movements (para 34, a control algorithm 12 considered to comprise the trained model will determine the appropriate signal pattern for the FES system to apply to the appropriate location in the nervous system thereby the appropriate muscle; para 55 further describes the algorithm as selecting, executing, and adjusting the appropriate FES profiles 320, wherein an FES profile is considered to comprise stimulation parameters and electrode combination appropriate for particular conditions of the patient; para 51, after applying stimulation according to the control algorithm, the work output is determined which is considered to comprise the act of measuring the stimulated movement);
comparing the measured stimulated movement to a predetermined movement representative of neurotypical movement (para 51; The work output is compared to a defined value which can be a target value or a value measured during a previous stimulation period), and
calibrating the wearable stimulation array by retraining the model based on the comparison (para 51-52, The amount of electrical energy coupled into the muscles by the stimulation signals is varied in response to the results of the comparison in order to maximize the amount of work output by the muscles during a treatment period. This is accomplished by adjusting the frequency and/or pulse width during stimulation treatment in response to the work output measured. For example, if it was desired to move a leg, the programmed microprocessor could produce hip movement by generating control signals for stimulation transducers which stimulate the iliacus, hamstring, and gluteal muscles. The microprocessor produces knee movement through generation of control signals for stimulation transducers which stimulate the quadriceps and hamstring muscles. Finally, the microprocessor produces ankle movement through generation of control signals for stimulation circuits which stimulate the gastrocnemius and tibialis muscle groups. As the hip, knee and ankle motion progresses, corresponding feedback signals are generated by sensors mounted on the body, and these feedback signals are applied to the microprocessor for closed-loop control of the stimulation control signals. The feedback obtained here to adjust and improve the stimulation is considered a calibration technique that ensures that the proper signal for achieving the desired leg movement is delivered to the target. Additionally, the feedback is considered to comprise retraining of the algorithm).
In regard to claim 4, the model/profile for FES in Hamilton et al. is enabled based on one or more EMG signals or a context in which the stimulated movement is to occur (para 28, 30 discuss use of EMG, and para 51 discuss context of which stimulated movement is to occur, e.g., moving a leg; para 15 suggests that the stimulation may also be used to assist with particular movements such as standing or walking).
In regard to claim 5, the model/profile for FES in Hamilton et al. is enabled based on a context in which the stimulated movement is to occur (para 35 contect referring to stimulating the trunk muscles, then leg muscles to facilitate particular positions; para 51 discuss context of which stimulated movement is to occur, e.g., moving a leg; para 15 suggests that the stimulation may also be used to assist with particular movements such as standing or walking).
In regard to claim 6, the model/profile for FES in Hamilton et al. is enabled based on one or more EMG signals (para 28, 30 discuss use of EMG).
In regard to claim 13, the wearable electrode array of Hamilton et al. provides both FES and EMG sensing, wherein the electrode are configured to alternate between providing stimulation and EMG sensing (para 49).
In regard to claim 14, the wearable electrode array of Hamilton et al. detects that the user is wearing the wearable stimulation array (para 52, such measurement is implies since Hamilton et al. teaches that the electrical stimulation signal is as effective as the contact between the electrode and user’s skin; Further, the sensors are considered to comprise obvious equivalents suitable for substitution to obtain this determination).
