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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's claims filed on 02/02/2026 have been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/26/2026 is being considered by the examiner.
Status of Claims
Claims 1-20 are currently pending and under examination. As per the amendments in the 02/02/2026 claim set (entered with the 02/26/2026 RCE), claims 1, 3, 8-9, 11, 13, and 19-20 are amended.
Priority
The instant application (filed on 03/27/2023) is a non-provisional application filed under 35 USC 111(a). Acknowledgment is made of applicant's claim for domestic priority based on provisional application 63/330,062 (filed on 04/12/2022). Amended Instant claims 1-20 are sufficiently described in the provisional application to receive an effective filing date of 04/12/2022 and all prior art will be evaluated with respect to this date.
Response to Arguments
Applicant’s arguments, see Remarks pages 8-11 (The Rejection of Claims Under§ 102), filed 02/02/2026, with respect to the rejections of claims 1-3, 11-14, and 20 under 35 U.S.C. § 102 have been fully considered. Regarding claim 1, Applicant argues:
Claim 1 is amended to more clearly recite the claimed subject matter. Applicant respectfully traverses the rejection and submits that the Thakur does not provide the claimed subject matter. For example, Applicant is unable to find in Thakur, among other things, "a sensory profiling circuit configured to receive information provided by the patient regarding painful symptoms of the patient and to determine a pain sensory profile for a body area of the patient using the received information, the pain sensory profile including one or more symptom types for the body area, the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies" and "a stimulation control circuit configured to determine a recommendation for one or more spinal cord stimulation (SCS) therapies selected from the available SCS therapies using the determined pain sensory profile", as recited in claim 1.
The Office Action asserts, under Response to Arguments:
... The Examiner interprets the pain sensory profile in the instant specification as containing elements of either a numerical or categorical nature in order to describe symptoms . . . . Thakur allows for quantitative or categorical pain inputs to be generated via a multisensor approach to describe pain symptoms .... Office Action at page 3.
It is unclear what is meant by "categorical nature" in this assertion, but Thakur states: "The categorical values may include 'low', 'medium', or 'high"', as quoted in the Office Action (Thakor at paragraph [0085]). Thus, both numerical and categorical values as disclosed in Thakor refer to a value of a pain score (a quantitative measure), which is considered in the Office Action to be the pain sensory profile as recited in claim 1. See, e.g., Office Action at pages 6-7 (Item 17, regarding "a sensory profiling circuit'). However, according to claim 1, the pain sensory profile includes one or more symptom types selected from a list of symptom types each including one or more types of sensation, in contrast to a merely quantitative measure. Additionally, claim 1 recites "to receive information provided by the patient ... and to determine a pain sensory profile ... using the received information". This is in contrast to the "multi sensor approach to describe pain symptoms" of Thakor as alleged in the Office Action. (02/02/2026 Remarks, p. 8-9)
This argument is persuasive. Non-quantitative inputs may be bettered described as subjective. Thakur discloses the collection of both quantitative and subjective inputs from information provided by the patient. Quantitative inputs include numerical values indicating the intensity of pain ([0065], [0085] – “The numerical values may be discrete or continuous within specified bounds such as between 0 and 10. The categorical values may include ‘low’, ‘medium’, or ‘high’”). Subjective inputs include information relating to pain location, duration, and sensation type ([0085] – such as “the pain markings can additionally include the different markings to distinguish various pain sensations such as aching, numbness, burning, stabbing, or needle pain, among others, and/or different markings to distinguish intensity of the pain sensations at different marked pain locations” where subjective values are quantified into a score in the pain profile/scales; [0073] – data separated into acute and chronic pain categories to determine therapy).
Thakur does not disclose “the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies” because the list of symptoms are not described as each being associated with a particular therapy. Therefore, the rejection of claim 1 is withdrawn. However, upon further consideration, a new ground(s) of rejection is made newly in view of Grandhe (US 2016/0136443).
