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 .
Specification
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because the abstract is written as a method claim, is not in narrative form, and also does not mention the system. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Specification
The disclosure is objected to because of the following informalities: The first paragraph of the specification should include the relevant international application information.
Appropriate correction is required.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the assignment of weigh to the weighed components of the neurophysiology activity data based on the biometric data, must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 1-14 and 19 are objected to because of the following informalities: 1) In Claim 1, last clause, “determination, the DBS.” should be “determination, of the DBS.”, 2) In Claim 2, last clause, “determination, the DBS.” should be “determination, of the DBS.”, 3) in claims 5 and 19, “at least one of a benchmark” should be “at least one benchmark”, 4) In Claim 14, “the methods” in line 2, should be “the method”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2, 5, 7, 10, 14, 16 and 25 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
1) Regarding Claims 2 and 16, it is unclear what the scope and meaning of “to stimulate the DBS” is. The DBS is the stimulation. What does stimulating the stimulation entail?
2) Regarding Claim 14, it is not clear whether the “a subject” and the “a patient” refer to the same person or not. Is the subject of Claim 14 the same or different than the “a patient” of Claim 1, which is included in Claim 14 as the body of the claim? If they are the same, then the two should refer to the person in the same manner and with proper antecedence.
3) Regarding Claims 7 and 10, the passive claiming of “[data] is collected” in a method claim, makes it unclear whether these limitations refer to steps, intended uses or otherwise optional limitations. An undisputable method claim has clauses that are designated by a present participle and separated with a comma (or a semicolon that includes a comma). See Credle v. Bond, 25 F.3d 1566, 1572 (Fed. Cir. 1994). Also see Ex parte Erlich, 3 USPQ2d 1011 (Bd. Pat. App. & Inter. 1986), requiring active positive steps for a method to be definite.
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.
Claims 1-4, 6-11, 13-18, 20-24, and 26-27 are rejected under 35 U.S.C. 103 as being unpatentable over US 2021/0228880 by Machado in view of US 2018/0104500 by Blum.
Regarding Claims 1 and 14, Machado discloses a method for identifying how to apply deep brain stimulation (DBS) to a patient (e.g. abstract, ¶¶ 7-8, Claim 1: DBS optimization method) and a method for treating stroke (e.g. ¶26: treatment of stroke) in a subject comprising applying closed-loop deep brain stimulation (e.g. ¶ 55: automated optimization based on feedback), the method comprising:
receiving with a controller, neurophysiology activity data (e.g. ¶¶ 16, 51, Fig. 7-8: LFP signals, for each electrode A-I, are measured by controller 12);
receiving with the controller, biometric data for the patient (e.g. ¶¶ 37,43,59,66-67; Fig. 2: biometric data from motor task component 18 or external sensors 16, such as “mechanical measures when performing or attempting to perform at least one motor task, or the like”, EEG data, movement and dynamometry/force data; Note here, that “biometric”, derived from “bio” and “metric”, encompasses measurement of any bio-signal, under the broadest reasonable interpretation, and this would include the LFP, EEG and force data of Machado);
identifying with the controller, a weighted component of the neurophysiology activity data (e.g. ¶ 53, Fig. 7-8: the LFP signals of each electrode A-I are “weighed against one another to select the ideal” electrode from the best LFP signal that is closest to the target neurons);
assigning with the controller, based on the biometric data for the patient, a weight to each of the weighted component (e.g. ¶¶ 53: the “weighing” of the electrodes and their LFP signals is also based on feedback from “a change in an instrumentation-based motor behavior”, again for selecting the ideal electrode; ¶¶ 66-68, and Fig. 10-11: these changes include changes to EEG measurements and force measurements based on motor tasks);
determining with the controller, based on the weighted component, how to apply the DBS (e.g. abstract, ¶¶ 7-8, Claim 1: selecting optimal electrodes and determining optimal parameters based on the feedback data, including the motor feedback data); and
instructing application with the controller, based on the determination, [of] the DBS (e.g. ¶¶ 7-8: optimal settings for delivery of DBS are output).
