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 .
Claim Objections
Claims 10 and 20 are objected to because of the following informalities: Claims 10 and 20 recite, “the one or more electrodes” in lines 6-7. However, in their independent claims (1 and 11, respectively), the electrodes are referred to as “a plurality of electrodes,” and the recording electrodes are referred to as “a second one or more electrodes.” For the purpose of clarity, please amend claims 10 and 20 to specify that the electrodes in claims 10 and 20 are the second one or more electrodes from claims 1 and 11 (since the second one or more electrodes are for sensing/recording EPs, as are those in claims 10 and 20).
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 20 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.
Regarding claim 20, the claim recites, “the system of claim 9.” However, claim 9 is a method claim, not a system. The Examiner notes that the claim is most likely intended to recite, “the system of claim 19,” and the claim is interpreted as such for examiner. Appropriate correction is required.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-9 and 11-19 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Haddock et al. (US 20230201597 A1, "Haddock").
Regarding independent claim 1, Haddock teaches a method of providing deep brain stimulation (DBS) to a patient's brain (abstract: "Methods and systems for providing stimulation to a patient's brain using one or more electrode leads implanted in the patient's brain are described.") using one or more electrode leads implanted in the patient's brain (Abstract; para. [0029]; Fig. 1A and 1B; "stimulating electrodes 16 via one or more electrode leads"), wherein each of the one or more leads comprises a plurality of electrodes (para. [0029]; Fig. 1A and 1B; "stimulating electrodes 16 via one or more electrode leads"), the method comprising: using a first one or more of the electrodes to provide active stimulation to the patient's brain (claim 1:"using stimulation circuitry of the IPG to cause a first one or more of the plurality of electrodes to provide electrical stimulation to the patient's brain"), using a second one or more of the electrodes to record one or more electrical signals indicative of evoked potentials (EPs) evoked by a target volume of the patient's brain (claim 1: "using sensing circuitry of the IPG to record evoked potentials (EPs) using a second one or more of the plurality of electrodes"), comparing the one or more recorded signals to a plurality of modeled EPs (claim 4: "comparing the extracted features of the recorded new EPs to the new EP features predicted by the activation model"), wherein each of the modeled EPs comprise predicted electrical signals (claim 4: "using the network activation model to predict a change in the EP features that will result from the adjustment of the stimulation, using the network activation model to predict new EP features based on the adjustment to the stimulation, recording new EPs following the adjustment to the stimulation.") at one or more of the electrodes in response to activation of the target volume by modeled stimulation with a predefined set of model stimulation parameters (claim 1: " use a network activation model to estimate a network activation value based on the extracted one or more EP features"; claim 4: "comparing the extracted features of the recorded new EPs to the new EP features predicted by the activation model, and adjusting the network activation model based on the comparison."; Additionally, para. [0005] discloses that parameters are controlled to determine the optimal volume of tissue activation, as well as determining electrode parameters.), and using the comparison to adjust the stimulation (claim 1:"use the network activation value to adjust the stimulation.").
Regarding independent claim 11, Haddock teaches a system for providing deep brain stimulation (DBS) to a patient's brain using one or more electrode leads implanted in the patient's brain (abstract: "Methods and systems for providing stimulation to a patient's brain using one or more electrode leads implanted in the patient's brain are described."), wherein each of the one or more leads comprises a plurality of electrodes (para. [0029]; Fig. 1A and 1B; "stimulating electrodes 16 via one or more electrode leads"), the system comprising: control circuitry (claim 1: "control circuitry") configured to execute a method comprising: using a first one or more of the electrodes to provide active stimulation to the patient's brain (claim 1:"using stimulation circuitry of the IPG to cause a first one or more of the plurality of electrodes to provide electrical stimulation to the patient's brain"), using a second one or more of the electrodes to record one or more electrical signals indicative of evoked potentials (EPs) evoked by a target volume of the patient's brain (claim 1: "using sensing circuitry of the IPG to record evoked potentials (EPs) using a second one or more of the plurality of electrodes"), comparing the one or more recorded signals to a plurality of modeled EPs (claim 4: " comparing the extracted features of the recorded new EPs to the new EP features predicted by the activation model"), wherein each of the modeled EPs comprise predicted electrical signals (claim 4: "using the network activation model to predict a change in the EP features that will result from the adjustment of the stimulation, using the network activation model to predict new EP features based on the adjustment to the stimulation, recording new EPs following the adjustment to the stimulation.") at one or more of the electrodes in response to activation of the target volume by modeled stimulation with a predefined set of model stimulation parameters (claim 1: " use a network activation model to estimate a network activation value based on the extracted one or more EP features"; claim 4: "comparing the extracted features of the recorded new EPs to the new EP features predicted by the activation model, and adjusting the network activation model based on the comparison."; Additionally, para. [0005] discloses that parameters are controlled to determine the optimal volume of tissue activation, as well as determining electrode parameters.), and using the comparison to adjust the stimulation (claim 1:"use the network activation value to adjust the stimulation.").