Applicant also argues:
The Office Action asserts, under Response to Arguments (regarding "to determine a recommendation for one or more spinal cord stimulation (SCS) therapies selected from available SCS therapies using the determined pain sensory profile", as recited in claim 1):
... Thakur's programming circuit 235 uses the pain inputs to generate parameters for programming ( which would be interpreted as recommendations) while also allowing for manual control from user commands ([0072]). The inputs can include information entered by the user and integrated into the programmer ([0070]). Office Action at page 5.
It is unclear how these cited portions of Thakur relate to the limitation "to determine a recommendation ... "because it is unclear how Thakur provides the pain sensory profile as recited in claim 1 (as discussed above) and what are considered to be the "available SCS therapies." A clarification is respectfully requested if the rejection is maintained. Applicant respectfully requests reconsideration and allowance of claim 1. (02/02/2026 Remarks, p. 9)
This argument is not persuasive. The pain sensory profile is not constrained to a particular type of input as defined in the previous limitation, so that the use a pain scale showing the localized intensity in Thakur alone ([0072] – pain scales provided by sensors, [0080, 00985] – pain scales provided by user input) would qualify as a use of the pain sensory profile to select a particular SCS therapy. Therefore, the rejection of this limitation is maintained.
Note in the amended claim language (“to determine a pain sensory profile for a body area of the patient using the received information, the pain sensory profile including one or more symptom types for the body area, the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies”) the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation (more specificity may be needed in the “recommendation” limitation in claim 1 to require the use of the sensation type associated with a specific therapy).
Regarding claims 2-3, Applicant argues:
Claim 3 is amended to conform to the amended claim 1. Applicant respectfully traverses the rejection. Claims 2-3 are dependent on claim 1, which is believed to be patentable as discussed above. Therefore, the discussion above for claim 1 is incorporated herein to support the patentability of claims 2-3. Applicant respectfully requests reconsideration and allowance of claims 2-3. (02/02/2026 Remarks, p. 9)
This argument is persuasive due to the dependence of claims 2-3 on claim 1 (with its previously withdrawn rejection). Therefore, the rejections of claims 2-3 are withdrawn.
Regarding claim 11, Applicant argues:
Claim 11 is amended to correct an inadvertent error (missing "of' between "a body area" and "the patient") and to more clearly recite the claimed subject matter.
Applicant respectfully traverses the rejection and submits that the Thakur does not provide the claimed subject matter. For example, Applicant is unable to find in Thakur, among other things, "determining a pain sensory profile for a body area of the patient using the received information using a processor of a programming device, the pain sensory profile including one or more symptom types for the body area, the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies" and" determining a recommendation for one or more spinal cord stimulation (SCS) therapies using the processor, the one or more SCS therapies selected from the available SCS therapies using the determined pain sensory profile", as recited in claim 11.
The Office Action asserts, under Response to Arguments:
11. The method in claim 11 and the non-transitory computer-readable storage medium in claim 20 have equivalent amendments and arguments as those presented above for the system in claim 1 (pages 9-12, 08/15/2025 Remarks). Given these similarities, the Examiner interprets the arguments for claims 11 and 20 as being addressed in the discussion for claim 1 above. Therefore, the rejections of claims 11 and 20 over Thakur are maintained. Office Action at page 5.
Therefore, because claims 1 and 11 are amended by adding the same limitation, the discussion for claim 1 above is incorporated herein to further support the patentability of claim 11. Applicant respectfully requests reconsideration and allowance of claim 11. (02/02/2026 Remarks, p. 9-10)
This argument is overall persuasive. Claim 11 is a method of delivering neurostimulation from a stimulation device where the same arguments and responses for the system delivering neurostimulation in claim 1 are relevant. Thakur does not disclose “the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies” because the list of symptoms are not described as each being associated with a particular therapy. Therefore, the rejection of claim 11 is withdrawn. However, upon further consideration, a new ground(s) of rejection is made newly in view of Grandhe (US 2016/0136443).
With regards to the “recommendation” limitation, the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation.
Regarding claims 12-14, Applicant argues:
Claim 13 is amended to conform to the amended claim 11. Applicant respectfully traverses the rejection. Claims 12-14 are dependent on claim 11, which is believed to be patentable as discussed above. Therefore, the discussion above for claim 11 is incorporated herein to support the patentability of claims 12-14. Applicant respectfully requests reconsideration and allowance of claims 12-14. (02/02/2026 Remarks, p. 10)
This argument is persuasive due to the dependence of claims 12-14 on claim 11 (with its previously withdrawn rejection). Therefore, the rejections of claims 12-14 are withdrawn.