Machado does not explicitly disclose a trained algorithm applied to the weighed component.
However, Blum teaches an analogous DBS method, which includes the use of trained algorithms applied to weighed clinical feedback to derive optimal stimulation (e.g. ¶¶ 21, 91,93, 96-97,106,188, 192, 197, Fig. 5, Claim 14: trained machine learning algorithms to optimize DBS based on weighed feedback). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to incorporate trained algorithms applied to the weighed component in a method according to the teachings of Machado, as taught by Blum, as this would: a) predictably optimize DBS, b) would be a matter of selection among known and limited options of optimization algorithms that would have been obvious to try, and c) enable continuous improvement of the optimization and the capability to draw from large datasets involving past data and/or multiple patients.
Regarding Claim 2, Machado as modified in Claim 1 teaches the method of claim 1, further comprising: receiving feedback data following the DBS with the controller; training an algorithm based on the feedback data to determine whether a sufficient level of criteria to stimulate the DBS are met with the controller; and instructing application with the controller, based on the determination, the DBS (as noted in Claim 1, the algorithm as modified by phosita is continuously improved and trained, including on DBS data from the patient, see e.g. Blum, ¶¶ 20,93,97).
Regarding Claim 3, Machado as modified in Claim 1 teaches the method of claim 1, wherein the neurophysiology activity data includes local field potentials (e.g. ¶ 53: LFPs).
Regarding Claim 4, Machado as modified in Claim 1 teaches the method of claim 1, wherein the biometric data for the patient includes an activity level of the patient (e.g. ¶ 61: motor squeeze activity level).
Regarding Claim 6, Machado as modified in Claim 1 teaches the method of claim 1, further comprising instructing the patient to complete a task (e.g. ¶8: instructing the patient to perform a motor task).
Regarding Claim 7, Machado as modified in Claim 1 teaches the method of claim 1, wherein the biometric data is collected when the patient has been instructed to complete a task, is in a process of completing a task, and/or has completed a task (this claim covers all possible timing in association with collecting the biometric data from performance of a motor task, thus is met by collecting biometric data in association with a motor task at any time; e.g. ¶37,42,49: collecting biomarker data from a motor task; Also note here, that conditional limitations in method claims are optional unless the claim positively recites the steps that would necessitate the contingency to be met, see MPEP 2111.04).
Regarding Claim 8, Machado as modified in Claim 1 teaches the method of claim 6, wherein the task comprises one motor task (e.g. ¶8,31,37: motor task).
Regarding Claim 9, Machado as modified in Claim 1 teaches the method of claim 8, wherein the motor task comprises moving an affected extremity (e.g. ¶37: movement of an extremity).
Regarding Claim 10, Machado as modified in Claim 1, wherein the biometric data is collected when the patient is at rest (e.g. Fig. 10: measurements are taken when there is zero force; Also note here, that conditional limitations in method claims are optional unless the claim positively recites the steps that would necessitate the contingency to be met, see MPEP 2111.04).
Regarding Claim 11, Machado as modified in Claim 1 teaches the method of claim 1, wherein the trained algorithm comprises a heuristic algorithm (e.g. Blum, ¶ 93, 96: heuristic algorithms).
Regarding Claim 13, Machado as modified in Claim 1 teaches the method of claim 1, wherein the patient has epilepsy (e.g. ¶ 26: epilepsy).