In regard to claims 19 and 20, Hamilton et al. wearable functional electrical stimulation (FES) system to aid a user with useful and controlled movements of limb (para 28 and 30). Hamilton et al. includes computer readable medium and microprocessor (para 13, 33, and 34) for storing and controlling a technique that carries out the following steps:
Hamilton et al. disclose a method comprising:
measuring movement stimulated by electrodes of a wearable stimulation array, wherein stimulation is determined using a model trained to identify electrical stimulation corresponding to respective movements (para 34, a control algorithm 12 considered to comprise the trained model will determine the appropriate signal pattern for the FES system to apply to the appropriate location in the nervous system thereby the appropriate muscle; para 55 further describes the algorithm as selecting, executing, and adjusting the appropriate FES profiles 320, wherein an FES profile is considered to comprise stimulation parameters and electrode combination appropriate for particular conditions of the patient; para 51, after applying stimulation according to the control algorithm, the work output is determined which is considered to comprise the act of measuring the stimulated movement);
comparing the measured stimulated movement to a predetermined movement representative of neurotypical movement (para 51; The work output is compared to a defined value which can be a target value or a value measured during a previous stimulation period), and
calibrating the wearable stimulation array by retraining the model based on the comparison (para 51-52, The amount of electrical energy coupled into the muscles by the stimulation signals is varied in response to the results of the comparison in order to maximize the amount of work output by the muscles during a treatment period. This is accomplished by adjusting the frequency and/or pulse width during stimulation treatment in response to the work output measured. For example, if it was desired to move a leg, the programmed microprocessor could produce hip movement by generating control signals for stimulation transducers which stimulate the iliacus, hamstring, and gluteal muscles. The microprocessor produces knee movement through generation of control signals for stimulation transducers which stimulate the quadriceps and hamstring muscles. Finally, the microprocessor produces ankle movement through generation of control signals for stimulation circuits which stimulate the gastrocnemius and tibialis muscle groups. As the hip, knee and ankle motion progresses, corresponding feedback signals are generated by sensors mounted on the body, and these feedback signals are applied to the microprocessor for closed-loop control of the stimulation control signals. The feedback obtained here to adjust and improve the stimulation is considered a calibration technique that ensures that the proper signal for achieving the desired leg movement is delivered to the target. Additionally, the feedback is considered to comprise retraining of the algorithm).
Claim(s) 2, 3, 8-10, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamilton et al. (US Publication no. 2013/0123568 – disclosed by Applicant) in view of DeSapio et al. (US Publication no. 2017/0303849 – disclosed by Applicant).
In regard to claims 2 and 3, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach creating a training set comprising measured movement data associated with respective actuation instruction, each actuation instruction specifying an electrical signal to be transmitted from a first set of the plurality of electrodes to a second set of the plurality of electrodes; and training the model using the training set, wherein the measured movement data is representative of neurotypical movement measured from a general population of users. DeSapio et al. describes a similar device as Hamilton et al. to stimulate movement particularly for gait intervention. DeSapio et al. provides FES based on a musculoskeletal model 414 run by an analytics module 402 on an embedded processor in order to help remediate gait (para 92-94). The musculoskeletal model 414 of DeSapio et al. is considered similar and equivalent to the FES profile described by Hamilton et al. DeSapio et al. teaches training set comprising measured movement data associated with respective actuation instruction, each actuation instruction specifying an electrical signal to be transmitted from a first set of the plurality of electrodes to a second set of the plurality of electrodes; and training the model using the training set, wherein the measured movement data is representative of neurotypical movement measured from a general population of users (para 98 and 100, DeSapio et al. obtains a generic model and applies a training/testing procedure to refine and personalize the model to the particular user in order to accurately judge deviations from optimum performance of the system). It is considered to have been obvious to one of ordinary skill in the art at the time of the invention to modify the systems described by Hamilton et al. to provide training data to retrain the model so that the model may be personalized to the user in order to provide accurate subject-specific movement estimation and prediction for optimum performance.
In regard to claim 8, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach comparing the measured movement to a predetermined movement representative of fatigue affecting the movement; and determining a level of fatigue of the measured movement based on the comparison, wherein the model is configured to enable the corresponding electrical signal based on the level of fatigue. DeSapio et al. is found to teach comparing the measured movement to a predetermined movement representative of fatigue affecting the movement; and determining a level of fatigue of the measured movement based on the comparison, wherein the model is configured to enable the corresponding electrical signal based on the level of fatigue (para 102). Modification of Hamilton et al. to determine the level of fatigue in the manner as claimed since DeSapio et al. teach that fatigue causes error in gait thereby affecting movement and requiring activation of stimulation therapy for correction.
In regard to claim 9, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach measuring the movement using one or more IMU sensor and storing data characterizing the measured movement to apply to the model to stimulate the movement or used to characterize a movement profile of the user. DeSapio et al. includes a plurality of distributed sensors including EMG, IMU, and ground force reaction sensors (para 95). Data from IMU sensors and/or ground force reaction sensors is measured and stored for characterizing the measured movement to apply to the model to stimulate the movement or used to characterize a movement profile of the user (para 96). It is considered to have been obvious to one of ordinary skill in the art at the time of the invention to modify the FES system of Hamilton et al. to include an IMU or ground force reaction sensor since DeSapio et al. teaches that the sensors are known to be useful in providing inertial characteristics and foot placement feedback to adjust stimulation.
