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 Preliminary Amendment
This Office Action is responsive to the preliminary amendment filed 23 December 2025. As per the amendment: claims 1, 13-15, and 20 have been amended, claims 21-22 have been added, and claim 12 has been cancelled. Thus, claims 1-11 and 13-22 are presently pending and under examination.
Response to Arguments
Response to Arguments Regarding 35 U.S.C. § 102/103
Applicant’s arguments, see pg. 7-8, filed 12/23/2025, with respect to the rejection(s) of claim(s) 1, 2, 4, 6, 12, 14-17, 19 and 20 under 35 U.S.C. 102 (a)(1) in under Nelson et al. (US 2014/0358024 A1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Saab (US 2018/0228421 A1), hereinafter Saab.
Applicant has amended independent claims 1, 15, and 20 to recite “a local field potential (LFP) signal received from one or more electrodes disposed in an epidural space adjacent at least one of a cervical, thoracic, or lumbar region of a spinal cord of a patient” and argues that Nelson fails to teach this limitation. Examiner agrees and notes that although Nelson discloses “The location at which the signals are obtained may be adjusted to a disease onset side of the body of patient 12” ([0063]) and where “additional leads or lead segments having one or more electrodes positioned at different target tissue sites, which may be within brain 28 or outside of brain (e.g., proximate to a spinal cord of patient 12, a peripheral nerve of patient 12, a muscle of patient 12, or any other suitable therapy delivery site). The additional leads may be used for delivering different stimulation therapies to respective stimulation sites within patient 12 or for monitoring at least one physiological parameter of patient 12.” ([0076]), Nelson fails to explicitly disclose “a local field potential (LFP) signal received from one or more electrodes disposed in an epidural space adjacent at least one of a cervical, thoracic, or lumbar region of a spinal cord of a patient” and therefore a new rejection has been made under Saab.
Saab teaches a method for detecting neuronal oscillations in the spinal cord for the diagnosis and treatment of pain and disease/disorders of the peripheral and central nervous system ([0002]) wherein the local field potential (LFP) signal is received from one or more electrodes disposed in an epidural space adjacent at least one a cervical, thoracic, or lumbar region of a spinal cord of a patient ([0006] “a) recording local field potential (LFP) waveforms in the spinal cord of the subject;” , [0059] “The methods described herein for detection of neuronal oscillation in the spinal cord may be used for local assessment of pathology in the spinal cord (e.g. at the lumbar level), but may could also be used as a ‘comparator’ when sensors are placed at multiple levels of the spinal cord to assess the ‘relative’ state of pathology (e.g., sensors could be placed at lumbar, thoracic and cervical levels, as well as in the brain).”, [0078] “LFP was recorded from the spinal cord dorsal horn lumbar 4 level in an anesthetized rat using a sharp microelectrode”, [0021] “LFP waveforms may be recorded with one or more sensors positioned in the spinal cord of the subject. In various embodiments, the one or more sensors includes one or more electrodes.”); and apply a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0006] “b) applying fast Fourier transfer (FFT) to convert LFP waveforms from the time domain to the frequency domain, thereby producing a power spectral density (PSD) histogram”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted Nelson’s LFP signals with Saab’s LFP signal received from one or more electrodes disposed in an epidural space adjacent at least one cervical, thoracic, or lumbar region of a spinal cord of a patient, as these prior art references are directed to detecting LFP signals to determine a disease/disorder state of a patient associated with pain. One would be motivated to do this as the spinal cord plays a major role in a pain pathway.
Therefore, claims 1-2, 4, 6, 14-17, and 19-21 are now rejected under 35 U.S.C. 103 (Nelson in view of Saab).
No additional specific arguments were presented for previously set forth 35 U.S.C. 103 rejections of dependent claims 3, 5, 7-11, 13, and 18 nor specifically with respect to the previously cited references: Min, Sen, Fabietti, Abbaspour, and Srivastava.
Therefore, claims 3, 5, 7-11, 13, and 18 remain rejected under 35 U.S.C. 103, as described in detail below.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 30 September 2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
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 13 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 13 currently depends from cancelled claim 12, and therefore the dependency of the claim is indefinite. For examination purposes, claim 13 will be read as if dependent on claim 1, which recites the one or more electrodes disposed in the an epidural space.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-2, 4, 6, 14-17, and 19-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson et al. (US 2014/0358024 A1, previously cited), hereinafter Nelson in view of Saab (US 2018/0228421 A1), hereinafter Saab.
