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 06/24/2026 have been fully considered but they are not persuasive.
Regarding Applicant’s first argument, that the sensing of Moffitt is fixed while Applicant’s system has ER features collected simultaneously from a group of electrodes at their respective positions, with the sensing electrodes being distinct from the stimulating electrodes, is unpersuasive as it is not commensurate with the scope of the claims. Applicant’s Claim 1 makes no mention of any variability or adjustment of the sensing locations of the claims, just that the sensing electrodes are at respective sensing locations. It also does not require simultaneous detection as argued by Applicant. As cited, and as the claims currently read, Moffitt teaches the claim limitations. Moffitt also further teaches the sensing electrodes being distinct from the stimulating electrodes, as Para. 0063 and 0064 disclose the system determining which electrodes are sensing electrodes
Regarding Applicant’s second argument, that it is improper to cite Paras. 0086 and Para. 0100 together for the same limitation as the paragraphs refer to separate functions, is unpersuasive. Para. 0094 states, “According to some embodiments, ERNA responses may be used both during the fitting process and during ongoing therapy as a biomarker or indicator of effective stimulation and/or of patient state. For example, the patient's IPG may be configured with one or more algorithms to determine ERNA responses to stimulation. For example, the algorithms may be configured as part of the sensing/feedback algorithm 140 executable in the control circuitry 102 of the IPG 10 (FIG. 6). Thus, according to some aspects of the disclosure, the fitting process may address two considerations: (1) determining the optimum stimulation parameters for providing therapy to the patient, and (2) determining optimum parameters for evoking ERNA responses for use as a biomarker/feedback variable”. This shows that the aspects of Para. 0086 occur in an ongoing manner to the active stimulation system occurring in Para. 0100.
Therefore, the rejections under U.S.C. 102 are maintained, and updated to account for the newly amended claim limitations.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication 20220040486 awarded to Moffitt, hereinafter Moffitt (as cited on the IDS dated 07/25/2024).
Regarding Claims 1 and 13, Moffitt teaches a neuromodulation system and method (abstract), comprising: at least one lead (leads 17, Fig. 1a) including a plurality of electrodes (electrode array 17, Fig. 1a); an electrostimulator configured to provide electrostimulation to a neural target of a patient (IPG 10, Fig. 1a, Para. 0035); a sensing circuit configured to sense an evoked response (ER) to the electrostimulation (control circuitry 102, Fig. 6, Para. 0061, “FIG. 6 shows an IPG 100 that includes stimulation and sensing functionality. (An ETS as described earlier could also include stimulation and sensing capabilities). FIG. 6 shows further details of the circuitry in an IPG 100 that can provide stimulation and sensing innate or evoked signals. The IPG 100 includes control circuitry 102, which may comprise a microcontroller”); and a controller circuit operably connected to the electrostimulator and the sensing circuit (Para. 0062, “The control circuitry 102 may be configured with one or more sensing/feedback algorithms 140 that are configured to cause the IPG to make certain adjustments and/or take certain actions based on the sensed signal. For example, embodiments of the disclosed IPG are configured to sense evoked neural responses referred to as evoked resonant neural responses (ERNAs)”), the controller circuit configured to: in response to the electrostimulation delivered to the neural target in accordance with a stimulation setting via a stimulating electrode on the at least one lead, collect sensed ERs (Para. 0062, “The control circuitry 102 may be configured with one or more sensing/feedback algorithms 140 that are configured to cause the IPG to make certain adjustments and/or take certain actions based on the sensed signal. For example, embodiments of the disclosed IPG are configured to sense evoked neural responses referred to as evoked resonant neural responses (ERNAs)”) from each of a group of sensing electrodes positioned at respective sensing locations, the sensing electrodes selected from the plurality of electrodes on the at least one lead (Para. 0063, “The IPG 100 also includes stimulation circuitry 28 to produce stimulation at the electrodes 16, which may comprise the stimulation circuitry 28 shown earlier (FIG. 3). A bus 118 provides digital control signals from the control circuitry 102 