Regarding Claim 15, Machado teaches a system for identifying how to apply deep brain stimulation (DBS) to a patient (e.g. abstract, ¶¶ 7-8, Claim 1: DBS optimization system), the system comprising:
a controller (e.g. ¶ 38, Fig. 1: controller 12) configured to receive neurophysiology activity data (e.g. ¶¶ 16, 51, Fig. 7-8: LFP signals, for each electrode A-I, are measured by controller 12);
the controller is further configured to receive biometric data for the patient (e.g. ¶¶ 43,59,66-67; Fig. 2: biometric data from motor task component 18 or external sensors 16, such as “mechanical measures when performing or attempting to perform at least one motor task, or the like”, EEG data, and dynamometry/force data; Note here, that “biometric”, derived from “bio” and “metric”, encompasses measurement of any bio-signal, under the broadest reasonable interpretation, and this would include the LFP, EEG and force data of Machado);
the controller is further configured to identify a weighted component of the neurophysiology activity data (e.g. ¶ 53, Fig. 7-8: the LFP signals of each electrode A-I are “weighed against one another to select the ideal” electrode from the best LFP signal that is closest to the target neurons);
the controller is further configured to assign based on the biometric data for the patient, a weight to each of the more weighted component (e.g. ¶¶ 43,59,66-67; Fig. 2: biometric data from motor task component 18 or external sensors 16, such as “mechanical measures when performing or attempting to perform at least one motor task, or the like”, EEG data, and dynamometry/force data; Note here, that “biometric”, derived from “bio” and “metric”, encompasses measurement of any bio-signal, under the broadest reasonable interpretation, and this would include the LFP, EEG and force data of Machado);
the controller is further configured to determine, based on the weighted component, whether to apply the DBS (e.g. abstract, ¶¶ 7-8, Claim 1: selecting optimal electrodes and determining optimal parameters based on the feedback data, including the motor feedback data, thus at the very least the spatial selectivity meets the claimed “whether” in terms of selecting for each electrode whether to apply the DBS; In addition, the biometric feedback, is used to avoid side effects, thus also meeting the claimed “whether”, see ¶¶ 32,48,59); and
the controller is further configured to instruct application of the DBS in response to the algorithm (e.g. ¶¶ 7-8: optimal settings for delivery of DBS are output).
Machado does not explicitly disclose a trained algorithm applied to the weighed component.
However, Blum teaches an analogous DBS method, which includes the use of trained algorithms applied to weighed clinical feedback to derive optimal stimulation (e.g. ¶¶ 21, 91,93, 96-97,106,188, 192, 197, Fig. 5, Claim 14: trained machine learning algorithms to optimize DBS based on weighed feedback). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to incorporate trained algorithms applied to the weighed component in a system according to the teachings of Machado, as taught by Blum, as this would: a) predictably optimize DBS, b) would be a matter of selection among known and limited options of optimization algorithms that would have been obvious to try, and c) enable continuous improvement of the optimization and the capability to draw from large datasets involving past data and/or multiple patients.
Regarding Claim 16, Machado as modified in Claim 1 teaches the system of claim 15, further comprising: the controller is further configured to receive feedback data following the DBS; the controller is further configured to train an algorithm based on the feedback data to determine whether a sufficient level of criteria to stimulate the DBS are met; and the controller is further configured to apply, based on the determination, the DBS (as noted in Claim 1, the algorithm as modified by phosita is continuously improved and trained, including on DBS data from the patient, see e.g. Blum, ¶¶ 20, 93, 97).
Regarding Claim 17, Machado as modified in Claim 1 teaches the system of claim 15, wherein the neurophysiology activity data includes local field potentials (e.g. ¶ 53: LFPs).
Regarding Claim 18, Machado as modified in Claim 1 teaches the system of claim 15, wherein the biometric data for the patient includes an activity level of the patient (e.g. ¶ 61: motor squeeze activity level).
Regarding Claim 20, Machado as modified in Claim 1 teaches the system of claim 15, wherein the controller is further configured to instruct the patient to complete a task (e.g. ¶8: instructing the patient to perform a motor task).
Regarding Claim 21, Machado as modified in Claim 1 teaches the system of claim 15, wherein the controller is further configured such that the biometric data is collected when the patient has been instructed to complete a task, is in a process of completing a task, or has completed a task (this claim covers all possible timing in association with collecting the biometric data from performance of a motor task, thus is met by collecting biometric data in association with a motor task at any time; e.g. ¶37,42,49: collecting biomarker data from a motor task).
