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, filed November 10, 2025, with respect to the rejection(s) of claim(s) 1-4, 7-16, and 19-20 under 35 USC 103 have been fully considered and are persuasive. Therefore, the previous rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection have been made as can be further seen below.
Election/Restrictions
Applicant's election with traverse of Species 1A in the reply filed on June 11, 2025 is acknowledged. The traversal is on the ground(s) that:
No reasons were given above for the proper restriction requirement and
Examining all species under the linking claim does not impose a serious search burden, since the applicant asserts that the search for generic claims would “encompass the prior art relevant to all species.”
In response to applicant’s argument that no reasons were given above, an inadvertent closing paragraph was used, but the species are independent or distinct because they are alternatives to one another as claimed. Furthermore, in regard to the applicant’s second argument, this is not found persuasive because search of claim 1 would not necessarily include the search queries needed to fully search a more specific dependent claim. Furthermore, a more specific search of one species would not necessarily include the various specific queries needed to search a different species. Therefore, the requirement is still deemed proper and is therefore made FINAL.
Claims 5-6 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected species, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on June 11, 2025.
Claim Rejections - 35 USC § 103
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 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, 8, 11, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over US 10,099,057 B2 to Kent et al. (hereinafter “Kent”) in view of US 2011/0230936 A1 to Jensen et al. (hereinafter “Jensen”).
Regarding claim 1, Kent teaches a method (abstract, line 1), comprising:
delivering a neuromodulation signal according to neuromodulation parameters to neural tissue (abstract, lines 1-7);
sensing local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49);
providing a comparison of at least one excitation pulse from the stimulation waveform with the evoked potential waveform in order to identify the neural system response (col. 5, lines 16-26, and col. 24, lines 20-38);
and
controlling the delivery of the neuromodulation signal based on the comparison (abstract, col. 1, lines 65-67, col. 2, lines 1-13 and lines 18-25, col. 5, lines 16-26, and col. 24, lines 20-54),
but does not disclose,
Sensing local field potentials (LFPs) within a spinal cord or a peripheral nerve indicative of ongoing LFP oscillations, wherein the ongoing LFP oscillations are present in the spinal cord or the peripheral nerve without the neuromodulation signal;
extracting one or more features from the local field potentials LFPs that are indicative of the ongoing oscillations;
providing a comparison of the extracted one or more feature(s) to corresponding one or more setpoints;
and
controlling the delivery of the neuromodulation signal based on the comparison.
However, Jensen teaches techniques for delivering electrical stimulation at one or more phases in response to ongoing oscillating signals in a patient (see abstract, lines 1-4). The system (fig. 1) teaches:
Sensing local field potentials (LFPs) within a spinal cord or a peripheral nerve indicative of ongoing LFP oscillations (see abstract: “This disclosure describes techniques for delivering electrical stimulation at one or more phases relative to an ongoing oscillating signal in a patient, and then mapping the response to the oscillating signal.”, and para 0049), wherein the ongoing LFP oscillations are present in the spinal cord or the peripheral nerve without the neuromodulation signal (see fig, 4A-100, para 0004, and para 0074: “first four sentences”). Since the oscillating signals are ongoing/continuous in nature, and the electrical stimulation is delivered during one or more phases in relation to the ongoing signal, the LFP oscillations are present in the brain with and without the neuromodulation signal being present. Furthermore, Jensen teaches extracting/selecting one or more features from the local field potentials LFPs that are indicative of the ongoing oscillations (see abstract, fig. 5B, fig. 6, and para 0082);
providing a comparison of the extracted/selected one or more feature(s) (such as one or more of a phase, period, or amplitude of the oscillating signal) to corresponding one or more setpoints (where the “setpoint” in this case is the phase response map characteristic—see para 0082);
