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 Arguments
Applicant’s arguments with respect to claims 121-140 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.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 121-140 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claims 121, 125 and 129 recite a “learning algorithm. The specification has not sufficiently described what constitutes a “learning algorithm” or an “aggregation learning algorithm” or how the algorithm is designed or trained.
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.
Claims 121-137 and 140 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Whiting et al. (US 2018/0235537 A1).
As to claim 121, Whiting et al. discloses a system for transcutaneously stimulating one or more peripheral nerves of a user ([0062]), the system comprising: a wearable neurostimulation device ([0062-0063]) comprising one or more electrodes ([0063-0065]) configured to generate electric stimulation signals based on therapy parameters ([0067, 0070]), the therapy parameters being determined by an aggregation learning algorithm ([0119, 0133]), the aggregation learning algorithm predicting a plurality of outcomes for the user based on a plurality of predefined profiles ([0119, 0133]), the plurality of predefined profiles being based on features extracted from data for a plurality of users ([0088, 0131, 0133]); one or more sensors ([0078]) configured to detect physiological data, wherein the one or more sensors are operably connected to the wearable neurostimulation device ([0078]); and one or more hardware processors configured to: perform a therapy session with the therapy parameters (Abstract; [0067, 0070]); measure physiological data from the one or more sensors during the therapy session, wherein the physiological data includes one or more of heart rate, blood glucose, blood pressure, respiration rate, body temperature, blood volume, sound pressure, photoplethysmography, electroencephalogram, electrocardiogram, blood oxygen saturation, and/or skin conductance data ([0042, 0078]); adjust the therapy parameters based on the measured physiological data from the therapy session ([0042, 0044, 0073]); optimize the adjusted therapy parameters by a learning algorithm based on an individual database, the learning algorithm predicting a modified outcome based on the individual database which includes an aggregation of physiological data and satisfaction data from multiple therapy sessions for the user ([0112, 0114-0117] Figure 7); and perform another therapy session with the optimized therapy parameters (Figure 7).
As to claim 122, Whiting et al. discloses the physiological data includes respiration rate and heart rate ([0056]). The functional language and introductory statement of intended use of claim122 has been carefully considered but are not considered to impart any further structural limitations over the prior art. Since Whiting et al. utilizes therapy parameters as claimed by the Applicant, Whiting et al. is therefore capable of being used to treat depression. In addition nothing prevents Whiting et al. from treating depression. Therefore, the device of Whiting et al. is therefore capable of being used to treat depression.
As to claim 123, Whiting et al. discloses the one or more sensors are further configured to detect sleep patterns and activity level of the user ([0056]).
As to claim 124, the functional language and introductory statement of intended use of claim122 has been carefully considered but are not considered to impart any further structural limitations over the prior art. Since Whiting et al. utilizes therapy parameters as claimed by the Applicant, Whiting et al. is therefore capable of being used to treat migraine or Lyme disease. In addition nothing prevents Whiting et al. from treating migraine or Lyme disease. Therefore, the device of Whiting et al. is therefore capable of being used to treat migraine or Lyme disease.
As to claim 125, Whiting et al. discloses a system for transcutaneously stimulating one or more peripheral nerves of a user ([0062]) with a wearable neurostimulation device ([0062-0063]) comprising one or more electrodes ([0063-0065]) configured to generate electric stimulation signals based on therapy parameters ([0067, 0070]), one or more sensors ([0078]) configured to detect physiological data, wherein the one or more sensors are operably connected to the wearable neurostimulation device ([0078]); and one or more hardware processors configured to: perform a therapy session with the therapy parameters (Abstract; [0067, 0070]); measure physiological data from the one or more sensors during the therapy session, wherein the physiological data includes one or more of heart rate, blood glucose, blood pressure, respiration rate, body temperature, blood volume, sound pressure, photoplethysmography, electroencephalogram, electrocardiogram, blood oxygen saturation, and/or skin conductance data ([0042, 0078]); provide the set of therapy parameters, the physiological data, and the user satisfaction data to a learning algorithm ([0042, 0044, 0073, 0119, 0133]); receive optimized therapy parameters from the learning algorithm, the learning algorithm predicting a modified outcome based on an individual database which includes an aggregation of physiological data and satisfaction data from multiple therapy sessions for the user ([0112, 0114-0117] Figure 7); and perform another therapy session with the optimized therapy parameters, wherein the neurostimulation device is a wearable transcutaneous device (Figure 7).
As to claim 126, Whiting et al. discloses the physiological data includes respiration rate and heart rate ([0056]). The functional language and introductory statement of intended use of claim122 has been carefully considered but are not considered to impart any further structural limitations over the prior art. Since Whiting et al. utilizes therapy parameters as claimed by the Applicant, Whiting et al. is therefore capable of being used to treat depression. In addition nothing prevents Whiting et al. from treating depression. Therefore, the device of Whiting et al. is therefore capable of being used to treat depression.