In regard to claim 10, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach measuring forces from a user’s joints. DeSapio et al. teaches that the measured movement from the sensors includes measuring forces from the user’s joints such as joint torque (para 94). Modification of Hamilton et al. to determine forces of a user’s joints is obvious since DeSapio et al. teach that joint torque is indicative of fall risk which would require stimulation activation to prevent a fall.
In regard to claim 15, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach obtaining movements representing a phase of a gait cycle. DeSapio et al. teaches obtaining a phase of a gait cycle (para 105 and 108). Modification of Hamilton et al. to determine a gait cycle is considered to have been obvious since DeSapio et al. teaches that doing so provides effective feedback to guide stimulation to stabilize the subject.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamilton et al. (US Publication no. 2013/0123568 – disclosed by Applicant) in view of Choi et al. (EP 3 009 068).
In regard to claim 7, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach measuring an EMG signal using one or more of the electrodes; determining a frequency response of the EMG signal; and determining a level of fatigue based on the frequency response, wherein a lower frequency response is associated with a higher level of fatigue. Hamilton et al. does teach that a sensor for detecting muscle fatigue is incorporated within, Hamilton et al. is silent with respect to the type of sensor. Choi et al. expressly teaches that a frequency response of the EMG signal extracted via a Fourier Transform indicates a point in time when muscle fatigue occurs (para 49). It is considered to have been obvious to one of ordinary skill in the art at the time of the invention to measure fatigue of the muscle from the frequency response of the EMG signal since this is expressly taught by Choi et al. The modification would include the application of a known technique to an known device capable of obtaining EMG signals to yield a predictable result.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamilton et al. (US Publication no. 2013/0123568 – disclosed by Applicant) in view of Peckham et al. (US Patent no. 5,167,229 – disclosed by Applicant).
In regard to claim 12, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach determining a plurality of electrical signals by changing one or more of a frequency, an amplitude, or a pulse width of the corresponding electrical signal; sequentially enabling the plurality of electrical signals through permutations of pairs of the plurality of electrodes; pausing between successive enabling of electrical signals of the plurality of electrical signals to allow the user to provide feedback of the movement stimulated by an enabled electrical signal; and calibrating the wearable stimulation array by retraining the accessed model based on the received feedback of the movement stimulated by the plurality of electrical signals. Peckham et al. describes a wearable FES system like Hamilton et al. Peckham et al. teaches that the operator may specify stimulation channels through user input, and the stimulation channels may be organized to output sequentially (col 14 lines 8-22). Additionally, stimulation parameters such as pulse width, current amplitudes, and interpulse intervals can be controlled independently for each electrode (col 13 lines 52-57). Modification of Hamilton et al. in this manner is considered obvious to one of ordinary skill in the art since the fixed sequential sequencing provides organization of electrodes in groups to simplify testing.
Claim(s) 11, 16, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamilton et al. (US Publication no. 2013/0123568 – disclosed by Applicant) in view of Schwarz et al. (US Publication no. 2018/0036531 – disclosed by Applicant).
In regard to claim 11, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach measuring non-stimulated movement using sensors of the wearable stimulation array, the non-stimulated movement representative of a user performing a given movement without stimulation creating, using the non-stimulated movement and the measured stimulated movement, a movement profile of the user. Schwarz et al. describe in a device similar to Hamilton et al. (para 75). Schwarz et al. teach the step for measuring non-stimulated movement using sensors of the wearable stimulation array (i.e., a predetermined movement), the non-stimulated movement representative of a user performing a given movement without stimulation creating, using the non-stimulated movement and the measured stimulated movement, a movement profile of the user (para 148-150). This allows an ideal sequence of movements to be stored in the system as a threshold. A comparison of the actual sequence of movements recorded by means of the sensor with the sequence of predetermined movements as threshold can generate a control signal if the actual sequence of movements of the user and the predetermined sequence of movements deviates too strongly from the predetermined sequence of movements. Modification of Hamilton et al. to measure non-stimulated movement is considered to have been obvious to one of ordinary skill in the art in view of the teachings of Schwarz et al. that demonstrate that measurement of predetermined movements form a threshold so that one or more control pulse parameters may be modified to assist a user to carry out precisely this sequence of movements.