Regarding claim 1, Nelson discloses a system ([0005] “The disclosure describes example systems, devices, and methods for determining a patient state based on activity of a bioelectrical brain signal of a patient in one or more frequency sub-bands of a frequency band of interest”) comprising:
a memory (memory 62) configured to receive and store a local field potential (LFP) signal ([0091] “memory 62 may also store brain signal data generated by sensing module 66 via at least one of electrodes 24, 26”) received from one or more electrodes ([0061] “IMD 16 may include a sensing module that is configured to sense bioelectrical brain signals within one or more regions of brain 28 via a subset of electrodes 24, 26, another set of electrodes, or both.”, [0063] “Example bioelectrical brain signals include, but are not limited to, an electroencephalogram (EEG) signal, an electrocorticogram (ECoG) signal, a LFP sensed from within one or more regions of a patient's brain…The location at which the signals are obtained may be adjusted to a disease onset side of the body of patient 12 or severity of symptoms or disease duration.”); and
processing circuitry (processor 60) configured to:
apply a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0156] “processor 80 generates a spectrogram of the bioelectrical brain signal (124)”, [0041] “The spectral pattern, as well as other frequency domain characteristics of a bioelectrical brain signal, may be determined based on any suitable transform of the sensed bioelectrical brain signal, such as, but not limited to, a Fast Fourier Transform.”); and
determine a change in a physiological state of the patient from the frequency transformed LFP signal ([0134] “The spectrogram provides a three-dimensional plot of the signal strength of the frequency content of a bioelectrical brain signal as it changes over time”, [0156] “processor 80…determines one or more spectral characteristics indicative of one or more patient states (126)”, [0150] “the LFP spectral patterns may also change as a function of the patient state.”).
Nelson fails to explicitly disclose wherein the local field potential (LFP) signal is received from one or more electrodes disposed in an epidural space adjacent at least one of a cervical, thoracis, or lumbar region of a spinal cord of a patient.
However, Saab teaches a method for detecting neuronal oscillations in the spinal cord for the diagnosis and treatment of pain and disease/disorders of the peripheral and central nervous system ([0002]) wherein the local field potential (LFP) signal is received from one or more electrodes disposed in an epidural space adjacent at least one a cervical, thoracic, or lumbar region of a spinal cord of a patient ([0006] “a) recording local field potential (LFP) waveforms in the spinal cord of the subject;” , [0059] “The methods described herein for detection of neuronal oscillation in the spinal cord may be used for local assessment of pathology in the spinal cord (e.g. at the lumbar level), but may could also be used as a ‘comparator’ when sensors are placed at multiple levels of the spinal cord to assess the ‘relative’ state of pathology (e.g., sensors could be placed at lumbar, thoracic and cervical levels, as well as in the brain).”, [0078] “LFP was recorded from the spinal cord dorsal horn lumbar 4 level in an anesthetized rat using a sharp microelectrode”, [0021] “LFP waveforms may be recorded with one or more sensors positioned in the spinal cord of the subject. In various embodiments, the one or more sensors includes one or more electrodes.”); and apply a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0006] “b) applying fast Fourier transfer (FFT) to convert LFP waveforms from the time domain to the frequency domain, thereby producing a power spectral density (PSD) histogram”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted Nelson’s LFP signals with Saab’s LFP signal received from one or more electrodes disposed in an epidural space adjacent at least one cervical, thoracic, or lumbar region of a spinal cord of a patient, as these prior art references are directed to detecting LFP signals to determine a disease/disorder state of a patient associated with pain. One would be motivated to do this as the spinal cord plays a major role in a pain pathway.
Regarding claim 2, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson further discloses wherein to determine the change in the physiological state of the patient, the processing circuitry is further configured to: measure a power of the frequency transformed LFP signal in one or more spectral bands; and determine the change in the physiological state of the patient based on the measured power. ([0149] “The other spectral characteristics that may be indicative of a patient state include, for example, the power level of a bioelectrical brain signal of the patient in one or more frequency sub-bands of the frequency band, a shift in a power distribution (e.g., a peak power or an average power over a particular range of frequencies) between sub-bands of the frequency band”, [0134]-[0135]“The graph shown in FIG. 5 illustrates the power spectra of the LFPs over approximately 24 hours and illustrates how much of the sensed bioelectrical brain signal lies within each given frequency band over a range of frequencies…The spectrogram shown in FIG. 5 indicates that the amplitude (also referred to herein as the "power level" or "activity") in at least one frequency sub-band (e.g., about 18 Hz to about 28 Hz) of the beta frequency band may fluctuate as a function of the medication state of a patient.”, Abstract: “determine a patient state based on the power level of a bioelectrical brain signal of the patient in one or more frequency sub-bands of a frequency band,… such as a shift in a power distribution between sub-bands,… a pattern of the power distribution over one or more frequency sub-bands”).
