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 .
Withdrawal of Finality
The finality of Office Action dated May 6, 2026 is hereby withdrawn.
The limitations of the previously allowable claim 17 are now amended into claim 1, however, upon search, US 2021/0346699 A1 to Miocinovic et al. has been found the reads on the current limitations in claim 1, therefore, the previous final office action is withdrawn.
Response to Arguments
Applicant's arguments filed June 24, 2026 have been fully considered but they are not completely persuasive.
Regarding applicant’s first argument, applicant argues that Saab does not teach controlling delivery of an electrical neuromodulation signal based on the sensed spinal LFP oscillations, but instead teaches controlling a drug dosage (such as a pharmalogical agent) based on the sensed spinal LFP. The examiner respectfully disagrees.
As stated in para [0025] and para [0042], and para [0074] the “therapeutic agent” (which can be any agent that produces a healing or stabilizing effect for the patient), is not limited to a drug dosage/drug delivery, but can also include providing a neuromodulatory treatment to the patient (such as deep brain stimulation or spinal cord stimulation) as stated in para [0042]. Therefore, after the LFPs are sensed in the spinal cord of the subject, the therapeutic agent is administered to the subject (which can be a either a drug dosage or stimulation provided to the patient).
Furthermore, applicant argues that Saab does not teach “providing a comparison of the extracted one or more features to corresponding one or more setpoints” and “controlling the delivery of the neuromodulation signal based on the comparison” and further provides support from para [0077] of Saab. The examiner respectfully disagrees this statement.
First, although the applicant is referencing paragraphs that were not previously relied on in the final rejection, in regard to applicant’s first argument, the examiner would like to highlight that Jensen (which was first introduced in the final rejection dated May 6, 2026) already disclosed the claim limitations disclosed above, and therefore did not rely on Saab to teach the claim limitations discussed above. Saab was solely relied on to teach LFP oscillations present in the spinal cord. Furthermore, applicant argues that the closed-loop aspect of the system (such as the sensing stimulation of the system described in para [0077]) are both directed to the brain, not the spinal cord or peripheral nerve. The examiner respectfully disagrees.
As previously stated above and stated in the abstract, it is apparent that the sensing and stimulation is primarily directed to the spinal cord of the subject, but can also be used for treatment of the brain in addition to the spinal cord, which is previously stated in para [0025] and para [0074] in addition to the abstract.
Although the examiner has found applicant’s argument regarding the rationale provided in the final rejection to be persuasive, in view of the explanation applicant provided above, applicant’s arguments regarding the references have not been found to be persuasive.
Furthermore, after further search and consideration, claim 18 have overcome the prior art of record, however, it is not indicated as allowable in view of the 35 U.S.C. 112(b) rejection noted below. Therefore, the current rejections will be addressed in a second-action non-final.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea and a mental process without significantly more. Claim 1 recites a method for delivering a neuromodulation signal to the patient according to neuromodulation parameters to the neural tissue, sensing local field potentials within the spinal cord or peripheral nerve without the neuromodulation signal, extracting one or more features from the local field potential that are indicative of ongoing oscillations, providing a comparison of the extracted one or more feature(s) to corresponding one or more setpoints, controlling the delivery of the neuromodulation signal based on the comparison, and mapping relationships between correlated features and states, where mapping the relationship includes performing a regressive fit for each state to determine the relationship between the corresponding state and features, or plotting a ratio of correlated variables against programming parameters.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.05. The instant claims are evaluated according to such analysis.
Step 1:
Claims 1 and 20 recite a method (process).
Step 2A, Prong 1:
Claims 1 and 20 recite the steps of:
Sensing local field potentials (LFPs) within a spinal cord or peripheral nerve indicative of ongoing LFP oscillations.
Extracting one or more feature from the 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.
Mapping relationships between correlated features and states, wherein the mapping relationships includes performing a regressive fit for each state or plotting a ratio of correlated variables against programming parameters.
The steps above, under broadest reasonable interpretation, can be performed by mental process steps because they can be practically performed in the human mind. For instance, a clinician can use the system to sense local field potentials (LFPs) within a spinal cord or peripheral nerve indicative of ongoing oscillations, extract one or more features from the LFPs indicative of the ongoing oscillations, provide a comparison of the extracted one or more features to corresponding one or more setpoints, control the neuromodulation signal based on the comparison, and mapping relationships between correlated features in states, where the mapping relationship can include a regressive fit for each state to determine the relationships between the corresponding state and features.
Step 2A, Prong 2:
Claims 1 and 20 include the additional elements of:
Delivering a neuromodulation signal according to neuromodulation parameters to neural tissue. This is merely adds insignificant extra-solution activity to the judicial exception. See MPEP 2106.04 (d).
Controlling the delivery of the neuromodulation signal based on the comparison. This is merely adds insignificant extra-solution activity to the judicial exception. See MPEP 2106.04 (d).
Linking the use of a judicial exception to insignificant extra-solution activity do not provide integration into a practical application.
Step 2B:
Claims 1 and 20 include the additional elements of:
Delivering a neuromodulation signal according to neuromodulation parameters to neural tissue. This is merely adds insignificant extra-solution activity to the judicial exception. See MPEP 2106.04 (d).
Controlling the delivery of the neuromodulation signal based on the comparison. This is merely adds insignificant extra-solution activity to the judicial exception. See MPEP 2106.04 (d).
