DETAILED ACTION
Applicant' s arguments, filed 10/08/2025, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 06/13/2025, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-7 and 21-31 are the current claims hereby under examination. Claims 29-31 are withdrawn from consideration by election by original presentation.
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 .
Election/Restrictions
Newly submitted claims 29-31 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons:
Claim 29 includes language directed towards receiving data from an internally-imbedded electrode device, identifying time points that are discontinuous from each other, estimating a number of time points in one or missing packets of unknown duration between the time segments, and realigning the waveform data based on the number of time points
The inventions of claim 1 and claim 29 are unrelated. Inventions are unrelated if it can be shown that they are not disclosed as capable of use together and they have different designs, modes of operation, and effects (MPEP § 802.01 and § 806.06). In the instant case, the different inventions are not capable of use together and/or have materially different modes of operation because the system of claim 1 does not recite the steps of receiving data from an internally-imbedded electrode device, identifying time points that are discontinuous from each other, estimating a number of time points in one or missing packets of unknown duration between the time segments, and realigning the waveform data based on the number of time points.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 29-31 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
Claims 1-7, and 21-28 are hereby the present claims under examination.
All references to Applicant’s specification are made using the paragraph numbers assigned in the US publication of the present application US 2022/0338786 A1.
Priority
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 63/175,838, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. The provisional application 63/175,838 appears to relate to the subject matter of claims 1-2 and 4-7, provisional application 63/175,838 does not appear to relate to the subject matter of claim 3. Provisional application 63/175,838 does not appear to support the claimed subject matter of claims 1-4 and 6 for the same reasons described in the below presented 112(a) written description rejections. In particular, the claimed system appears to include materially different processing methods than those present in the disclosure.
The disclosure of the prior-filed application, Application No. 63/184,891, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. The provisional application 63/184,891 appears to relate to the subject matter of claim 3. Provisional application 63/184,891 does not appear to support the claimed subject matter of claim 1-7 for the same reasons described in the below presented 112(a) written description rejections. In particular, provisional application 63/184,891 appears to describe how to estimate a number of time points in one or more missing packets using system ticks but not phase differences.
Provisional applications 63/175,838, and 63/184,891 in combination appear to provide support for the specification of the present application, but the present disclosure does not appear to support the present claims.
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.
Claims 5, and 7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites “recording a plurality of proximal waveform data received proximal to one or both of a time or a stimulation phase of the waveform data”. It is unclear if this “recording” of data is the same as, related to, or different from “Receive, from the iEEG device, waveform data” of claim 1 line 7. For the purposes of this examination, the limitation will be interpreted as extracting a subset of the received data according the proximity to “one or both of a time or a stimulation phase of the waveform data”.
Claim 5 recites “recording a plurality of proximal waveform data received proximal to one or both of a time or a stimulation phase of the waveform data”. The term “proximal” as used in this instance, is a relative term which renders the claim indefinite. The term “proximal” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. In particular, it is unclear how close the “proximal” waveform data must be to the time or stimulation phase of the waveform data to be considered “proximal waveform data”. For the purposes of this examination, any data including a stimulation artifact will be considered “proximal waveform data”.
Claim 7 recites “generate the filtered waveform data in real-time” but it is unclear if this limitation is the same as, related to, or different from “generate filtered waveform data” of claim 1 line 14. For the purposes of this examination, the limitations will be interpreted as referring to the same generation step and will be interpreted in the same manner as described above.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-4, 6, 22-24, and 26-28 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “determine, based on a regularization of the waveform data, a stimulation period relative to a sampling rate” however the specification does not appear to utilize “regularization” of waveform data to identify a stimulation period. Paragraphs 0064-0068 and Fig. 4 describe how the stimulation period is determined by identifying the candidate period with the smallest deviation from an estimated template. This process is not described as “regularization” and the common meaning of “regularization” as defined by Merriam webster is “to make regular by conformance to law, rules, or custom” which does not match the described method of the specification. This rejection is further applied to the similar recitations of claim 24.
Claim 1 recites “identify, based on the waveform data and the stimulation period, a stimulation artifact” the specification does not support the breadth of this limitation. The specification is directed towards a particular method of identifying the stimulation artifact as described in paragraph 0069. The specification does not fully support the claimed identification of a stimulation artifact using any possible identification method involving the waveform data and stimulation period. This rejection is further applied to the similar recitations of claim 24.