Regarding claim 4, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson further discloses wherein to determine the change in the physiological state of the patient, the processing circuitry is further configured to: compare respective powers of the frequency transformed LFP signal in two or more spectral bands ; and determine the change in the physiological state of the patient based on the comparison ([0137]-[0139] “As shown in FIG. 6A, in the first time period 112, a power level of the bioelectrical brain signal of the human subject in a first frequency sub-band (e.g., about 13 Hz to about 20 Hz) of the beta frequency band (e.g., about 13 Hz to about 35 Hz) is relatively high, as indicated by the relatively intense color 113 in FIG. 6A. In particular, during time period 112, the peak activity in the beta band occurs in the first frequency sub-band. In a second time period 114, the human subject is under the influence of medication (e.g., a pharmaceutical agent) to mitigate effects of the movement disorder. As shown in FIG. 6A, compared to the first time period 112, the beta band activity in the first frequency sub-band decreases during the second time period 114 in which the human subject is receiving movement disorder therapy and beta band activity in a second frequency sub-band (e.g., about 20 Hz to about 30 Hz) of the beta band increases.…FIG. 6A indicates that a shift in peak power within the beta band between the first and second frequency sub-bands of the beta band may be a biomarker for a positive response to medication. It is believed that the shift in peak power of a frequency band of interest between two or more sub-bands of the frequency band of interest may be a biomarker for other patient states instead of or in addition to the state in which a positive response to medication is observed, such as, but not limited to, a movement state, a sleep state, a speech state, a state in which one or more symptoms of a patient condition are observed, and the like.”).
Regarding claim 6, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson further discloses wherein the processing circuitry is further configured to: determine one or more parameters for electrical stimulation therapy based on the determined change in the physiological state of the patient ([0065] “the processor generates an indication of the determined patient state, controls therapy delivery to the patient based on the determined patient state… For example, the processor can control therapy delivery by, for example, modifying one or more therapy parameter values based on the determined patient state.”).
Regarding claim 14, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson further discloses, wherein the processing circuitry is part of an implantable medical device (IMD) (Figure 2: IMD 16 includes a processor 60), wherein the IMD is configured to be implanted in the patient ([0050] “IMD 16 may be implanted within a subcutaneous pocket in the pectoral region of patient 12. In other examples, IMD 16 may be implanted within other regions of patient 12, such as a subcutaneous pocket in the abdomen or buttocks of patient 12 or proximate the cranium of patient 12”).
Regarding claim 15, Nelson discloses a method ([0005] “The disclosure describes example systems, devices, and methods for determining a patient state based on activity of a bioelectrical brain signal of a patient in one or more frequency sub-bands of a frequency band of interest”) comprising:
receiving, by processing circuitry, a local field potential (LFP) signal received from one or more electrodes ([0061] “IMD 16 may include a sensing module that is configured to sense bioelectrical brain signals within one or more regions of brain 28 via a subset of electrodes 24, 26, another set of electrodes, or both.”, [0063] “Example bioelectrical brain signals include, but are not limited to, an electroencephalogram (EEG) signal, an electrocorticogram (ECoG) signal, a LFP sensed from within one or more regions of a patient's brain…The location at which the signals are obtained may be adjusted to a disease onset side of the body of patient 12 or severity of symptoms or disease duration.”);
applying, by the processing circuitry, a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0156] “processor 80 generates a spectrogram of the bioelectrical brain signal (124)”, [0041] “The spectral pattern, as well as other frequency domain characteristics of a bioelectrical brain signal, may be determined based on any suitable transform of the sensed bioelectrical brain signal, such as, but not limited to, a Fast Fourier Transform.”); and
determining, by the processing circuitry, a change in a physiological state of the patient from the frequency transformed LFP signal ([0134] “The spectrogram provides a three-dimensional plot of the signal strength of the frequency content of a bioelectrical brain signal as it changes over time”, [0156] “processor 80…determines one or more spectral characteristics indicative of one or more patient states (126)”, [0150] “the LFP spectral patterns may also change as a function of the patient state.”).
Nelson fails to explicitly disclose the local field potential (LFP) signal received from one or more electrodes disposed in an epidural space adjacent at least one of a cervical, thoracic, or lumbar region of a spinal cord of a patient.
However, Saab teaches a method for detecting neuronal oscillations in the spinal cord for the diagnosis and treatment of pain and disease/disorders of the peripheral and central nervous system ([0002]) wherein the local field potential (LFP) signal is received from one or more electrodes disposed in an epidural space adjacent at least one a cervical, thoracic, or lumbar region of a spinal cord of a patient ([0006] “a) recording local field potential (LFP) waveforms in the spinal cord of the subject;” , [0059] “The methods described herein for detection of neuronal oscillation in the spinal cord may be used for local assessment of pathology in the spinal cord (e.g. at the lumbar level), but may could also be used as a ‘comparator’ when sensors are placed at multiple levels of the spinal cord to assess the ‘relative’ state of pathology (e.g., sensors could be placed at lumbar, thoracic and cervical levels, as well as in the brain).”, [0078] “LFP was recorded from the spinal cord dorsal horn lumbar 4 level in an anesthetized rat using a sharp microelectrode”, [0021] “LFP waveforms may be recorded with one or more sensors positioned in the spinal cord of the subject. In various embodiments, the one or more sensors includes one or more electrodes.”); and applying a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0006] “b) applying fast Fourier transfer (FFT) to convert LFP waveforms from the time domain to the frequency domain, thereby producing a power spectral density (PSD) histogram”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted Nelson’s LFP signals with Saab’s LFP signal received from one or more electrodes disposed in an epidural space adjacent at least one cervical, thoracic, or lumbar region of a spinal cord of a patient, as these prior art references are directed to detecting LFP signals to determine a disease/disorder state of a patient associated with pain. One would be motivated to do this as the spinal cord plays a major role in a pain pathway.