to one or more PDACs 40.sub.i or NDACs 42.sub.i to produce currents or voltages of prescribed amplitudes (I) for the stimulation pulses, and with the correct timing (PW, F) at selected electrodes”) and distinct from the stimulating electrode (Para. 0094, “According to some embodiments, ERNA responses may be used both during the fitting process and during ongoing therapy as a biomarker or indicator of effective stimulation and/or of patient state. For example, the patient's IPG may be configured with one or more algorithms to determine ERNA responses to stimulation. For example, the algorithms may be configured as part of the sensing/feedback algorithm 140 executable in the control circuitry 102 of the IPG 10 (FIG. 6). Thus, according to some aspects of the disclosure, the fitting process may address two considerations: (1) determining the optimum stimulation parameters for providing therapy to the patient, and (2) determining optimum parameters for evoking ERNA responses for use as a biomarker/feedback variable”); generate ER features from the sensed ERs (Para. 0100, “At step 1606, the ERNA algorithm (e.g., the sensing/feedback algorithm 140 of the IPGs microcontroller, FIG. 6) analyzes the ERNA response to extract one or more ERNA parameters”); fit the generated ER features to a model (Para. 0100, “At step 1608, the ERNA algorithm determines if the ERNA parameter(s) are commensurate with a desirable patient state (as determined during the fitting procedure 1500, FIG. 15)”) to represent a spatial distribution of the generated ER features across the sensing locations (Para. 0086, “Thus, a model for source location using measured ERNA responses may be based on the maximum amplitude of the ERNA response and on the slope of the curve of the amplitude as a function of position on the electrode lead. Multiple values for those properties may be determined at different slices in time. The model may also consider other aspects, such as the patient's medication state”); and based at least in part on a comparison of the fitted model to acceptance criteria (Para. 0086, “Thus, a model for source location using measured ERNA responses may be based on the maximum amplitude of the ERNA response and on the slope of the curve of the amplitude as a function of position on the electrode lead. Multiple values for those properties may be determined at different slices in time. The model may also consider other aspects, such as the patient's medication state”), provide a recommendation to a user to reposition the at least one lead (Para. 0088, “Thus, according to some embodiments, the system may use a source localization technique, as described above, to determine the relative position of the electrode lead with respect to the ERNA response. The UI of the system, such as UI 1000 (FIG. 10), may present information relating to the location of the ERNA source and/or feedback regarding how to move the electrode lead”) or to adjust the stimulation setting to cause the fitted model to compare more favorably to the acceptance criteria (Para. 0099, “Thus, the fitting process may involve determining interrogation waveforms/locations as well as determining therapy waveforms/locations. For example, the clinician may try different candidate interrogation waveforms to determine which interrogation waveform allows the best sensing of ERNA responses”).
Regarding Claims 2-3 and 14, Moffitt teaches the inventions above, wherein the at least one lead includes a deep brain stimulation (DBS) lead, and wherein the electrostimulator is configured to provide DBS to a brain target of the patient in accordance with a stimulation setting based on the ER features or the fitted model of the ER features (Para. 0015) wherein the plurality of electrodes include one or more ring electrodes disposed at respective longitudinal positions along a length of the at least one lead (Figs. 1a/1b), or one or more rows of segmented electrodes where each row comprises segmented electrodes disposed about a circumference of the at least one lead at a specific longitudinal position (Figs. 1a/1b), wherein the stimulating electrode and the group of selected sensing electrodes are each selected from the one or more ring electrodes or the one or more rows of segmented electrodes (Paras. 0035-0036).
Regarding Claim 4, Moffitt teaches the neuromodulation system of claim 3, wherein the sensed ERs include ERs sensed from multiple longitudinal sensing locations corresponding to the selected sensing electrodes along the length of the at least one lead (Paras. 0007 and 0036), wherein the fitted model represents a longitudinal distribution of the ER features across the multiple longitudinal sensing locations (Para. 0086).