Regarding claims 2 and 12, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock also teaches the limitations wherein comparing the one or more recorded signal to the modeled EPs comprises extracting one or more features of the recorded signals and comparing the extracted features to corresponding features of the modeled EPs (claim 1: "extract one or more EP features of the recorded EPs, use a network activation model to estimate a network activation value based on the extracted one or more EP features"; claim 4: "using the network activation model to predict new EP features based on the adjustment to the stimulation, recording new EPs following the adjustment to the stimulation, extracting one or more features of the recorded new EPs, comparing the extracted features of the recorded new EPs to the new EP features predicted by the activation model, and adjusting the network activation model based on the comparison.").
Regarding claims 3 and 13, Haddock teaches the method of claim 2 and the system of claim 12 (see rejection above). Haddock further teaches wherein the one or more extracted features comprise one or more of one or more peak heights (para. [0068]:" Thus, ERNA may provide a biomarker for electrode location, which can indicate acceptable or optimal lead placement and/or stimulation field placement for achieving the desired therapeutic response. An example of an ERNA in isolation is illustrated in FIG. 8. The ERNA comprises a number of positive peaks P.sub.n and negative peaks N.sub.n, which may have one or more characteristic amplitudes, lengths, separations, latencies, or other features."; amplitude is peak height; para. [0077]-[0087]: " a height of any peak ), one or more peak-peak heights (para. [0077]-[0087]: "a peak-to-peak height between any two peaks"), areas under one or more peaks (para. [0077]-[0087]: "an area or energy under any peak"), one or more latencies (para. [0068]: "latencies"; para. [0087]: "latencies of any peaks"), and one or more peak-peak ratios (para. [0077]-[0087]: "a ratio of peak heights").
Regarding claims 4 and 14, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein comparing the one or more recorded signal to the modeled EPs comprises overlaying the recorded signals and the modeled EPs. (para. [0065]: "This allows the clinician programmer 70 on which GUI 100 is rendered to overlay the lead image 111 and the electric field image 112 with the tissue imaging information in the visualization interface 106 so that the position of the electric field 112 relative to the various tissue structures 114i can be visualized.").
Regarding claims 5 and 15, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein the modeled EPs are comprised within a look-up table (LUT). (para. [0108]: "Accordingly, some embodiments may rely on mutable routines to periodically adjust (especially, reduce) stimulation to re-establish the internal models' state-change region. These routines may be adaptively scheduled as the system learns the user's behavior, driven by pre-set schedules (e.g., implemented internally in memory as lookup tables)").
Regarding claims 6 and 16, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein adjusting the stimulation comprises adjusting the stimulation to provide stimulation to a larger portion of the target volume. (para. [0005] mentions that the desired goal of the adjusting stimulation parameters is to optimizes target volume activation while minimizing the activation of non-target tissue. Haddock's disclosure implies that optimizing the activation of tissue with a control algorithm entails increasing the volume of the target region where stimulation is provided).
Regarding claims 7 and 17, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein adjusting the stimulation comprises adjusting one or more of an amplitude, pulse width, frequency, duty cycle, or stimulation location. (para. [0035]: "Stimulation parameters typically include amplitude (current I, although a voltage amplitude V can also be used); frequency (f); pulse width (PW) of the pulses."; Also see paras. [0061] and [0077]-[0097]).
Regarding claims 8 and 18, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein adjusting the stimulation comprises adjusting which electrodes are active for providing stimulation (para. [0062]: "Stimulation parameter interface 104 may further allow a user to select the active electrodes—i.e., the electrodes that will receive the prescribed pulses…") and/or adjusting a fractionation of current among the electrodes that are active. (para. [0062]: " Stimulation parameter interface 104 may further allow a user to select the active electrodes—i.e., the electrodes that will receive the prescribed pulses. Selection of the active electrodes and the fractionation of current among the active electrodes can occur in conjunction with a leads interface 102, which can include an image 103 of the one or more leads that have been implanted in the patient.").
Regarding claims 9 and 19, Haddock teaches the method of claim 1 and the system of claim 11 (see rejection above). Haddock further teaches wherein the method further comprises determining the modeled EPs for each of the predefined sets of model stimulation parameters. (claim 5: "the network activation model is a linear estimate derived from the extracted features."; Additionally, para. [0013] explains the process of determining model Eps: “use the model to predict new EP features based on the adjustment to the stimulation, record new EPs following the adjustment to the stimulation, extract one or more features of the recorded new EPs, compare the predicted new EP features with the extracted features of the recorded new EPs, and adjust the model based on the comparison. According to some embodiments, the model is a linear estimate derived from the extracted features.” As disclosed, these new model EP predictions are based on adjusted parameters).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Haddock et al. (US 20230201597 A1, "Haddock") in view of Blum et al. (US 20190015039 A1, “Blum”).