Regarding claim 16, Nelson in view of Saab teaches the method of claim 15 (as shown above). Nelson further discloses wherein to determining the change in the physiological state of the patient comprises: measuring a power of the frequency transformed LFP signal in one or more spectral bands; and determining the change in the physiological state of the patient based on the measured power ([0149] “The other spectral characteristics that may be indicative of a patient state include, for example, the power level of a bioelectrical brain signal of the patient in one or more frequency sub-bands of the frequency band, a shift in a power distribution (e.g., a peak power or an average power over a particular range of frequencies) between sub-bands of the frequency band”, [0134]-[0135]“The graph shown in FIG. 5 illustrates the power spectra of the LFPs over approximately 24 hours and illustrates how much of the sensed bioelectrical brain signal lies within each given frequency band over a range of frequencies…The spectrogram shown in FIG. 5 indicates that the amplitude (also referred to herein as the "power level" or "activity") in at least one frequency sub-band (e.g., about 18 Hz to about 28 Hz) of the beta frequency band may fluctuate as a function of the medication state of a patient.”, Abstract: “determine a patient state based on the power level of a bioelectrical brain signal of the patient in one or more frequency sub-bands of a frequency band,… such as a shift in a power distribution between sub-bands,… a pattern of the power distribution over one or more frequency sub-bands”).
Regarding claim 17, Nelson in view of Saab teaches the method of claim 15 (as shown above). Nelson discloses wherein determining the change in the physiological state of the patient comprises: comparing respective powers of the frequency transformed LFP signal in two or more spectral bands ; and determining the change in the physiological state of the patient based on the comparison ([0137]-[0139] “As shown in FIG. 6A, in the first time period 112, a power level of the bioelectrical brain signal of the human subject in a first frequency sub-band (e.g., about 13 Hz to about 20 Hz) of the beta frequency band (e.g., about 13 Hz to about 35 Hz) is relatively high, as indicated by the relatively intense color 113 in FIG. 6A. In particular, during time period 112, the peak activity in the beta band occurs in the first frequency sub-band. In a second time period 114, the human subject is under the influence of medication (e.g., a pharmaceutical agent) to mitigate effects of the movement disorder. As shown in FIG. 6A, compared to the first time period 112, the beta band activity in the first frequency sub-band decreases during the second time period 114 in which the human subject is receiving movement disorder therapy and beta band activity in a second frequency sub-band (e.g., about 20 Hz to about 30 Hz) of the beta band increases.…FIG. 6A indicates that a shift in peak power within the beta band between the first and second frequency sub-bands of the beta band may be a biomarker for a positive response to medication. It is believed that the shift in peak power of a frequency band of interest between two or more sub-bands of the frequency band of interest may be a biomarker for other patient states instead of or in addition to the state in which a positive response to medication is observed, such as, but not limited to, a movement state, a sleep state, a speech state, a state in which one or more symptoms of a patient condition are observed, and the like.”).
Regarding claim 19, Nelson in view of Saab teaches the method of claim 15 (as shown above). Nelson further discloses the method further comprising: determining one or more parameters for electrical stimulation therapy based on the determined change in the physiological state of the patient ([0065] “the processor generates an indication of the determined patient state, controls therapy delivery to the patient based on the determined patient state… For example, the processor can control therapy delivery by, for example, modifying one or more therapy parameter values based on the determined patient state.”); and controlling stimulation circuitry to deliver the electrical stimulation therapy according to the one or more parameters ([0122] “processor 60 may take in response to determining the bioelectrical brain signal includes the biomarker associated with a particular patient state includes controlling therapy delivery to the patient based on the determined patient state. In some examples, if the patient state indicates the occurrence of a patient symptom or another state in which therapy delivery is desirable, then processor 60 controls stimulation generator 64 (FIG. 2) to initiate the delivery of electrical stimulation therapy to patient 12 in response to determining the bioelectrical brain signal includes the biomarker, and, therefore, in response to detecting the patient state.”).