Regarding claim 20, Applicant argues:
Applicant respectfully traverses the rejection and submits that the Thakur does not provide the claimed subject matter. For example, Applicant is unable to find in Thakur, among other things, the method comprising "determining a pain sensory profile for a body area of the patient using the received information, the pain sensory profile including one or more symptom types for the body area, the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies" and "determining a recommendation for one or more spinal cord stimulation (SCS) therapies selected from available SCS therapies using the determined pain sensory profile", as recited in claim 20.
The Office Action asserts, under Response to Arguments:
11. The method in claim 11 and the non-transitory computer-readable storage medium in claim 20 have equivalent amendments and arguments as those presented above for the system in claim 1 (pages 9-12, 08/15/2025 Remarks). Given these similarities, the Examiner interprets the arguments for claims 11 and 20 as being addressed in the discussion for claim 1 above. Therefore, the rejections of claims 11 and 20 over Thakur are maintained. Office Action at page 5.
Therefore, because claims 1 and 20 are amended by adding the same limitation, the discussion for claim 1 above is incorporated herein to further support the patentability of claim 20. Applicant respectfully requests reconsideration and allowance of claim 20. (02/02/2026 Remarks, p. 10-11)
This argument is overall persuasive. Claim 20 is a non-transitory computer-readable storage medium in a neurostimulation system where the same arguments and responses for the system delivering neurostimulation in claim 1 are relevant. Thakur does not disclose “the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies” because the list of symptoms are not described as each being associated with a particular therapy. Therefore, the rejection of claim 11 is withdrawn. However, upon further consideration, a new ground(s) of rejection is made newly in view of Grandhe (US 2016/0136443).
With regards to the “recommendation” limitation, the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation.
Applicant’s arguments, see Remarks page 12 (The Rejection of Claims Under§ 103), filed 02/02/2026, with respect to the rejections of claims 4-10 and 15-19 under 35 U.S.C. § 103 have been fully considered. Regarding these dependent claims, Applicant argues:
Claims 4-10 and 15-19 were rejected under 35 U.S.C. § 103 over Thakur in view of Parker (U.S. Patent Application Publication No. 2013/0261697, hereinafter "Parker"). Claims 8-9 and 19 are amended for clearer antecedent basis. Applicant respectfully traverses the rejection. Claims 4-10 are dependent on claim 1, which is believed to be allowable for at least the reason discussed above. The addition of Parker does not appear to address the deficiency of the rejection of claim 1 using Thakur. Therefore, the discussion above for claim 1 is incorporated herein to support the patentability of claims 4-10. Claims 15-19 are dependent on claim 11, which is believed to be allowable for at least the reason discussed above. The addition of Parker does not appear to address the deficiency of the rejection of claim 11 using Thakur. Therefore, the discussion above for claim 11 is incorporated herein to support the patentability of claims 15-19. Applicant respectfully requests reconsideration and allowance of claims 4-10 and 15-19. (02/02/2026 Remarks, p. 11)
This argument is persuasive due to the dependence of claims 4-10 on claim 1 (with its previously withdrawn rejection) and claims 15-19 on claim 11 (with its previously withdrawn rejection). Therefore, the rejections of claims 4-10 and 15-19 are withdrawn.
Summary: The prior art rejections for claims 1-20 are withdrawn. 35 U.S.C. § 103 rejections for claims 1-20 newly in view of Grandhe are added.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C.
103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-8 and 10-20 are rejected under U.S.C 103 as being unpatentable over Thakur (US 2018/0085584 A1) in view of Grandhe (US 2016/0136443).