Claim 1 recites “adaptively applying stimulation to the patient-specific area of interest for treating a neurological condition based on the filtered waveform” but the specification does not appear to describe how the stimulation is “adaptively” applied based on the filtered waveform. Paragraph 0052 of the specification recites that adaptive neurostimulation systems have a need for removing stimulation artifacts from recorded signals. But does not appear to describe how the filtered waveform data is used to adapt the stimulation. Paragraphs 0054-0055 further state that the filtering may allow for closed-loop control of stimulation amplitude but such a statement of functionality is insufficient to support the claim language. The specification does not appear to describe how the filtered waveform data is processed or otherwise considered to adjust the stimulation in specific ways. This rejection is further applied to the similar recitations of claim 24.
Claim 1 recites “for treating a neurological condition” but the specification appears to describe that the treatment is applied to the conditions listed in paragraph 0052 and newly added claim 21. The full scope of “a neurological condition” being any neurological condition is not supported. This rejection is further applied to the similar recitations of claim 24.
Claim 2 recites “estimating, based on the candidate stimulation period, a waveform template” which appears to indicate that the estimation of the waveform template is based on the candidate stimulation period. However paragraph 0065 which describes the method of Fig. 4 does not indicate that the waveform template estimation is “based on” the candidate stimulation period. Rather the specification appears to indicate that a waveform template is estimated for each of the candidate stimulation periods but does not appear to describe any particular connection between the waveform template estimation and the candidate period. The specification does not appear to support the estimation of the waveform template being “based on” the candidate stimulation period. Furthermore, the specification does not appear to describe how the “waveform template” is estimated. Paragraph 0065 merely provides a statement of functionality stating that the waveform template is estimated for each candidate period but does not appear to describe how this “estimation” takes place, what factors are considered, and how those factors are utilized to result in an estimated waveform template.
Claim 3 recites “estimating, based on the one or more phase shifts, a number of time points in one or more missing packets of unknown data;” however the specification does not appear to disclose an estimation method for determining a number of time points in one or more missing packets of data based on one or more phase shifts. In particular, paragraph 0076 described a method of determining a number of samples, or time points, in one or more missing packets of unknown data using the system ticks of the preceding and following data packets, but does not appear to utilize the phase shift to determine the number of missing samples, or time points. Furthermore, paragraph 0111 describes how the model may handle phase shifts in data, but explicitly states that the number of missing samples is unknown. It would appear that the specification does not support the estimation of a number of time points in one or more missing packets based on phase shift data. This rejection is further applied to the similar recitations of claim 28.
Claim 4 recites “identify the stimulation artifact by applying Nadaraya-Watson Kernel regression and a linear filter to the waveform data and the stimulation period” but the specification does not appear to describe how this regression and linear filter is applied to the waveform data and stimulation period and how the regression and linear filter result in the identification of the stimulation artifact. In particular, the specification only references Nadaraya-Watson Kernel regression in paragraph 0008 which only provides a mere statement of functionality which is insufficient to support the claimed identification step.
Claim 6 recites “a third design parameter that controls a minimum duration for the candidate stimulation period” but the specification does not appear to describe such a design parameter. Paragraphs 0060-0063 appear to describe what parameters are used for artifact estimation and the number of time bins and number of skipped time bins are both listed as parameters but there does not appear to be a design parameter limiting the minimum duration for the candidate stimulation period. In particular the parameter Dperiod does not appear to be defined as a minimum duration for the candidate stimulation period but rather defined as a distance on the timescale from the artifact period as described in paragraph 0069.
Claim 22 recites “detecting a biomarker associated with the neurological disorder from the filtered waveform data” but the specification does not appear to detail such a detection process. In particular, paragraph 0052 recites that there may not be definitive biomarkers for OCD, TRD, or chronic pain. Additionally, paragraphs 0054-0055 recite that the PARRM algorithm can be used to remove stimulation artifacts and may further provide biomarker detection but no description of how biomarker detection is performed, or what biomarkers are being detected, is provided. The specification appears to provide only a statement of functionality that the algorithm may further detect biomarkers associated with the neurological disorders which is insufficient to support the claimed scope of detecting any biomarker associated with the neurological disorders. This rejection is further applied to the similar recitations of claim 26.