Regarding claim 20, Nelson discloses a non-transitory computer-readable medium storing instructions that, when executed, causes one or more processors ([0169] “In one or more examples, the functions described in this disclosure may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on, as one or more instructions or code, a computer-readable medium and executed by a hardware-based processing unit”) to:
receive a local field potential (LFP) signal received from one or more electrodes ([0061] “IMD 16 may include a sensing module that is configured to sense bioelectrical brain signals within one or more regions of brain 28 via a subset of electrodes 24, 26, another set of electrodes, or both.”, [0063] “Example bioelectrical brain signals include, but are not limited to, an electroencephalogram (EEG) signal, an electrocorticogram (ECoG) signal, a LFP sensed from within one or more regions of a patient's brain…The location at which the signals are obtained may be adjusted to a disease onset side of the body of patient 12 or severity of symptoms or disease duration.”);
apply a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0156] “processor 80 generates a spectrogram of the bioelectrical brain signal (124)”, [0041] “The spectral pattern, as well as other frequency domain characteristics of a bioelectrical brain signal, may be determined based on any suitable transform of the sensed bioelectrical brain signal, such as, but not limited to, a Fast Fourier Transform.”); and
determine a change in a physiological state of the patient from the frequency transformed LFP signal ([0134] “The spectrogram provides a three-dimensional plot of the signal strength of the frequency content of a bioelectrical brain signal as it changes over time”, [0156] “processor 80…determines one or more spectral characteristics indicative of one or more patient states (126)”, [0150] “the LFP spectral patterns may also change as a function of the patient state.”).
Nelson fails to explicitly disclose a local field potential (LFP) signal received from one or more electrodes disposed in an epidural space adjacent at least one cervical, thoracic, or lumbar region of a spinal cord of a patient.
However, Saab teaches a method for detecting neuronal oscillations in the spinal cord for the diagnosis and treatment of pain and disease/disorders of the peripheral and central nervous system ([0002]) a local field potential (LFP) signal is received from one or more electrodes disposed in an epidural space adjacent at least one a cervical, thoracic, or lumbar region of a spinal cord of a patient ([0006] “a) recording local field potential (LFP) waveforms in the spinal cord of the subject;” , [0059] “The methods described herein for detection of neuronal oscillation in the spinal cord may be used for local assessment of pathology in the spinal cord (e.g. at the lumbar level), but may could also be used as a ‘comparator’ when sensors are placed at multiple levels of the spinal cord to assess the ‘relative’ state of pathology (e.g., sensors could be placed at lumbar, thoracic and cervical levels, as well as in the brain).”, [0078] “LFP was recorded from the spinal cord dorsal horn lumbar 4 level in an anesthetized rat using a sharp microelectrode”, [0021] “LFP waveforms may be recorded with one or more sensors positioned in the spinal cord of the subject. In various embodiments, the one or more sensors includes one or more electrodes.”); and applying a frequency transform to the LFP signal to create a frequency transformed LFP signal ([0006] “b) applying fast Fourier transfer (FFT) to convert LFP waveforms from the time domain to the frequency domain, thereby producing a power spectral density (PSD) histogram”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted Nelson’s LFP signals with Saab’s LFP signal received from one or more electrodes disposed in an epidural space adjacent at least one cervical, thoracic, or lumbar region of a spinal cord of a patient, as these prior art references are directed to detecting LFP signals to determine a disease/disorder state of a patient associated with pain. One would be motivated to do this as the spinal cord plays a major role in a pain pathway.
Regarding claim 21, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson discloses wherein the processing circuitry is configured to adjust, based on the change to the physiological state of the patient, a value of a stimulation parameter that defines electrical stimulation therapy ([0123] “the patient state indicates the occurrence of a patient symptom or another state in which therapy delivery is desirable, processor 60 may modify one or more stimulation parameter values (or other therapy parameter values in the case of therapy other than electrical stimulation therapy)”) and wherein the system further comprises stimulation circuitry configured to generate, based on the value of the stimulation parameter, the electrical stimulation therapy deliverable to the spinal cord of the patient ([0123] “processor 60 may modify one or more stimulation parameter values (or other therapy parameter values in the case of therapy other than electrical stimulation therapy) with which stimulation generator 64 (FIG. 2) generates electrical stimulation therapy in response to determining the bioelectrical brain signal includes the biomarker, and, therefore, in response to detecting the patient state.”).
Nelson fails to disclose wherein the electrical stimulation therapy deliverable to the spinal cord of the patient.
However, Saab teaches wherein the electrical stimulation therapy deliverable to the spinal cord of the patient ([0011] “d) administering a therapeutic agent to said subject, if there is an increase of one or more of said frequency bands from baseline, absence or occurrence of newly identified frequency bands, and/or shifts in peak amplitude or peak latency.”, [0042] ““therapeutic agent” refers to any agent that produces a healing, curative, stabilizing, or ameliorative effect. An “agent” may also be used to, e.g., stimulate or cause or a response in the subject, e.g., neuronal oscillation in the central nervous system, e.g., spinal cord, e.g. feedback system (including neurofeedback system).”, [0074] “Therapeutic agents may include, pharmacological, non-pharmacological, and neuromodulatory agents (e.g. deep brain stimulation, spinal cord stimulation, transcranial current stimulation, transcranial magnetic stimulation, and ultrasound stimulation).”, emphasis added).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson to incorporate the teachings of Saab to have the electrical stimulation therapy deliverable to the spinal cord of the patient, as these prior art references are directed to detecting LFP signals to determine a disease/disorder state of a patient associated with pain. One would be motivated to do this to be able to treat disorders arising from the spinal cord.