These additional elements in claims 1 and 20 identified by the courts, either alone or in combination, have found not to be enough to qualify as “significantly more” than the abstract idea itself when recited in a claim with a judicial exception.
Dependent Claims:
Claims 2-4, 7-16, 18-19, and 21 further define the mental process and abstract idea, therefore failing to amount to “significantly more” than the abstract ideas either alone or in combination as previously stated for the independent claims.
To overcome the current 101 rejection, the examiner suggests amending the claims to include when and how the mapping is being used in the system (i.e. is the relationship mapping between correlated features and states being done to determine the delivered neuromodulation signal, after the delivered the neuromodulation signal, etc).
Claim Rejections - 35 USC § 112
Claim 18 is 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.
Claim 18 recites in lines 15-16, “Performing a sensitivity analysis on a plurality of parameters to identify one or more of the plurality of parameters having a greater change between good and bad states with a change in SCS…” The term “good” and “bad” states lacks definitiveness, therefore making the scope of the invention indefinite. A clear definition of “good” or “bad” with respect to the effect caused by the stimulation parameters should be provided. Para [0040], [0060]-[0061], and [0094]-[0096] references good and bad states, but further clarification is needed in order to specify what these good and bad states are specifically.
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”), US 2018/0228421 A1 to Saab, and US 2021/0346699 A1 to Miocinovic et al. (hereinafter “Miocinovic”).
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 brain and action potentials within a spinal cord (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 the brain 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)”).
Jensen does not disclose wherein the LFP oscillations are present in the spinal cord or peripheral nerve.
However, Saab teaches a system and method for detection neuronal oscillations within a patient (see abstract and para 0025). The system (fig. 1) teaches sensing neuronal oscillation within the spinal cord of a patient (see abstract and para 0006), and based on the analysis of the LFP waveform, provide a therapeutic agent to the patient, wherein the therapeutic agent includes providing a neuromodulation signal to the patient (see abstract, para 0006, para 0025, and para 0042).
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 and the spinal cord oscillation sensing of Saab 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.
Although Saab teaches a system and method for detecting LFP within the spinal cord of the patient, they do not teach mapping relationships between correlated features and states, wherein the mapping relationships includes:
performing a regressive fit for each state to determine the relationships between the corresponding state and features; or plotting a ratio of correlated variables against programming parameters.
However, Miocinovic teaches systems and methods for automatically determining patient-specific set of stimulation parameters based on applying an optimization algorithm (see abstract). The system (fig. 1) teaches wherein a Gaussian Process Regression Model performs a regressive fit for each state/clinical response score to determine the relationship between corresponding states/clinical scores and features/stimulation parameters (see para [0085]-[0087] and para [0092]-[0093]).
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, the spinal cord oscillation sensing of Saab, and the regression method of Miocinovic to arrive at the claimed invention. Such modification would improve the system by optimizing the closed-loop neuromodulation system, allowing for more precise and effective neuromodulation 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, 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:
sensing local field potentials within a brain and action potentials within a spinal cord (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 the brain 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)”).
Jensen does not disclose wherein the LFP oscillations are present in the spinal cord or peripheral nerve.
However, Saab teaches a system and method for detection neuronal oscillations within a patient (see abstract and para 0025). The system (fig. 1) teaches sensing neuronal oscillation within the spinal cord of a patient (see abstract and para 0006), and based on the analysis of the LFP waveform, provide a therapeutic agent to the patient, wherein the therapeutic agent includes providing a neuromodulation signal to the patient (see abstract, para 0006, para 0025, and para 0042).
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 and the spinal cord oscillation sensing of Saab 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, Saab, Miocinovic, 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, but does not explicitly disclose wherein extracting one or more features includes 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, Saab, Miocinovic, 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, Saab, and Miocinovic, 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, 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, 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, Saab, and Miocinovic, 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, 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, Saab, and Miocinovic, 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, Saab, and Miocinovic, 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, Saab, Miocinovic, 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, Saab, and Miocinovic, 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 Conclusion
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.
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Kent in view of Miocinovic.
Regarding claim 21, Kent as modified teaches The non-transitory machine-readable medium of claim 20, but does not explicitly disclose wherein the method further comprises mapping relationships between correlated features and states, wherein the mapping relationships includes: performing a regressive fit for each state to determine the relationships between the corresponding state and features; or plotting a ratio of correlated variables against programming parameters.
However, Miocinovic teaches systems and methods for automatically determining patient-specific set of stimulation parameters based on applying an optimization algorithm (see abstract). The system (fig. 1) teaches wherein a Gaussian Process Regression Model performs a regressive fit for each state/clinical response score to determine the relationship between corresponding states/clinical scores and features/stimulation parameters (see para [0085]-[0087] and para [0092]-[0093]).
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, the spinal cord oscillation sensing of Saab, and the regression method of Miocinovic to arrive at the claimed invention. Such modification would improve the system by optimizing the closed-loop neuromodulation system, allowing for more precise and effective neuromodulation treatment for each patient.
Conclusion
In regard to claim 18, no art is provided for this claim, however it is not allowable unless the current 112b rejection is overcome.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARMEL J WEBSTER whose telephone number is (703)756-5960. The examiner can normally be reached Monday-Friday 7:30am-5:00pm.
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, NIKETA PATEL can be reached at 571-272-4156. 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.
/K.J.W./Examiner, Art Unit 3792
/NIKETA PATEL/Supervisory Patent Examiner, Art Unit 3792
Prosecution Insights