Regarding Claim 1, Thakur discloses a system for delivering neurostimulation from a stimulation device to a patient ([0050]), the system comprising:
• a programming control circuit configured to program the stimulation device for controlling delivery of the neurostimulation according to one or more stimulation waveforms and one or more stimulation fields ([0072] – parameter values for operating the stimulator, where characterization of the stimulation waveform is described in [0056]);
• a sensory profiling circuit (pain score generator 233) configured to receive information provided by the patient regarding painful symptoms of the patient (analysis from sensor measurements of patients for severity [0065] and pain type [0073]; [0080] – user provided pain information about pain scales and [0085] – data from questionnaire is input into the pain score generator with parameters such as pain severity, body area, and pain type) and to determine a pain sensory profile for a body area of the patient using the received information ([0085] – pain map; [0058] – electrodes can be automatically selected based on pain profile), the pain sensory profile including one or more symptom types for the body area ([0085] – such as “the pain markings can additionally include the different markings to distinguish various pain sensations such as aching, numbness, burning, stabbing, or needle pain, among others, and/or different markings to distinguish intensity of the pain sensations at different marked pain locations” where subjective values are quantified into a score in the pain profile/scales; [0073] – data separated into acute and chronic pain categories to determine therapy), and
• a stimulation control circuit (electrostimulator 213 and controller 214) configured:
- to determine a recommendation for one or more spinal cord stimulation (SCS) therapies selected from available SCS therapies using the determined pain sensory profile ([0072], [0076] – the pain score is used to determine therapy; [0080] – user provided pain information about pain scales; [0009] – spinal cord stimulation); and
- to determine the one or more stimulation waveforms and the one or more stimulation fields using the recommended one or more SCS therapies ([0056-0057] – the electrostimulation controller translates the determined settings into a SCS therapy waveform, [0058] – specific stimulation electrodes are selected based on pain information collected and analyzed from the patient). Note the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation.
Thakur discusses the numerical pain scale as avoiding the drawbacks of using subjective pain sensation data, namely requiring extra time and personnel for interpreting how the subjective pain sensation should be associated with a desired stimulation therapy ([0006]). However, Thakur does not disclose the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies.
Grandhe, in the same field of endeavor of a spinal cord stimulation device to inhibit pain ([0002-0003], [0077]), teaches using the system in step 1002 where “the pain condition is input into the system using, for example, the external programming unit, the patient interface unit, or any other input device. The pain condition can be expressed in any suitable manner that is accepted by the system, such as, for example, descriptive text, selection from a list of pain sites or symptoms or other indicators, identification of pain regions on an anatomical representation, or any other suitable method of indicating the source, symptom, or site of the pain” ([0079]). Once this subjective data is entered, step 1004 details how aggregated data is used to determine a correlation between the pain condition input and a desired therapy where the recommendations are provided to the user or clinician in step 1006 (Fig. 10, [0079]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to alter Thakur’s spinal stimulation device with a quantitative pain score by incorporating the correlation of subjective pain data with sets of treatment parameters. This would have been obvious because both Thakur and Grandhe discuss correlations to establish a localized stimulation for relieving back/spinal pain and Grandhe provides a solution/improvement to automatically interpret subjective data to produce the most effective stimulation pattern/settings. Therefore, a person of ordinary skill in the art would be motivated to improve the system of Thakur by incorporating the correlation of subjective pain data with sets of treatment parameters in Grandhe as a complement to the quantitative pain score in Grandhe.
Regarding Claim 2, the system for delivering neurostimulation according to Claim 1 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses comprising a user interface ([0070]) including
• a presentation device ([0070] – display);
• a user input device ([0070] – input devices); and
• an interface control circuit including the sensory profiling circuit and the stimulation control circuit ([0070] – “The input device may enable a system user to program the parameters used for sensing the physiological signals, generating signal metrics, or generating the pain score”)
wherein the sensory profiling circuit is configured to receive the information regarding painful symptoms of the patient using the user input device ([0067]: multi-sensor physiologic information in [0052-0054] used to compute pain scales; [0080] – user provided pain scale information), and
the stimulation control circuit is configured to present the recommendation for the one or more SCS therapies using the presentation device ([0070] – “the user interface 234 may enable a system user to confirm, reject, or edit the weight factors determined by the weight generator 232, or to confirm, rejection, or edit the programming of the implantable neuromodulator 210A, such as parameters for electrostimulation.”; [0040], [0076] - recommendations).