Claim(s) 3, 5, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab as applied to claims 1 and 15 above, and further in view of Min et al. (US 2016/0175594 A1, previously cited), hereinafter Min.
Regarding claim 3, Nelson in view of Saab teaches the system of claim 2 (as shown above). Nelson and Saab, alone or in combination, fail to teach wherein to determine the change in the physiological state of the patient, the processing circuitry is further configured to: determine the change in the physiological state of the patient based on the measured power and one or more of an evoked compound action potentials (ECAPs) signal, an output of accelerometer, a respiration measure, or an electrocardiogram (ECG) signal.
However, Min teaches a system and method for controlling stimulation of nervous tissue of a patient based on the frequency data of an ECAP wherein to determine the change in the physiological state of the patient, the processing circuitry is further configured to: determine the change in the physiological state of the patient based on the measured power and one or more of an evoked compound action potentials (ECAPs) signal ([0043] “The NS system 100 may represent a closed loop neurostimulation device, where the NS device 100 is configured to provide real-time sensing functions evoked compound action potential (ECAP) signals from a dorsal root ganglion lead…. The NS system 100 detects an amount of activity associated with each type of nerve fiber based on the frequency content of the ECAP signals.”, [0057] “The controller 151 may determine whether a frequency content for each of the frequency components exceeds a threshold or falls within an acceptable range, thereby indicating that no pain or an acceptable low level of pain is experienced by the patient.”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Min to determine the change in the physiological state of the patient, the processing circuitry is further configured to: determine the change in the physiological state of the patient based on the measured power and one or more of an evoked compound action potentials (ECAPs) signal, as these prior art references and the instant application are directed to determining patient states based on sensed signals. One would be motivated to do this as this can provide a better insight into the state or functioning of the brain.
Regarding claim 5 and 18, Nelson in view of Saab teaches the system of claim 1 and the method of claim 15 (as shown above). Nelson and Saab, alone or in combination, fail to teach wherein the physiological state of the patient includes one or more of a degree or extent of pain, a degree of sensitivity to pain, a susceptibility of a neural target to transmit or receive information, a susceptibility of a neural target to respond therapeutically to electrical stimulation, or a biochemical state.
However, Min teaches wherein the physiological state of the patient includes one or more of a degree or extent of pain ([0057] “The controller 151 may determine whether a frequency content for each of the frequency components exceeds a threshold or falls within an acceptable range, thereby indicating that no pain or an acceptable low level of pain is experienced by the patient.”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Min to have the physiological state of the patient include one or more of a degree or extend of pain, a degree of sensitivity to pain, a susceptibility of a neural target to transmit or receive information, a susceptibility of a neural target to respond therapeutically to electric stimulation, or a biochemical state, as these prior art references and the instant application are directed to determining patient states based on sensed signals. One would be motivated to do this as pain can negatively impact a patient’s life.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab as applied to claim 1 above, and further in view of Sen, Asok K., Dostrovsky, Jonathan O., Evidence of Intermittency in the Local Field Potentials Recorded from Patients with Parkinson′s Disease: A Wavelet-Based Approach, Computational and Mathematical Methods in Medicine, 8, 658248, 7 pages, 2007. https://doi.org/10.1080/17486700701502363, hereinafter Sen (previously presented).
Regarding claim 7, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson and Saab, alone or in combination, fail to explicitly teach wherein to apply the frequency transform to the LFP signal to create the frequency transformed LFP signal, the processing circuitry is configured to: apply a wavelet transform to the LFP signal to create the frequency transformed LFP signal.
However, Sen teaches recording LFPs from patients with Parkinson’s disease wherein to apply the frequency transform to the LFP signal to create the frequency transformed LFP signal, the processing circuitry is configured to: apply a wavelet transform to the LFP signal to create the frequency transformed LFP signal (pg. 167, 3. Wavelet analysis of intermittency: “we calculated the wavelet power spectrum (WPS) of the LFP signal using CWT”, CWT is defined as continuous wavelet transform).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have substituted the Fourier Transform of Nelson and Saab with the wavelet transform of Sen, as these prior art references are directed to measuring LFP signals. One would be motivated to do this as wavelet transform has many advantages over Fourier transform such as better frequency resolution and more precise temporal resolution, the ability to adjust the time and frequency resolutions in an adaptive fashion, as recognized by Sen (pg. 166, I. Introduction, lines 12-25)
Claim(s) 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab as applied to claim 1 above, in view of M. Fabietti et al., "Neural Network-based Artifact Detection in Local Field Potentials Recorded from Chronically Implanted Neural Probes," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-8, doi: 10.1109/IJCNN48605.2020.9207320., hereinafter Fabietti (previously presented).