Regarding claim 10, Haddock teaches the method of claim 9 (see 102 rejection above). However, Haddock does not expressly teach wherein determining the modeled EPs comprises: for each of the predefined sets of model stimulation parameters, determining a stimulation field model (SFM) that predicts a volume of tissue activated using the set of model stimulation parameters, determining an overlap region of the SFM with the target volume, and predicting electrical signals that will be sensed at the one or more of the electrodes based on activation of neural elements within the overlap region, and wherein the method further comprises comparing the one or more recorded signals to the predicted electrical signals to predict an overlap of stimulation fields created by the active stimulation with the target volume (Haddock teaches about a visualization interface in para. [0064], but does not disclose that this is an SFM that predicts the volume of activation).
Blum, in the same field of endeavor of implantable electrical stimulation systems and methods, discloses a system and method for estimating the effects of electrical stimulation. Blum discloses a stimulation field model (SFM) that predicts a volume of tissue activated using the set of model stimulation parameters (para. [0009]: "…estimating the region including determining a stimulation field model (SFM) for that first set of stimulation parameters."), determining an overlap region of the SFM with the target volume (para. [0009]: "estimating a degree of overlap between the estimated region of tissue stimulated by one of the first sets of stimulation parameters and a one of the at least one effect region based on the clinical response resulting from stimulation using the one of the first sets of stimulation parameters."), and predicting electrical signals that will be sensed at the one or more of the electrodes based on activation of neural elements within the overlap region (para. [0009]: "the estimated region of tissue stimulated by one of the first sets of stimulation parameters and a one of the at least one effect region based on the clinical response resulting from stimulation using the one of the first sets of stimulation parameters."), and wherein the method further comprises comparing the one or more recorded signals to the predicted electrical signals to predict an overlap of stimulation fields created by the active stimulation with the target volume (para. [0009]: " In at least some embodiments of the system, computer-readable medium, or method, estimating the region including determining a stimulation field model (SFM) for that first set of stimulation parameters. In at least some embodiments of the system, computer-readable medium, or method, determining the spatial relationship further includes estimating a degree of overlap between the estimated region of tissue stimulated by one of the first sets of stimulation parameters and a one of the at least one effect region based on the clinical response resulting from stimulation using the one of the first sets of stimulation parameters."; the estimated (predicted region is compared to the clinical response resulting from the first set of stimulation parameters.; Additionally, see para. [0063] that mentions SFM is a model of the volume of activation: "an estimated stimulation field map, SFM (or volume of activation, VOA)").
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of Haddock to include the stimulation field model and predicted overlap between the model and activation region, as disclosed by Haddock. One of ordinary skill in the art would recognize that an SFM can be used to model stimulation parameters in electrical stimulation leads to optimize therapeutic treatment. By including a step where an SFM is used to predict the overlap between the response region and target volume of activation, one would be able to optimize the volume of activation of a target volume. Therefore, it would have been obvious to include the steps of using an SFM, as disclosed by Blum, to improve the system and method of Haddock.
Regarding claim 10, Haddock teaches the system of claim 19 (see 102 rejection above). However, Haddock does not expressly teach wherein determining the modeled EPs comprises: for each of the predefined sets of model stimulation parameters, determining a stimulation field model (SFM) that predicts a volume of tissue activated using the set of model stimulation parameters, determining an overlap region of the SFM with the target volume, and predicting electrical signals that will be sensed at the one or more of the electrodes based on activation of neural elements within the overlap region (Haddock teaches about a visualization interface in para. [0064], but does not disclose that this is an SFM that predicts the volume of activation).
Blum discloses a stimulation field model (SFM) that predicts a volume of tissue activated using the set of model stimulation parameters (para. [0009]: "…estimating the region including determining a stimulation field model (SFM) for that first set of stimulation parameters."), determining an overlap region of the SFM with the target volume (para. [0009]: "estimating a degree of overlap between the estimated region of tissue stimulated by one of the first sets of stimulation parameters and a one of the at least one effect region based on the clinical response resulting from stimulation using the one of the first sets of stimulation parameters."), and predicting electrical signals that will be sensed at the one or more of the electrodes based on activation of neural elements within the overlap region (para. [0009]: "the estimated region of tissue stimulated by one of the first sets of stimulation parameters and a one of the at least one effect region based on the clinical response resulting from stimulation using the one of the first sets of stimulation parameters.").
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of Haddock to include the stimulation field model and predicted overlap between the model and activation region, as disclosed by Haddock. One of ordinary skill in the art would recognize that an SFM can be used to model stimulation parameters in electrical stimulation leads to optimize therapeutic treatment. By including an SFM to predict the overlap between the response region and target volume of activation, one would be able to optimize the volume of activation of a target volume. Therefore, it would have been obvious to include an SFM, as disclosed by Blum, to improve the system and method of Haddock.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Haddock et al. (US 20220395690 A1) disclose methods and systems for estimating neural activity and are pertinent to the subject matter of independent claims 1 and 11.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OWEN LEWIS MARSH whose telephone number is (571)272-8584. The examiner can normally be reached 7:30am – 5pm (M-Th), 8am – noon (F).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/O.L.M./Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796
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