and
controlling the delivery of the neuromodulation signal based on the comparison (see para 0082: “The phase response map is a characteristic of the oscillating signal and, as such, may also be used to determine the efficacy of the applied first electrical stimulation……. Stimulation generator 44 may deliver substantially similar first electrical stimulation to the ongoing oscillating signal and processor 40 may analyze phase response map 150 to determine whether the phase response map changed. For example, if the phase shift remain unchanged, processor 40 may determine that the first electrical stimulation should be used for therapeutic purposes, i.e., for delivery of second electrical stimulation. If, however, the phase shift was much smaller despite the application of substantially similar first electrical stimulation, processor 40 may determine that the first electrical stimulation parameters should not be used for therapeutic purposes, given that the ongoing oscillating signals response to those first electrical stimulation parameters is not repeatable.”, and para 0083, emphasis on the following sentences: “After stimulation generator 44 delivers the first electrical stimulation at each respective phase of the plurality of phases, processor 40 measures a response in the oscillating signal to the first electrical stimulation (205), e.g., a delay, an advance, or no change in a phase of the oscillating signal, a change in amplitude, a change in period, and a change in a phase response map. Based on the measured responses, processor 40 determines a phase at which to deliver second electrical stimulation (210). For example, processor 40 may determine a phase from phase response map 59. Then, stimulation generator 44 delivers the second electrical stimulation to the patient at the determined phase (215)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Kent with the teachings of Jensen to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal in response to the patient normal neuronal activity, ultimately providing personalized and accurate stimulation treatment for each patient.
Regarding claim 8, Kent as modified teaches the method of claim 1, wherein the controlling the delivery of the neuromodulation signal based on the comparison includes providing a feedback closed loop control using a Proportion Integral Derivative (PID), PID with thresholds, a lookup table, a Kalman control, an On/Off control or a threshold control (see col. 17, lines 40-67 and col. 18, lines 1-11). The processor identifies and uses the candidate response function to determine the resultant response function (which is the neuronal system response) based on the comparison with a threshold, which is ultimately used to determine values for a set of neural stimulation parameter for delivering neural stimulation therapy to a patient.
Regarding claim 11, Kent as modified teaches the method of claim 1 that senses local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49), further comprising:
filtering the sensed LFPs to filter out at least one of noise, ECAPs, or one or more artifacts; or performing bandpass filtering frequencies of interest (see col. 9, lines 63-67, col. 10, lines 1-13, and col. 20, lines 10-20).
Regarding claim 20, Kent teaches a non-transitory machine-readable medium including instructions (col. 12, lines 6-23 and col. 26, lines 7-20), which when executed by a machine, cause the machine to perform a method comprising:
delivering a neuromodulation signal according to neuromodulation parameters to neural tissue (abstract, lines 1-7);
sensing local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49);
providing a comparison of at least one excitation pulse from the stimulation waveform with the evoked potential waveform in order to identify the neural system response (col. 5, lines 16-26, and col. 24, lines 20-38);
and
controlling the delivery of the neuromodulation signal based on the comparison (abstract, col. 1, lines 65-67, col. 2, lines 1-13 and lines 18-25, col. 5, lines 16-26, and col. 24, lines 20-54), but does not disclose
Sensing local field potentials (LFPs) within a spinal cord or a peripheral nerve indicative of ongoing LFP oscillations, wherein the ongoing LFP oscillations are present in the spinal cord or the peripheral nerve without the neuromodulation signal;
extracting one or more features from the local field potentials LFPs that are indicative of the ongoing oscillations;
providing a comparison of the extracted one or more feature(s) to corresponding one or more setpoints;
and
controlling the delivery of the neuromodulation signal based on the comparison.