Regarding claim 8, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson and Saab, alone or in combination, fail to explicitly teach wherein the processing circuitry is further configured to: remove a confounding signal from the frequency transformed LFP signal.
However, Fabietti teaches an artifact detection tool (Abstract) wherein “The neural recordings known as Local Field Potentials (LFPs) provide important information on how neural circuits operate and relate. Due to the involvement of complex electronic apparatuses in the recording setups, these signals are often significantly contaminated by artifacts generated by a number of internal and external sources. To make the best use of these signals, it is imperative to detect and remove the artifacts from these signals” (Abstract).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Fabietti to have the processing circuitry further configured to: remove a confounding signal from the frequency transformed LFP signal, as these prior art references and the instant application are directed to measuring and analyzing LFP signals. One would be motivated to do this as the presence of noise or artifacts in the signal will result in misdiagnosis, incorrect functioning of Brain-Computer Interfaces (BCI) device, or mislead in the study of the brain’s behavior, as recognized by Fabietti (pg. 1, I. Introduction, Column 2, lines 18-21).
Regarding claim 9, Nelson in view of Saab in view of Fabietti teaches the system of claim 8 (as shown above). Nelson and Saab, alone or in combination, fail to teach wherein the confounding signal is one or more of an electrocardiogram (ECG) signal, a stimulation signal, or an evoked compound action potential (ECAPs) signal.
However, Fabietti teaches wherein the confounding signal is one or more of an electrocardiogram (ECG) (I. Introduction, Column 2, lines 7-9 and 12-13: “Physiological artifacts include electrooculogram, electromyogram, electrocardiogram and others… The electrocardiogram artifact is produced by the electric activity of the heart…”), a stimulation signal (I. Introduction, Column 2, lines 14-15: “Furthermore, LFP can be contaminated with stimulation artifacts during experiments”.), or an evoked compound action potentials (I. Introduction, Column 2, lines 14-17: “Furthermore, LFP can be contaminated with…spiking activity of local neurons and other distal electrical activity in the brain may be present in the recording.”).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Fabietti to have the confounding signal be one or more of an electrocardiogram (ECG) signal, a stimulation signal, or an evoked compound action potential (ECAPs) signal, as these prior art references and the instant application are directed to measuring and analyzing LFP signals. One would be motivated to do this as neural signals are often susceptible these internal (physiological) sources or external (non-physiological) ones, as recognized by Fabietti (pg. 1, I. Introduction, Column 1, line 17- Column 2, line 2).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab in view of Fabietti as applied to claim 9 above, and further in view of Abbaspour S, Fallah A. Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique. J Biomed Phys Eng. 2014 Mar 8;4(1):33-8. PMID: 25505766; PMCID: PMC4258854, hereinafter Abbaspour (previously presented).
Regarding claim 10, Nelson in view of Saab in view of Fabietti teaches the system of claim 9 (as shown above). Nelson, Saab, and Fabietti, alone or in combination, fail to teach wherein to remove the ECG signal from the frequency transformed LFP signal, the processing circuitry is further configured to: identify peaks in the ECG signal; and subtract the ECG peaks from the frequency transformed LFP signal.
However, Abbaspour teaches a method of removing electrocardiogram contamination from signals wherein the method “contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction.” (pg. 33, Methods) which resulted in “a substantial removal of the ECG contamination” (pg. 36, Results).
Although, Abbaspour does not explicitly teach LFP signal, it would have been obvious to one skilled in the art to apply the method of identifying peaks in the ECG signals and subtracting the peaks from the frequency transformed LFP signal, as Fabietti also mentioned the application of artifact subtraction from LFP signals (pg. 2, II. State of the art, Column 1, lines 2-5).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson, Saab and Fabietti to incorporate the teachings of Abbaspour to remove the ECG signal from the frequency transformed LFP signal, the processing circuitry is further configured to: identify peaks in the ECG signal; and subtract the ECG peaks from the frequency transformed LFP signal, as these prior art references and the instant application are directed to sensing body signals. One would be motivated to do this to reduce the contamination in the desired signal.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab as applied to claim 1 above, and further in view of Srivastava et al. (US 2018/0193650 A1, previously cited), hereinafter Srivastava.
Regarding claim 11, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson and Saab, alone or in combination, fail to explicitly teach wherein the processing circuitry is further configured to: initiate a measurement of the LFP signal when the patient is in a supine position.
However, Srivastava teaches a system for managing pain in a subject by sensing one or more physiological signals to determine a pain score/state (Abstract) wherein the processing circuitry is further configured to: initiate a measurement of the LFP signal when the patient is in a supine position ([0097] “the physiological signals may include…neural signals, such as, by way of example of limitation…neural activity signal… the functional signals may include patient posture, gait, balance, physical activity signals, or signals indicating sleep or awake state, among others. Such functional signals may responsively co-variate with a pain episode…In some examples, one or more of the physiological signals may be acquired during a transition of a functional signal, such as changes in posture or when the patient goes to sleep.”).