Regarding Claim 22, Machado as modified in Claim 1 teaches the system of claim 20, wherein the task comprises a motor task (e.g. ¶8,31,37: motor task).
Regarding Claim 23, Machado as modified in Claim 1 teaches the system of claim 22, wherein the motor task comprises moving an affected extremity (e.g. ¶37: movement of an extremity).
Regarding Claim 24, Machado as modified in Claim 1 teaches the system of claim 22, wherein the trained algorithm comprises a heuristic algorithm (e.g. Blum, ¶ 93, 96: heuristic algorithms).
Regarding Claim 26, Machado as modified in Claim 1 teaches the system of claim 15, wherein the patient has epilepsy (e.g. ¶ 26: the system is capable for use in a patient with epilepsy).
Regarding Claim 27, Machado as modified in Claim 1 teaches the system of claim 15, wherein the biometric data is collected when the patient is at rest (e.g. Fig. 10: measurements are taken when there is zero force, thus the system is capable for collecting the data when the patient is at rest; Note that “the data is collected” is interpreted as a purely functional limitation that does not directly depend on any of the claimed structures).
Claims 5 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Machado/Blum, as applied to Claims 1 and 15, and further in view of US 2018/0085586 by Stanslaski.
Regarding Claims 5 and 19, Machado as modified in Claims 1 and 15 teaches claims 1 and 15, respectively, yet does not explicitly teach wherein the controller is further configured to determine whether to apply the DBS comprises identifying at least one of a benchmark for at least one of a frequency of a received neurophysiological data, a phase of a frequency band of the received neurophysiological data, a spike of individual unit activity, phase coincidence of multi-unit activity of the received neurophysiological data, and/or a time-locked neural signal.
However, Stanslaski teaches an analogous DBS system and method, wherein the system is configured to uses correlations of certain frequency bands of neurological signals from the patient as indicators to the presence or absence of side effects, such as dyskinesia, and adjusts the stimulation to avoid these side effects (e.g. ¶¶ 82,130,177,184: Gamma and Beta frequencies indicate the presence or absence of certain side effects and the DBS is adjusted accordingly). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to incorporate correlations between Gamma or Beta frequency bands from neurological signals as indicators of side effects in the optimization of DBS in a method and system according to the teachings of Machado, as taught by Stanslaski, in order to reduce or eliminate side effects, such as dyskinesia, as suggested by Stanslanski (e.g. ¶82).
Claims 12 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Machado/Blum, as applied to Claims 2 and 16, and further in view of US 20210316144 by Ganguly.
Regarding Claims 12 and 25, Machado as modified in Claims 1 and 15 teaches Claims 2 and 16, respectively, yet does not explicitly disclose wherein the controller is further configured to adjust a timing of a stimulation relative to one or more phases of motor planning or relative to one or more phases of motor execution.
However, Ganguly teaches an analogous DBS system and method to treat stroke (e.g. abstract), wherein therapeutic delivery of electrical stimulation time-locked to the expected onset of low frequency oscillatory (LFOs) activity was found to significantly improve upper limb motor function (e.g. ¶¶ 9, 37). These LFOs establish the timing of motor execution (¶37, Fig. 1A), they are used as feedback (Claim 1), and they are used to adjust the timing, relative to motor task planning or execution, of DBS in order to evoke them (¶37, 42, Fig. 1A). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to incorporate timing adjustment of DBS relative to a phase of motor planning or execution in a system and method, according to the teachings of Machado, as taught by Ganguly, in order to evoke LFOs and improve upper limb motor function, as suggested by Ganguly (¶37).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANOLIS Y PAHAKIS whose telephone number is (571)272-7179. The examiner can normally be reached M-F 9-5, EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, CARL LAYNO can be reached at (571)272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MANOLIS PAHAKIS/Examiner, Art Unit 3796