Claim 22 recites “applying a therapeutically effective amplitude for the stimulation based on the biomarker” but the specification does not appear to describe how the amplitude of stimulation is determined based on the biomarker. Paragraph 0055 provides a variety of different frequencies of treatment which correspond to different neurological conditions but does not describe how the biomarker is used to select the frequency utilized. Paragraph 0055 further provides only a statement of functionality that the feature estimation can be used to control the amplitude of stimulation. No particular method of how the features are used to determine the amplitude is provided. Paragraphs 0093-0094 further describe how the amplitude may be varied but do not appear to relate the amplitude to the biomarker. This rejection is further applied to the similar recitations of claim 26.
Claim 23 recites “performing, via the iEEG device, deep brain stimulation of the patient-specific area of interest is performed with a first signal amplitude less than a therapeutically effective amplitude, and wherein adaptively applying the stimulation to the patient-specific area of interest for treating the neurological condition based on the filtered waveform data is performed with a second signal amplitude of the therapeutically effective amplitude” but the specification does not appear to describe such stimulation. Paragraphs 0094-0095 describe how the amplitude may be varied when performing loss estimations but do not recite that the estimations may be performed using stimulation amplitudes below therapeutically effective thresholds. Furthermore, paragraphs 0101-0102 recite that periodic estimation of lost packets (PELP) may in theory be performed using stimulation amplitudes below therapeutic amplitudes but PELP estimation is separate and distinct from the identification and subtraction of the stimulation artifact performed using the DBS of the patient specific area of interest as recited in claim 1. The specification does not appear to describe the such a process using stimulations that are below the therapeutically effective thresholds. Additionally, the specification does not appear to describe how stimulation below a therapeutically effective threshold would result in filtered waveform that can be used to adaptively apply stimulation for treating the neurological condition as recited by claim 1 and seemingly supported by paragraph 0052. This rejection is further applied to the similar recitations of claim 27.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 5, 21-22, and 24-26 are rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto “A template subtraction method for stimulus artifact removal in high-frequency deep brain stimulation” published 01/30/2002 by the Journal of Neuroscience Methods, retrieved 06/26/2025 from ScienceDirect, pages 1-6 in view of Kahana US Patent Application Publication Number US 2018/0021579 A1 hereinafter Kahana.
Regarding claim 1, Hashimoto teaches a system for reconstruction and removal of electrical stimulation artifacts during deep brain stimulation (Abstract), the system comprising:
an intracranial electroencephalography (iEEG) device (Section 2.2 Recording Sessions: the recording electrode parallelling the stimulation electrode);
one or more processors (Section 2.4 Operating Procedure paragraph 2: An IBM compatible PC); and
non-transitory memory storing instructions (Section 2.4 Operating Procedure paragraph 2: An IBM compatible PC)) that, when executed by the one or more processors, cause the one or more processors to:
performing, via the iEEG device, deep brain stimulation of a patient-specific area of interest (Section 2.1 DBS system: square pulses of constant voltage were delivered; Fig. 2: trigger stimulus artifact)
receive, from the iEEG device, waveform data caused by a deep brain stimulation of the patient-specific area of interest (Section 2.4 Operating Procedure paragraph 2: the playback signal data of each session are read; Fig 2: read data stream);
determine, based on a regularization of the waveform data, a stimulation period (Section 2.4 Operating Procedure paragraphs 2-3: the stimulus artifacts are triggered using a voltage level window discriminator Thus it would seem that stimulus artifacts are identified by spikes outside of normal variations in the data which is considered to anticipate “regularization of the data”; all peri-stimulus segments are identified; Fig. 2: stimulation period is identified) relative to a sampling rate (Section 2.4 Operating Procedure paragraph 5: an optimization procedure to compensate for sampling time variation, templates are compared to individual traces to find the template with the smallest difference);
identify, based on the waveform data and the stimulation period, a stimulation artifact (Section 2.4 Operating Procedure paragraph 3: the template of the stimulus artifact is constructed using all the identified stimulus segments and by averaging the data; Fig. 3A and 3B);
subtract the stimulation artifact from the waveform data (Section 2.4 Operating Procedure paragraph 3: the stimulus artifact is subtracted from the individual traces; Fig. 3C); to
generate filtered waveform data indicating an absence of the stimulation artifact (Section 2.4 Operating Procedure paragraph 3: after template subtraction only a small residual artifact remains and the period during which neuronal activity may be discriminated become significantly longer; Fig. 3C).