As to claim 127, Whiting et al. discloses the one or more sensors are further configured to detect sleep patterns and activity level of the user ([0056]).
As to claim 128, the functional language and introductory statement of intended use of claim122 has been carefully considered but are not considered to impart any further structural limitations over the prior art. Since Whiting et al. utilizes therapy parameters as claimed by the Applicant, Whiting et al. is therefore capable of being used to treat migraine or Lyme disease. In addition nothing prevents Whiting et al. from treating migraine or Lyme disease. Therefore, the device of Whiting et al. is therefore capable of being used to treat migraine or Lyme disease.
As to claim 129, Whiting et al. discloses a system for transcutaneously stimulating one or more peripheral nerves of a user ([0062]), the system comprising: a wearable neurostimulation device ([0062-0063]) comprising one or more electrodes ([0063-0065]) configured to generate electric stimulation signals based on therapy parameters ([0067, 0070]), the therapy parameters being determined by an aggregation learning algorithm ([0119, 0133]), the aggregation learning algorithm predicting a plurality of outcomes for the user based on a plurality of predefined profiles ([0119, 0133]), the plurality of predefined profiles being based on features extracted from data for a plurality of users ([0088, 0131, 0133]); one or more sensors configured to detect motion data ([0015, 0080, 0145]), wherein the one or more sensors are operably connected to the wearable neurostimulation device ([0078]); and one or more hardware processors configured to: perform a therapy session with the therapy parameters (Abstract; [0067, 0070]); measure kinematic data including data from the detected motion signals during the therapy session ([0080, 0145]), wherein the data includes tremor data (since Whiting et al. senses patient movement/body position, Whiting et al. would necessarily sense tremor data since tremor involves movement/body position of the patient); adjust the therapy parameters based on measured data from the detected motion signals during the therapy session (Figure 7); optimize the adjusted therapy parameters by a learning algorithm based on an individual database ([0112, 0114-0117] Figure 7), the learning algorithm predicting a modified outcome based on the individual database which includes an aggregation of kinematic data and satisfaction data from multiple therapy sessions for the user ([0112, 0114-0117, 0145] Figure 7); and perform another therapy session with the optimized therapy parameters (Figure 7).
As to claim 130, Whiting et al. discloses the features extracted from the data include test kinematic data ([0080, 0130, 0133, 0145]).
As to claim 131, Whiting et al. discloses the features extracted from the data include satisfaction data (Figure 4).
As to claim 132, Whiting et al. discloses the therapy parameters are based at least in part on a predetermined decision tree (Figures 4 and 7).
As to claim 133, Whiting et al. discloses the therapy parameters are based at least in part on one or more user profiles ([0088, 0131, 0133]).
As to claim 134, Whiting et al. discloses the kinematic data is collected from a sensor onboard the neurostimulation device ([0078]).
As to claim 135, Whiting et al. discloses the kinematic data includes at least one of accelerometer data and gyroscope data ([0015, 0078, 0080, 0145]).
As to claim 136, Whiting et al. discloses the features extracted from the data for the plurality of users include one or more of geospatial data, temporal data, disease, patient attributes or characteristics, or neurostimulation device characteristics associated with the extracted features ([0131, 0133]).
As to claim 137, Whiting et al. discloses the individual database includes at least one of: (i) kinematic data accumulated over multiple days and (ii) satisfaction data accumulated over multiple days ([0133]).
As to claim 140, Whiting et al. discloses the neurostimulation device includes a stimulator supporting at least one of the one or more hardware processors and a detachable band supporting the one or more electrodes (Figure 1).
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 factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 138-139 are rejected under 35 U.S.C. 103 as being unpatentable over Whiting et al. (US 2018/0235537 A1).
As to claim 138, Whiting et al. discloses the invention substantially as claimed but does not explicitly disclose the neurostimulation device is configured to be worn on at least one of: a wrist, a leg, and an ear. It would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the location the of the wearable device to have components such as sensors that engage with additional body parts, such as wrist, leg or ear, in order to provide the predictable results of modifying the treatment to meet specific patient therapeutic needs are requirements. Furthermore, it has been held that rearranging parts of an invention involves only routine skill in the art. In re Japikse, 86 USPQ 70 (see MPEP 2144.04)
As to claim 139, Whiting et al. discloses the invention substantially as claimed but does not explicitly disclose the one or more peripheral nerves includes at least one of a median, radial, ulnar, sural, femoral, peroneal, saphenous, or tibial nerve. It would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the peripheral nerve that is treated in order to provide the predictable results of modifying the treatment to meet specific patient therapeutic needs are requirements. Furthermore, it has been held that rearranging parts of an invention involves only routine skill in the art. In re Japikse, 86 USPQ 70 (see MPEP 2144.04)
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALYSSA M ALTER whose telephone number is (571)272-4939. The examiner can normally be reached M-F 8am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David E Hamaoui can be reached at (571) 270-5625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALYSSA M ALTER/Primary Examiner, Art Unit 3796
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