Regarding Claim 5, Moffitt teaches the neuromodulation system of claim 3, wherein the sensed ERs include ERs sensed from multiple circumferential sensing locations corresponding to the selected sensing electrodes about a circumference at a specific longitudinal position of the at least one lead (Para. 0007 and Para. 0036), wherein the fitted model represents a directional distribution of the ER features across the multiple circumferential sensing locations (Paras. 0087-0088).
Regarding Claim 6, Moffitt teaches the neuromodulation system of claim 1, wherein the controller circuit is configured to display on a user interface one or more of the sensed ERs, the generated ER features, the fitted model representing the spatial distribution of the generated ER features (Para. 0088), or the acceptance criteria (Para. 0093).
Regarding Claims 7 and 15, Moffitt teaches the inventions above, wherein the fitted model includes at least one of a parametric model (Para. 0100, “Kalman filter”).
Regarding Claims 8 and 16, Moffitt teaches the inventions above, wherein the controller circuit is configured to: determine a model parameter or feature of the fitted model (Para. 0100); and provide the recommendation to reposition the at least one lead or to adjust the stimulation setting based at least in part on a comparison of the determined model parameter or feature to a target parameter or feature value, the repositioning of the at least one lead (Para. 0088) or the adjustment of the stimulation setting causing the determined model parameter or feature to fall within a margin of the target parameter or feature value (Para. 0099).
Regarding Claims 9 and 17, Moffitt teaches the inventions above, wherein the model parameter or feature includes one or more parameters of a parametric model, and wherein the acceptance criteria includes an ER target location, wherein the controller circuit is configured to determine an ER distribution center of the generated ER features based at least in part on the one or more parameters of the parametric model, and to estimate a distance between the determined distribution center and the ER target location (Para. 0086).
Regarding Claims 10 and 18, Moffitt teaches the inventions above, wherein the model parameter or feature includes an amplitude (Para. 0086), a spatial location (Para. 0086), wherein the controller circuit is configured to provide the recommendation to reposition the at least one lead or to adjust the stimulation setting to cause the spatial location of the local peak to fall within a margin of a target location of ER peak (Para. 0086).
Regarding Claims 11 and 19, Moffitt teaches the inventions above, wherein the model parameter or feature includes one or more of a positive peak amplitude, wherein the controller circuit is configured to provide the recommendation to reposition the at least one lead or to adjust the stimulation setting based at least in part on a comparison of the positive peak amplitude to a predetermined threshold or a value range (Para. 0086, “he maximum ERNA response may be used for source localization. Likewise, the variation in ERNA response to stimulation at various positions upon the electrode lead may be used for source localization. FIG. 12B shows the ERNA amplitude as a function of stimulation location (r) along the electrode lead for locations Loc 1 and Loc 2. Notice that the maximum amplitude (A.sub.2, Max) measured for the near location Loc 2 is greater than the maximum amplitude (A.sub.3, Max) measured for the far location Loc 1. Also notice that the slopes (i.e., the derivatives) of the amplitudes, dA.sub.2/dr and dA.sub.1/dr, are different. Generally, for a location (such as Loc 2) that closer to the lead, the slope of the amplitude curve is greater than the slope of the amplitude curve for a more distant ERNA source (like Loc 1). Thus, a model for source location using measured ERNA responses may be based on the maximum amplitude of the ERNA response and on the slope of the curve of the amplitude as a function of position on the electrode lead. Multiple values for those properties may be determined at different slices in time. The model may also consider other aspects, such as the patient's medication state”).
Regarding Claims 12 and 20, Moffitt teaches the inventions above, wherein the model parameter or feature includes a ratio of a positive peak amplitude of the fitted model within a range defined by the sensing locations (Fig. 12b), wherein the controller circuit is configured to provide the recommendation to reposition the at least one lead or to adjust the stimulation setting to cause the ratio of the positive peak amplitude to the negative peak amplitude to exceed a predetermined threshold or fall within a predetermined value range (Para. 0086).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jess Mullins whose telephone number is (571)-272-8977. The examiner can normally be reached between the hours of 9:00 a.m. to 5:00 p.m. PST M-F.
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/JLM/
Examiner, Art Unit 3792
/ALLEN PORTER/Primary Examiner, Art Unit 3796
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