Hashimoto fails to further disclose the system including receiving the waveform data caused by the DBS wirelessly and adaptively applying stimulation to the patient-specific area of interest for treating a neurological condition based on the filtered waveform data
Kahana teaches a method for delivering electrical stimulation to alter a cognitive state of a user, the method comprising: monitoring a brain signal from the user via one or more intracranial electrodes implanted in the brain of the user while the user is presented with a stimulus; comparing the brain signal to a testing phase biomarker, wherein the testing phase biomarker is derived from a cognitive test performed on a contributor during a testing phase; delivering electrical stimulation to a brain of the user based on the comparing step to steer the brain of the user towards a high performance cognitive state (Abstract). Thus, Kahana falls within the same field of endeavor as Applicant’s invention.
Kahana teaches the use of an implantable deep brain stimulation device which may wirelessly transmit monitored brain signal data to a testing device. The device may include ACTIVA PC+S developed by Medtronic (Paragraphs 0097-0100). Kahana further teaches adaptively applying stimulation to a patient-specific region of interest based on signals received from the patient’s brain and biomarkers derived therefrom. The stimulation amplitude, frequency pulse width, and other parameters may be adjusted to achieve a desired response (Paragraph 0117-0120). The desired response may be treatment of a neurological condition (Paragraph 0062).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to incorporate the wireless data transmission and adjustment of stimulation parameters as taught by Kahana into the system of Hashimoto because using wireless transmission is a simple substitution of one known element for another with no surprising technical effect and incorporating the adjustment of stimulation parameters based on biomarkers derived from recorded signals would allow the system of modified Hashimoto to better tailor the stimulation pulses to the particular user and their desired treatment outcome.
Regarding claim 24, Hashimoto teaches a method (Abstract), comprising:
performing deep brain stimulation of a patient-specific area of interest via an intracranial electroencephalography (iEEG) device (Section 2.1 DBS system: square pulses of constant voltage were delivered; Fig. 2: trigger stimulus artifact; Section 2.2 Recording Sessions: the recording electrode parallelling the stimulation electrode);
receiving, from the iEEG device, waveform data caused by the deep brain stimulation of the patient-specific area of interest (Section 2.4 Operating Procedure paragraph 2: the playback signal data of each session are read; Fig 2: read data stream);
determining, based on a regularization of the waveform data, a stimulation period (Section 2.4 Operating Procedure paragraphs 2-3: the stimulus artifacts are triggered using a voltage level window discriminator Thus it would seem that stimulus artifacts are identified by spikes outside of normal variations in the data which is considered to anticipate “regularization of the data”; all peri-stimulus segments are identified; Fig. 2: stimulation period is identified) relative to a sampling rate of the waveform data (Section 2.4 Operating Procedure paragraph 5: an optimization procedure to compensate for sampling time variation, templates are compared to individual traces to find the template with the smallest difference);
identifying, based on the waveform data and the stimulation period, a stimulation artifact (Section 2.4 Operating Procedure paragraph 3: the template of the stimulus artifact is constructed using all the identified stimulus segments and by averaging the data; Fig. 3A and 3B);
subtracting the stimulation artifact from the waveform data (Section 2.4 Operating Procedure paragraph 3: the stimulus artifact is subtracted from the individual traces; Fig. 3C) to generate filtered waveform data indicating an absence of the stimulation artifact (Section 2.4 Operating Procedure paragraph 3: after template subtraction only a small residual artifact remains and the period during which neuronal activity may be discriminated become significantly longer; Fig. 3C); and
Hashimoto fails to further disclose the method including receiving the waveform data caused by the DBS wirelessly and applying stimulation to the patient-specific area of interest for treating a neurological condition based on the filtered waveform data.