Regarding Claim 3, the system for delivering neurostimulation according to Claim 2 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein the sensory profiling circuit is configured to:
• present a symptom questionnaire using the presentation device ([0085] – specifically mentions a questionnaire about pain symptoms and scoring as part of the user input, see pain markings list);
• to receive answers to the symptom questionnaire using the user input device [0070] – the user interface contains a mechanism for user to enter symptom information and pain scales), and
• to produce the pain sensory profile using the received answers ([0085] – “The patient subjective pain description may then be transformed into quantitative pain scales”),
the symptom questionnaire including:
the list of symptom types ([0085]),
a measure of severity for each symptom type of the list of symptom types ([0085] – “patient questionnaire that may include information of anatomical location and distribution of the pain, severity or intensity of pain at various pain locations”),
and a frequency for each symptom type of the list of symptom types ([0085] - “patient questionnaire that may include … temporal pattern such as persistence of the pain at various pain locations”),
the frequency associating the each symptom type with each physical state of a list of physical states of the patient ([0085] – the temporal relationships in the questionnaire provide information about the state of the patient over time).
Regarding Claim 4, the system for delivering neurostimulation according to Claim 3 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses:
• the sensory profiling circuit is configured to produce the pain sensory profile for each body area of multiple specified body areas of the patient ([0085] – a pain sensory profile is produced by area of the body; [0058] – the controller can select electrodes for stimulation based on an “anatomical area of pain”);
• the stimulation control circuit is configured to determine the recommendation for the one or more SCS therapies ([0072] – the pain score is used to determine therapy);
While location of pain and application of stimulation for specific anatomical locations is discussed in Thakur ([0058, 0086]), the selection of electrodes based on an anatomical area of pain in [0058] is not explicitly derived from pain types identified based on an anatomical map. However, Thakur does not disclose the pain sensory profile results in a pain sensory map for the patient or that the resultant pain sensory map is used to determine a recommendation for therapies.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can input areas of pain or other symptoms and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069]). Grandhe mentions the integration of the pain map into step 1004 to determine the appropriate therapy recommendation ([0079]).
Regarding Claim 5, the system for delivering neurostimulation according to Claim 4 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein:
• the stimulation control circuit is configured to determine a sensory subtype ([0073] – “In addition to or in lieu of the pain score which may be used to quantify severity of pain, the pain analyzer 231 may include circuits, or a processor executing instructions, for characterizing various types of pain, such as by differentiating chronic pain from acute pain”), and
• the stimulation control circuit is configured to determine the recommendation for the one or more SCS therapies using the determined sensory subtype ([0073] – “The pain therapy may be delivered, withheld, or otherwise modified in accordance with the pain type” where examples are provided).
Thakur does not explicitly state a subtype based on the pain sensory map.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can input areas of pain or other symptoms and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069]). Grandhe mentions the integration of the pain map into step 1004 to determine the appropriate therapy recommendation ([0079]).
Regarding Claim 6, the system for delivering neurostimulation according to Claim 5 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein:
• the stimulation control circuit is configured to receive one or more additional factors ([0069]) and to determine the recommendation for the one or more SCS therapies using the determined sensory subtype and the received one or more additional factors ([0069] – examples are provided where the pain thresholds, which determine stimulation parameters, are adjusted based on factors such as gender and sleep state).
the one or more additional factors including at least one of a stimulation-related factor, a disease-related factor, a demographic factor, or a behavioral factor ([0069] – additional inputs into the pain score generator include information about demographics, disease history, and behavior). The stimulation-related factor is interpreted as a pain response to stimulation from the device (specification - [00100]). Thakur discloses pain being assessed in response to electrical stimulation therapy in order to adjust the stimulation device ([0014]).
However, Thakur does not explicitly state a subtype based on the pain sensory map.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002).
Regarding Claim 7, the system for delivering neurostimulation according to Claim 5 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein the stimulation control circuit is configured to determine the recommendation for the one or more SCS therapies using predetermined relationships known sensory subtypes to the available SCS therapies ([0073] – the pain data is interpreted to categorize into specific pain types, which require specific SCS therapies). However, Thakur does not explicitly state predetermined relationship mapping.