In regard to claim 16, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach wherein the wearable stimulation array comprises a plurality of sensors configured to measure one or more of galvanic skin response, heart rate, or respiration rate. Schwarz et al. describe in a device similar to Hamilton et al. (para 75). The system includes a plurality of sensors configured to measure one or more of galvanic skin response, heart rate, or respiration rate (para 208). Modification of Hamilton et al. to include one of a galvanic skin response, heart rate, or respiration rate as shown in Schwarz et al. because Hamilton et al. teach that FES is useful for controlling blood pressure, heart rate, and.or respiration rate (para 7 and 67) wherein such as sensor would provide feedback for adaptive stimulation for those conditions.
In regard to claim 18, Hamilton et al. is considered to substantially suggest the invention as claimed, however does not teach measuring non-stimulated movement using sensors of the wearable stimulation array, the non-stimulated movement representative of a user performing a given movement without stimulation; comparing the non-stimulated movement to the predetermined movement representative of neurotypical movement; and retraining the model further based on the comparison of the non-stimulated movement to the predetermined movement. Schwarz et al. describe in a device similar to Hamilton et al. (para 75). Schwarz et al. teach the step for measuring non-stimulated movement using sensors of the wearable stimulation array (i.e., a predetermined movement), the non-stimulated movement representative of a user performing a given movement without stimulation creating, using the non-stimulated movement and the measured stimulated movement, a movement profile of the user (para 148-150). This allows an ideal sequence of movements to be stored in the system as a threshold. A comparison of the actual sequence of movements recorded by means of the sensor with the sequence of predetermined movements as threshold can generate a control signal if the actual sequence of movements of the user and the predetermined sequence of movements deviates too strongly from the predetermined sequence of movements. Modification of Hamilton et al. to measure non-stimulated movement is considered to have been obvious to one of ordinary skill in the art in view of the teachings of Schwarz et al. that demonstrate that measurement of predetermined movements form a threshold so that one or more control pulse parameters may be modified to assist a user to carry out precisely this sequence of movements.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11,931,674. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the ‘674 patent recite limitations that anticipate the present invention. For instance, the conflict between present claim 1 and claim of the ‘674 patent are exhibited below.
Claim 1 of the present invention:
A method comprising:
measuring movement stimulated by electrodes of a wearable stimulation array, wherein stimulation is determined using a model trained to identify electrical stimulation corresponding to respective movements; comparing the measured stimulated movement to a predetermined movement representative of neurotypical movement; and calibrating the wearable stimulation array by retraining the model based on the comparison.
Claim 1 of the ‘674 patent:
A method comprising:
initializing a wearable stimulation array comprising a plurality of electrodes;
accessing a model configured to, for each of a plurality of movements, enable a corresponding electrical signal from a first set of the plurality of electrodes to a second set of the plurality of electrodes to stimulate the movement by [[the]] a user;
in response to the use of the accessed model to stimulate a movement of the plurality of movements by the user using the wearable stimulation array, receiving feedback from the user indicating a measure of approval of the stimulated movement;
calibrating the wearable stimulation array by retraining the accessed model based on the received feedback to change, for at least the stimulated movement of the plurality of movements, one or more of the corresponding electrical signal, the first set of electrodes, and the second set of electrodes;
measuring the stimulated movement using one or more of inertial measurement unit (IMU) sensors or foot pressure sensors of the wearable stimulation array;
comparing the measured stimulated movement to a predetermined movement representative of neurotypical movement; and scoring the measured movement based on one or more of the received feedback or the comparison, wherein the accessed model is retrained further based on the scoring.
The present invention is considered to recite the same steps for measuring a stimulated movement, comparing the measured movement and a predetermined movement, then retraining the model based on the comparison. The retraining of the ‘674 is considered the same as calibration step of present claim 1. For these reasons, it is considered that the claims of the ‘674 patent anticipate the present claim. Present claims 19 and 20 are also in conflict in view of claims 19 and 20 of the ‘674 patent. Additional overlap is considered exhibited between dependent claims 2-18 of the present invention in view of dependent claims 2-18 of the ‘674 patent.
Allowable Subject Matter
Claim 17 is 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. The prior art contains insufficient teaching to warrant modification of the teachings of the cited prior art.
With regard to claim 17, the prior art is found deficient with respect to the pulse width ratio between the electrodes for stimulating movement.
Conclusion
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/BRIAN T GEDEON/Primary Examiner, Art Unit 3796 27 May 2026
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