Kahana teaches the use of an implantable deep brain stimulation device which may wirelessly transmit monitored brain signal data to a testing device. The device may include ACTIVA PC+S developed by Medtronic (Paragraphs 0097-0100). Kahana further teaches adaptively applying stimulation to a patient-specific region of interest based on signals received from the patient’s brain and biomarkers derived therefrom. The stimulation amplitude, frequency pulse width, and other parameters may be adjusted to achieve a desired response (Paragraph 0117-0120). The desired response may be treatment of a neurological condition (Paragraph 0062).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to incorporate the wireless data transmission and adjustment of stimulation parameters as taught by Kahana into the method of Hashimoto because using wireless transmission is a simple substitution of one known element for another with no surprising technical effect and incorporating the adjustment of stimulation parameters based on biomarkers derived from recorded signals would allow the system of modified Hashimoto to better tailor the stimulation pulses to the particular user and their desired treatment outcome.
Regarding claim 2, Hashimoto in view of Kahana teaches the system of claim 1. Modified Hashimoto further discloses the system wherein the instructions, when executed, cause the one or more processors to determine the stimulation period relative to the sampling rate by: performing one or more iterations of: selecting, from the waveform data, a candidate stimulation period; estimating, based on the candidate stimulation period, a waveform template; and quantifying a deviation of the candidate stimulation period from the waveform template; and identifying, as the stimulation period relative to the sampling rate, the candidate stimulation period associated with a quantified deviation that satisfies a threshold (Section 2.4 Operating Procedure paragraph 5: an optimization procedure to compensate for sampling time variation, multiple waveform templates are compared to individually selected traces to quantify deviations and selecting the template with the smallest difference).
Regarding claim 5, Hashimoto in view of Kahana teaches the system of claim 1. Modified Hashimoto further discloses the system wherein the instructions, when executed, cause the one or more processors to identify the stimulation artifact by: recording a plurality of proximal waveform data received proximal to one or both of a time or a stimulation phase of the received waveform data; averaging the recorded proximal waveform data; and identifying, based on the averaged recorded proximal waveform data, the stimulation artifact (Section 2.4 Operating Procedure paragraph 3: the template of the stimulus artifact is constructed using all the identified stimulus segments and by averaging the data; Fig. 3A and 3B The use of data during the stimulation period is considered analogous to “proximal waveform data”).
Regarding claims 21 and 25, Hashimoto in view of Kahana teaches the system of claim 1 and method of claim 24. Modified Hashimoto further discloses the system and method wherein the deep brain stimulation is applied for treatment of a neurological disorder selected from the group consisting of: Parkinson's Disease; Epilepsy; and Obsessive Compulsive Disorder; Essential Tremor; Treatment Resistant Depression (TRD); and Chronic pain (Section 2.1: DBS system: The stimulation pulses were chosen based on the greatest effect on Parkinsonian motor symptoms; Section 1: Introduction: DBS is reported to be effective for the treatment of tremor and Parkinson’s Disease. These limitations at least suggest that the system of Hashimoto is directed towards the treatment of Parkinson’s Disease and/or tremors).
Regarding claims 22 and 26, Hashimoto in view of Kahana teaches the system of claim 21 and method of claim 24. Modified Hashimoto fails to further discloses the system and method wherein adaptively applying the stimulation to the patient-specific area of interest for treating a neurological condition based on the filtered waveform data comprises: detecting a biomarker associated with the neurological disorder from the filtered waveform data; and applying a therapeutically effective amplitude for the stimulation based on the biomarker.
Kahana teaches adaptively applying stimulation to a patient-specific region of interest based on signals received from the patient’s brain and biomarkers derived therefrom. The stimulation amplitude, frequency pulse width, and other parameters may be adjusted to achieve a desired response (Paragraph 0117-0120). The desired response may be treatment of a neurological condition (Paragraph 0062).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to incorporate the adjustment of stimulation parameters based on biomarkers as taught by Kahana into the system and method of Hashimoto because incorporating the adjustment of stimulation parameters based on biomarkers derived from recorded signals would allow the system of modified Hashimoto to better tailor the stimulation pulses to the particular user and their desired treatment outcome.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Hashimoto in view of Kahana as applied to claim 1 above and further in view of Shanechi US Patent Application Publication Number US 2019/0200934 A1 hereinafter Shanechi
Regarding claim 7, Hashimoto in view of Kahana teaches the system of claim 1. Modified Hashimoto further discloses the system wherein the instructions, when executed, cause the one or more processors to receive the waveform data by: recording, in real-time and via electrodes connected to the patient-specific area of interest, an iEEG scan (Section 2.2 Recording session: the neuronal discharge was recorded).