However, Jensen teaches techniques for delivering electrical stimulation at one or more phases in response to ongoing oscillating signals in a patient (see abstract, lines 1-4). The system (fig. 1) teaches:
Sensing local field potentials (LFPs) within a spinal cord or a peripheral nerve indicative of ongoing LFP oscillations (see abstract: “This disclosure describes techniques for delivering electrical stimulation at one or more phases relative to an ongoing oscillating signal in a patient, and then mapping the response to the oscillating signal.” And para 0049), wherein the ongoing LFP oscillations are present in the spinal cord or the peripheral nerve without the neuromodulation signal (see fig, 4A-100, para 0004, and para 0074: “first four sentences”). Since the oscillating signals are ongoing/continuous in nature, and the electrical stimulation is delivered during one or more phases in relation to the ongoing signal, the LFP oscillations are present in the spinal cord with and without the neuromodulation signal being present. Furthermore, Jensen teaches extracting/selecting one or more features from the local field potentials LFPs that are indicative of the ongoing oscillations (see abstract, fig. 5B, fig. 6, and para 0082);
providing a comparison of the extracted one or more feature(s) (such as one or more of a phase, period, or amplitude of the oscillating signal) to corresponding one or more setpoints (where the “setpoint” in this case is the phase response map characteristic—see para 0082);
and
controlling the delivery of the neuromodulation signal based on the comparison (see para 0082: “The phase response map is a characteristic of the oscillating signal and, as such, may also be used to determine the efficacy of the applied first electrical stimulation……. Stimulation generator 44 may deliver substantially similar first electrical stimulation to the ongoing oscillating signal and processor 40 may analyze phase response map 150 to determine whether the phase response map changed. For example, if the phase shift remain unchanged, processor 40 may determine that the first electrical stimulation should be used for therapeutic purposes, i.e., for delivery of second electrical stimulation. If, however, the phase shift was much smaller despite the application of substantially similar first electrical stimulation, processor 40 may determine that the first electrical stimulation parameters should not be used for therapeutic purposes, given that the ongoing oscillating signals response to those first electrical stimulation parameters is not repeatable.”, and para 0083, emphasis on the following sentences: “After stimulation generator 44 delivers the first electrical stimulation at each respective phase of the plurality of phases, processor 40 measures a response in the oscillating signal to the first electrical stimulation (205), e.g., a delay, an advance, or no change in a phase of the oscillating signal, a change in amplitude, a change in period, and a change in a phase response map. Based on the measured responses, processor 40 determines a phase at which to deliver second electrical stimulation (210). For example, processor 40 may determine a phase from phase response map 59. Then, stimulation generator 44 delivers the second electrical stimulation to the patient at the determined phase (215)”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Kent with the teachings of Jensen to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal in response to the patient normal neuronal activity, ultimately providing personalized and accurate stimulation treatment for each patient.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Kent in view of Jensen, and further in view of US 2019/0001121 A1 to Lara et al. (hereinafter “Lara”).
Regarding claim 2, Kent as modified teaches the method of claim 1, but does not explicitly disclose wherein the extracting one or more features includes extracting at least one of a time domain feature, a frequency domain feature or a wavelet domain feature.
However, Lara teaches devices, systems, and methods for controlling a neurostimulator based on processed biosignal data (abstract and para 0024). The system (fig. 1) teaches wherein the extracting of one or more features includes extracting at least one of a time domain feature, a frequency domain feature or a wavelet domain feature (para 0023, lines 1-6).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Lara to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal, ultimately providing more accurate and precise stimulation treatment for the patient.
Regarding claim 3, Kent as modified teaches the method of claim 1, wherein the method include but does not explicitly disclose wherein the extracting one or more features include the extracting at least one time domain feature/ domain features.
However, Lara teaches wherein the extracting one or more features include the extracting at least one time domain feature/domain features (para 0023, lines 1-6).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Lara to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal, ultimately providing more accurate and precise stimulation treatment for the patient.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over to Kent in view of Jensen and Lara, and further in view of WO 2019/156936 A1 to Brill et al. (hereinafter “Brill”).
Regarding claim 4, Kent as modified teaches the method of claim 3, wherein the method further comprises evaluating the frequency of the ongoing LFP signal (see para 0018 and para 0049-0050) but does not explicitly disclose wherein the extracting at least one time domain feature includes extracting at least one of: peak to peak amplitude, standard deviation vs. mean, oscillation frequency, variance of peak-to-peak times, variance of individual min-max ranges, area under the curve (AUC), curve length, RMS amplitude, a regression measure of drift over time, or a measure of power.