Although, Srivastava does not explicitly state a supine position, it would be obvious to one skilled in the art that the physiological signal that is acquired during a transition of the posture of the patient, which can vary from standing, sitting, or laying down (i.e. supine).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson to incorporate the teachings of Srivastava to have the processing circuitry is further configured to: initiate a measurement of the LFP signal when the patient is in a supine position, as these prior art references and the instant application are directed to used physiological signals to determine a state of the patient. One would be motivated to do this as the supine position can result in the electrode being closer to the target area.
Claim(s) 13 and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nelson in view of Saab as applied to claim 1 above, and further in view of Harhangi et al. (US 2021/0393965 A1), hereinafter Harhangi.
Regarding claim 13, Nelson in view of Saab teaches the system of claim 1 (as shown above). Nelson further teaches the system further comprising the one or more electrodes ([0076] “one or more electrodes positioned at different target tissue sites, which may be within brain 28 or outside of brain (e.g., proximate to a spinal cord of patient 12, a peripheral nerve of patient 12, a muscle of patient 12, or any other suitable therapy delivery site).”, Figure 1, [0094] “the set of electrodes 24 of lead 20A includes electrodes 24A, 24B, 24C, and 24D, and the set of electrodes 26 of lead 20B includes electrodes 26A, 26B, 26C, and 26D.”).
Nelson and Saab, alone or in combination, fail to teach wherein the one or more electrodes are disposed within the epidural space to sense the LFP signal from a dorsal root ganglion (DRG).
However, Harhangi teaches a system sensing physiological data and adjusting the stimulation signal based on the sensed data in spinal cord injuries ([0040]) wherein the one or more electrodes are disposed within the epidural space to sense the LFP signal from a dorsal root ganglion (DRG) ([0041] “an electric signal at the distal end of an electrode can be measured by the sensor, so as to form a closed loop for controlling the electric signal to desired signal characteristics. As a further example, autonomous electrical activity in the target dorsal root ganglion DRG or adjacent tissue can be measured by the sensor, for monitoring local natural electric activity in the DRG or adjacent tissue of the patient, e.g. for tuning or matching the applied stimulation electric signal S, e.g. in shape, intensity or timing, to an electrical profile that is already present.”, view Figure 1).
It would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Harhangi to have wherein the one or more electrodes are disposed within the epidural space to sense the LFP signal from a dorsal root ganglion (DRG), as these prior art references and the instant application are directed to monitoring signals from a patient to adjust electrical stimulation parameters. One would be motivated to do this as the electrodes would be closer to the relevant neurons and there will be a reduction in posture/motion effects upon the recorded signal.
Regarding claim 22, Nelson and Saab teaches the system of claim 1 (as shown above). Nelson and Saab, alone or in combination, fail to teach wherein the LFP signal is received from the one or more electrodes disposed in the epidural space adjacent at least one of dorsal root ganglion, a dorsal root, a dorsal rootlet, a dorsal root entry zone, a ventral root, or a ventral rootlet, and wherein the cervical, thoracic, or lumbar region of the spinal cord includes one or more of the dorsal root, the dorsal rootlet, the dorsal root entry zone, the ventral root, or the ventral rootlet.
However, Harhangi teaches wherein the LFP signal is received from the one or more electrodes disposed in the epidural space adjacent at least one of dorsal root ganglion ([0041] “autonomous electrical activity in the target dorsal root ganglion DRG or adjacent tissue can be measured by the sensor, for monitoring local natural electric activity in the DRG or adjacent tissue of the patient”) and wherein the cervical, thoracic, or lumbar region of the spinal cord includes one or more of the dorsal root ([0025] “the distal ends of the electrodes can be positioned at the targeted dorsal root ganglion like L1, L2, L3, L4, L5, S1, S2, S3, S4, S5, Thoracic or Cervical levels.”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Nelson and Saab to incorporate the teachings of Harhangi to have wherein the LFP signal is received from the one or more electrodes disposed in the epidural space adjacent at least one of dorsal root ganglion, a dorsal root, a dorsal rootlet, a dorsal root entry zone, a ventral root, or a ventral rootlet, and wherein the cervical, thoracic, or lumbar region of the spinal cord includes one or more of the dorsal root, the dorsal rootlet, the dorsal root entry zone, the ventral root, or the ventral rootlet, as these prior art references are directed to monitoring signals from a patient to adjust electrical stimulation parameters. One would be motivated to do this as the electrodes would be closer to the relevant neurons and there will be a reduction in posture/motion effects upon the recorded signal.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Giftakis et al. (US 2018/0071530 A1) teaches LFP signals comprising cardiac (ECG) artifacts ([0074]).
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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/ATTIYA SAYYADA HUSSAINI/Examiner, Art Unit 3792
/NIKETA PATEL/Supervisory Patent Examiner, Art Unit 3792