Modified Hashimoto fails to further disclose the system wherein the instructions, when executed, cause the one or more processors to generate the filtered waveform data in real-time.
Shanechi teaches time-efficient identification of a brain network input-output (IO) dynamics model for brain stimulation includes generating an input stochastic-switched noise-modulated waveform characterized by at least one parameter modulated according to a stochastic-switched noise sequence, inputting the input stochastic-switched noise-modulated waveform to a clinical brain-response system, recording one or more time-correlated outputs of the clinical brain-response system responsive to the input stochastic-switched noise-modulated waveform, and identifying a brain network IO dynamics model that optimally correlates the input stochastic-switched noise-modulated waveform to the one or more time-delimited outputs of the clinical brain-response system. A desired brain response to an input electrical signal may be obtained using the model, such as by modulating the input electrical signal using a closed-loop control algorithm based on the brain network IO dynamics model (Abstract). Thus, Shanechi falls within the same field of endeavor as Applicant’s invention.
Shanechi teaches that in deep brain stimulation scenarios, neural signals are contaminated by stimulation artifacts what typically have a much higher amplitude than neural signals. Shanechi teaches that a hardware processor may remove stimulation artifacts in real time using template subtraction artifact removal algorithm (Paragraph 0092)
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of the invention to configure the system of modified Hashimoto to operate utilizing real-time data as taught by Shanechi because configuring the system to utilize real-time data would allow the system to be implemented into a wider variety of Applications including closed loop real-time stimulation and monitoring systems such as described in Shanechi (Shanechi: Paragraph 0092). Furthermore, while Shanechi is directed towards the processing of ECoG data, this is still a type of neural data and thus the system of Shanechi and its teachings could be readily adapted to other types of neural data including iEEG.
Claims 3-4, 6, 23, and 27-28 are not presently rejected over the prior art but are nonetheless rejected under 35 USC 112 as described above,
Response to Arguments
Applicant's arguments filed 10/08/2025 have been fully considered but they are not persuasive.
Applicant’s amendments to claim 1 are sufficient to overcome the previously presented 35 USC 101 rejection as they successfully implement the abstract idea into the practical application of applying stimulation based on the filtered waveform data.
Applicant argues that claim 3 is not indefinite because breadth is not indefiniteness and the broadest reasonable interpretation (BRI) of the claim is clear.
Applicant’s arguments are not found to be persuasive because while MPEP 2173.04 does recite that breadth is not indefinite it further recites “a claim is indefinite when the boundaries of the protected subject matter are not clearly delineated and the scope is unclear … a genus claim that could be interpreted in such a way that it is not clear which species are covered would be indefinite (e.g., because there is more than one reasonable interpretation of what species are included in the claim) ”. However upon reconsideration of the present claim language the rejection is withdrawn as the claim states that “the stimulation period” is based on the realigned waveform data and does not recite that the identification process, as recited in claim 2, or any other parameter or process is based on or uses the realigned waveform data. The realigned waveform data appears to only be directed towards “the stimulation period” identified at the end of claim 2 and not the recited process of identifying such a period from candidate stimulation periods. As such the rejection is withdrawn as the scope of the claim clearly indicates that the realigned waveform data is only applied to at least some portion of the stimulation period identified at the end of claim 2.
Applicant argues that claim 5 is definite because the claim recites the relationship of the data being “proximal” to one or both of the time or phase of the waveform data.
Applicant’s arguments are not found to be persuasive because, as described in the above 35 USC 1129B) rejection, the term “proximal” itself is indefinite. Furthermore, Applicant does not clarify the relationship of this “recorded” data to the “received” data of claim 1.
Applicant argues that the office action has not considered all of the undue experimentation factors and thus has not set forth a prima facie case for non-enablement of the claims.
Applicant’s arguments are not found to be persuasive because the rejections are directed towards a lack of written description, not enablement.
Applicant argues that Examiners definition of regularization is inconsistent with the field of the present disclosure and provides a definition provided by IBM and Wikipedia which indicate that “regularization” encompasses a range of techniques and/or is used to prevent overfitting. Applicant further contends that the paragraphs 0118-0119 and 0127 of the published application are directed towards fitting methods. Applicant further asserts that one of ordinary skill in the art would know the definition of “regularization” in respect to the fitting problems discussed in the disclosure.