However, Brill teaches wherein the extracting at least one time domain feature includes extracting at least one of: peak to peak amplitude, standard deviation vs. mean, oscillation frequency, variance of peak-to-peak times, variance of the individual min-max ranges, area under the curve (AUC), curve length, RMS amplitude, a regression measure of drift over time, or a measure of power (para 00120: “Note that a feature may be any signal processing metric extracted from the ECAP signal, such as the ECAP amplitude, delay, width, length of the curve as if measuring distance or any measure indicative of distance (e.g., the sum of absolute values of consecutive signal samples over a predefined moving window), area under the curve, ratio of 3 J specific amplitudes within the EC P pattern, or any other signal processing manipulation”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Brill to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal, ultimately providing more accurate and precise stimulation treatment for the patient.
Claims 7, 16, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over to Kent in view of Jensen, and further in view of US 10,842,997 B2 to Moffitt et al. (hereinafter “Moffitt”).
Regarding claim 7, Kent as modified teaches the method of claim 1 that senses local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49), but does not explicitly disclose wherein the corresponding setpoint(s) includes at least one feature for the local field potentials indicative of oscillations corresponding to a symptom level, a therapy rating, or side-effect ratings.
However, Moffitt teaches a system and method for regulating stimulation parameters supplied to a patient for neurostimulation (col. 1, lines 15-36). The system (figs. 1 and 5) uses machine learning to optimize neurostimulation patterns. In an embodiment, neurostimulation is applied to the patient, and following the stimulation, patient metrics (which is an objective pain measurement/therapy or side-effect rating) are obtained passively in which the patient metric is automatically collected from the patient, and are ultimately used by the machine learning engine to tune the stimulation applied to the patient (col. 12, lines 36-67 and col. 13, lines 1-8 and lines 28-44).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Moffitt to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal in order to prevent painful stimulation from being applied to the patient, ultimately providing more accurate and precise stimulation therapy to the patient.
Regarding claim 16, Kent as modified teaches the method of claim 1 that senses local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49), but does not disclose wherein the one or more setpoints correspond to a state based on a quantitative mapping of features for the LFPs that are indicative of the ongoing oscillations for:
baseline and therapy;
qualitative based on a pain score;
or overlaid upon pre-defined datasets.
However, Jensen teaches LFPs indicative of ongoing oscillations (see abstract, first sentence, para 0016, and para 0023), but does not explicitly disclose
wherein the one or more setpoints correspond to a state based on a quantitative mapping of features for the LFPs that are indicative of the ongoing oscillations for:
baseline and therapy;
qualitative based on a pain score;
or overlaid upon pre-defined datasets.
However, Moffitt teaches wherein one or more setpoints/metrics correspond to a state based on a quantitative mapping of features for the local field potentials that are indicative of the spinal cord oscillations for qualitative based on a pain score (see col. 7, lines 59-67, col. 8, lines 1-8, col. 10, lines 1-17 and lines 56-61, col. 12, lines 36-65, col. 13, lines 28-44, col. 16, lines 49-57).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified teachings of Kent with the teachings of Moffitt to arrive at the claimed invention. Such modification would improve the system by ensuring the system is able to accurately and automatically predict the most appropriate stimulation signal needed to properly treat the patient (without causing unwanted pain/ side-effects), ultimately providing the effective stimulation therapy/treatment for the patient.
Regarding claim 19, Kent as modified teaches the method of claim 1, but does not explicitly disclose wherein the one or more setpoints/metric(s) corresponds to a preconfigured state determined based on a patient's diagnosis or other demographic factors, or correspond to a user-customizable state.