Applicant’s arguments are not found to be persuasive because Applicant’s provided definitions are directed towards machine learning models which is not commensurate in scope with the claimed invention. Additionally, the provided definitions appear to cover a wide range of techniques and thus even if one of ordinary skill in the art were to interpret “regularization” in the described manner then Applicant’s specification would not support the full scope of performing any and all methods of regularization to determine a stimulation period relative to a sampling rate as Applicant’s specification appears to be directed towards a particular determination method. Finally, paragraphs 0118-0119 and 0127 are directed towards the removal of the artifact rather than the identification of the stimulation period and thus Applicant’s arguments that the recited methods of these paragraphs are “regularization” is not found to be persuasive because these paragraphs are not directed towards the step of the method that utilizes “regularization”
Applicant further argues that the Examiner’s citation of paragraph 0069 for citing what the specification teaches in regards to the limitation of “identify, based on the waveform data and the stimulation period, a stimulation artifact” is not commensurate in scope with what the specification supports because paragraph 0069 recites that Fig. 5 is a non-limiting embodiment of the invention and that paragraphs 0130 and 0132 recite that the changes and modifications can be made with departing from the spirit and scope of the invention.
Applicant’s arguments are not found to be persuasive because the specification recites only a single species (a single method of identifying the stimulation artifact) but claims a genus (any and all known and as of yet unknown method of identifying a stimulation artifact based on the waveform data and stimulation period) and the disclosed species is not considered sufficient support for the claimed genus.
Applicant argues that the limitation of “estimating, based on the candidate stimulation period, a waveform template” is supported by paragraph 0065 which recites “determine the simulation period, T, by searching for a period that creates a strongly resolved template” which corresponds to candidate stimulation periods and “the method estimates a waveform template with this period” which corresponds to the waveform template estimation.
This argument is not found to be persuasive because the cited language is a mere statement of functionality and does not describe how the waveform template is estimated using the candidate stimulation period. The specification simply recites that the action is performed.
Applicant argues that the limitation of “estimating based on the one or more phase shifts, a number of time points in one or more missing packets of unknown data” is supported by paragraphs 0108-0109 and 0119-0120 which each refer to phase shifts. Applicant asserts that one of ordinary skill in the art would be enabled by the specification to carry out the recited function.
This argument is not found to be persuasive because the cited paragraphs are each directed towards the removal of the artifact rather than the estimation of a number of time points in missing packets of data. In particular, the phase shift is used as a variable to better define the received data in the functions described by each of these paragraphs. The functions nor the paragraphs themselves make no mention of estimating a number of time points in missing packets of unknown data. The specification does not provide sufficient written description support. The claims are considered to be enabled.
Applicant argues that claim 4 is enabled because one of ordinary skill in the art would be able to apply the known methodology.
Applicant’s arguments are not found to be persuasive because the rejection is directed towards a lack of written description not enablement. The specification does not detail how the claimed regression method is used to achieve the recited outcome.
Applicant argues that claim 6 is enabled because paragraph 0065 includes a discussion regarding a parameter vector which enables a parameter of minimum duration.
This argument is not found to be persuasive because the rejection is directed towards a lack of written description rather than enablement. The specification does not appear to define the minimum duration parameter and further describe how it is used in the claimed processed of averaging the recorded proximal waveform data and identifying the stimulation artifact.
Applicant argues that Hashimoto fails to disclose the use of an intracranial electroencephalogram (iEEG) because Hashimoto described that the implanted electrodes are connected to a device outside of the cranium and thus the device is not an iEEG device.
Applicant’s arguments are not found to be persuasive because they are not commensurate in scope with the claim language. The recitation of “an iEEG device” does not limit the device to being fully implanted within the cranium of the patient. The device of Hashimoto delivers deep brain stimulation and records brainwaves using an implanted electrode. Thus the device is consider an iEEG device.
Applicant’s arguments remaining with respect to claim 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
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/MATTHEW ERIC OGLES/ Examiner, Art Unit 3791
/JASON M SIMS/ Supervisory Patent Examiner, Art Unit 3791