However, Moffitt teaches wherein the one or more setpoints/metric(s) corresponds to a preconfigured state determined based on a patient's diagnosis or other demographic factors, or correspond to a user-customizable state (col. 12: “Some patient metrics gathered via active participation with the patient may be referred to as subjective patient metrics, where the patient is asked to describe the pain. The patient metrics may include various aspects of pain, such as the severity as measured with a numerical value, the location(s) of pain, the sensation of pain (e.g., numbness, shape acute pain, throbbing, etc.), the duration of pain, or other aspects of pain. The patient metrics may also include results of questionnaires, responses to queries about a general state of wellness, results of memory tests (e.g., working memory tasks), rating scales, and the like” ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Kent with the teachings of Moffitt to arrive at the claimed invention. Such modification would improve the system by allowing for more personalized stimulation according to each patient’s state (such as their pain state or health state), ultimately allowing for more accurate and precise stimulation treatment for each patient.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over to Kent in view of Jensen, and further in view of US 2020/0001086 A1 to Fernandez et al. (hereinafter “Fernandez”).
Regarding claim 9, Kent as modified teaches the method of claim 1 that senses local field potentials within a spinal cord or a peripheral nerve (col. 11, lines 3-7 and 64-67, col. 12, lines 1-5, col. 1, lines 35-49), but does not explicitly disclose wherein the sensing local field potentials indicative of ongoing oscillations includes using electrodes designed, placed or orientated to enhance sensing of spinal cord oscillations.
However, Jensen teaches wherein the sensing local field potentials indicative of ongoing oscillations includes using electrodes designed, placed or orientated to enhance sensing of brain oscillations (see figs. 1-2, 24, 26, and 46, and para 0049), but does not disclose wherein sensing includes using electrodes designed, placed or orientated to enhance sensing of spinal cord oscillations.
However, Fernandez teaches a system configured to bilaterally sense neurophysiological signals from a patient (abstract). The system (figs. 1-9) discusses placing leads/paddle leads with electrodes that are specifically placed/oriented along the spinal cord to improve sensing and stimulation provided to the spinal cord for therapy (para 0019, 0070-0071, para 0092, and para 0094, lines 1-3).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Jensen and Fernandez to arrive at the claimed invention. Such modification would improve the system by ensuring the electrodes are oriented properly to improve the sensed LCPs generated following the stimulation, ultimately providing more accurate and precisely-tuned stimulation therapy for the patient.
Regarding claim 10, Kent as modified teaches the method of claim 9, but does not disclose wherein the electrodes include:
electrodes arranged in a paddle array and rostrocaudally orientated;
cylindrical electrodes with a large diameter or large surface area to increase sensing surface;
intradural electrodes;
epidural electrodes;
or electrodes placed over a dorsal horn.
However, Fernandez teaches wherein the electrodes include electrodes arranged in a paddle array and rostrocaudally orientated (see figs. 1 and 7-9, para 0071, para 0092, lines 1-8, para 0095, lines 1-4 ).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Fernandez to arrive at the claimed invention. Such modification would improve the system by ensuring the electrodes are oriented properly to improve the sensed LCPs generated following the stimulation, ultimately providing more accurate and precisely-tuned stimulation therapy for the patient.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over to Kent in view of Jensen, and further in view of WO 2019/156936 A1 to Brill et al. (hereinafter “Brill”).
Regarding claim 12, Kent as modified teaches the method of claim 1, further comprising using at least one other sensor/sensing electrodes to provide at least one other sensor signal (col. 11, lines 8-26 and col. 24, lines 20-38 and col. 24, lines 20-38), but does not explicitly disclose extracting at least one other feature from the other sensor signal, and providing a comparison to the at least one other feature from the other sensor signal to at least one other setpoint.
However, Brill teaches wherein the system comprises receiving, via a sensing electrodes, ECAP signals produced as a result of the first external stimulation supplied to the patient. Afterwards, the first signal is stored in memory within the device. Following the first stimulation, a second stimulation is applied to the patient via internal electrodes, and then second electrical signals are produced. Afterwards, a difference may be determined by comparing the received ECAP signals (generated by the internal stimulation) by comparing these signals with the ECAP signals stored in memory (which are also a result of the external stimulation). Furthermore, one or more features (or a single feature used as a landmark/setpoint) are extracted to create a feature parameter space (and used with machine learning techniques), and based off of the differences between either a single feature or more than one feature, the stimulation parameter is adjusted/reduced (para 00120).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Brill to arrive at the claimed invention. Such modification would improve the system by properly tuning the neurostimulation signal, ultimately providing more accurate and precise stimulation treatment for the patient.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Kent in view of Jensen, and further in view of US 2019/0246989 A1 to Genov et al. (hereinafter “Genov”).
Regarding claim 13, Kent as modified teaches the method of claim 1 comprising one or more setpoints (where the “setpoint” in this case is the phase response map characteristic—see para 0082), but does not explicitly disclose using machine learning to evaluate learning data to classify the one or more setpoints.
However, Genov teaches a system and method for classifying time series data for state identification (abstract, lines 1-2). The system (figs. 1-3) uses machine learning to train a machine learning model using learning data, and determining the occurrence of a state of the new time series data based on determining a classified feature vector (see abstract, para 0002, para 0051, and para 0078: “An OC-SVM model is trained and stored on an FPGA fabric along with feature normalization coefficients used for the training data”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Genov to arrive at the claimed invention. Such modification would improve the system by allowing for faster stimulation tuning with respect to the received sense signals, ultimately providing more faster and more precise stimulation treatment for the patient.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Kent in view of Jensen and Genov, and further in view of Brill.
Regarding claim 14, Kent as modified teaches the method of claim 13, but does not disclose wherein the using machine learning includes using a neural network, a Support Vector Machine (SVM), a least square model, or a mean squares model to determine how state variables change with stimulation, for use in controlling the delivery of the neuromodulation signal.
However, Brill teaches wherein using machine learning includes using a neural network (see para 00119: “The process may continue until the difference between the two evoked compound action potentials is less than or equal to the specified criterion. Machine learning (e.g., supervised machine learning) may be used to train a neural network model that may be stored in the memory 824 and the control circuitry 828 may retrieve and use the neural network model when making adjustments to the one or more electrical parameters. In an example where a neural network model is used to adjust the one or more electrical parameters, a number of adjustments may be reduced compared to the case where no neural network model is used”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified system of Kent with the teachings of Brill to arrive at the claimed invention. Such modification would improve the system by allowing for faster stimulation tuning with respect to the received sense signals, ultimately providing faster and more precise stimulation treatment for the patient.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Kent in view of Jensen, and further in view of US 2021/0085257 A1 to Patil et al. (hereinafter “Patil”).
Regarding claim 15, Kent as modified teaches the method of claim 1, but does not disclose wherein the method further comprises gathering learning data using intervals of stimulation and recording, wherein the intervals between stimulation are determined using known stimulation onset/offset times, patient preference, or a signal duration of sufficient length or with sufficient delay to obtain a desired amount of learning data with appropriate delay.
However Patil teaches a neural targeting system and method for proper placement of a stimulation probe in order to properly stimulate a target area of the brain afflicted with an illness or disorder (abstract). The system (fig. 1-2) teaches gathering learning data using intervals of stimulation and recording, wherein the intervals between stimulation are determined using a known signal duration of sufficient length (see para 0004, para 0020-0023, and para 0032).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified teachings of Kent with the teachings of Patil to arrive at the claimed invention. Such modification would improve the system by ensuring the system is able to accurately and automatically predict the most appropriate stimulation signal needed to properly treat the patient, ultimately providing the effective stimulation therapy/treatment for the patient.
Allowable Subject Matter
Claims 17-18 are 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 following is a statement of reasons for the indication of allowable subject matter:
The art cited above does not disclose the limitations stated in the claims. Furthermore, after a complete search, no additional references could be found which could properly anticipate or render obvious the limitations of claims 17-18 in any combination.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hershey et al. (US 2016/0082268 A1) teaches a system for calibrating dorsal horn stimulation through adjusting one or more modulation parameters using response information.
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/K.J.W./Examiner, Art Unit 3792
/NIKETA PATEL/Supervisory Patent Examiner, Art Unit 3792