As stated in claim 1, the proposed combination with Grandhe yields a clinical effects map using aggregated patient data to establish a predetermined relationship between patient symptoms and recommended therapies ([0070-0071]), as incorporated in step 1004 ([0079]).
Regarding Claim 8, the system for delivering neurostimulation according to Claim 7 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein the stimulation control circuit is further configured:
• to determine a suitability for the sensory subtype ([0066] – the weight generator is used to interpret input data in terms of correlation with a pain condition, where input data can be: sensor data [0067], patient history/demographics [0069], and user-supplied data [0086]; [0087] – the functional measures have a pre-determined correlation with the pain scales (P)) associated with each therapy of the recommended one or more SCS therapies ([0059] – “In an example, the controller 214 may control the generation and delivery of electrostimulation in a closed-loop fashion by adaptively adjusting one or more stimulation parameters or stimulation electrode configuration based on the detected signal metrics in response to the pain”; [0040], [0076] - recommendations);
• to determine the one or more stimulation waveforms and the one or more stimulation fields based on the recommended one or more SCS therapies and the associated one or more suitability ([0072] – the programmer circuit implements the waveform as a stimulation signal; [0058] – specific stimulation electrodes are selected based on pain information collected and analyzed from the patient).
However, Thakur does not explicitly state a subtype based on the pain sensory map or compute the likelihood of suitability.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002). A clinical effects map with aggregated patient data establishes a predetermined relationship between patient symptoms and recommended therapies, where the clinical effects map is used to determine a recommendation for the probabilistically most effective treatment ([0070-0071]; [0079] - as incorporated in step 1004).
Regarding Claim 10, the system for delivering neurostimulation according to Claim 8 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein the stimulation control circuit is configured to present ([0070] - the therapy is presented and controlled from the display, with a variety of display features disclosed):
• the recommendation for the one or more SCS therapies using the presentation device ([0070] – pain information via the pain score is displayed), the recommendation for the one or more SCS therapies showing the determined sensory subtype (analysis from sensor measurements of patients for severity [0065] and pain type [0073]; [0085] – data from questionnaire is input into pain score generator with parameters such as pain severity, body area, and pain type);
• one or more therapies selected from the available SCS therapies ([0070] – the selected therapy is visible on the user interface),
• one or more suitability each associated with a therapy of the selected one or more therapies for the determined sensory subtype ([0070] – displays correlations between pain score/scales, which determine the treatment, and inputs).
However, Thakur does not explicitly state a subtype based on the pain sensory map or compute the likelihood of suitability.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002). A clinical effects map with aggregated patient data establishes a predetermined relationship between patient symptoms and recommended therapies, where the clinical effects map is used to determine a recommendation for the probabilistically most effective treatment ([0070-0071]; [0079] - as incorporated in step 1004).
Regarding Claim 11, Thakur discloses a method for delivering neurostimulation from a stimulation device to a patient ([0094]), the method comprising:
• receiving information provided by the patient regarding painful symptoms of the patient (analysis from sensor measurements of patients for severity [0065] and pain type [0073]; [0080] – user provided pain information about pain scales and [0085] – data from questionnaire is input into pain score generator with parameters such as pain severity, body area, and pain type);
• determining a pain sensory profile for a body area of the patient using the received information ([0085] – pain map; [0058] – electrodes can be automatically selected based on pain profile), using a processor of a programming device ([0062] – processor involved with programming, [0064] - pain score generator 233), the pain sensory profile including one or more symptom types for the body area ([0085] – subjective symptoms are listed where subjective values are quantified into a score in the pain profile/scales; [0073] – data separated into acute and chronic pain categories to determine therapy),
• determining a recommendation for one or more spinal cord stimulation (SCS) therapies using the processor ([0100]);
• determining one or more stimulation waveforms and one or more stimulation fields using the recommended one or more SCS therapies using the processor ([0100] – SCS waveform properties; [0058] – specific electrode locations are selected based on pain information collected and analyzed from the patient), the one or more SCS therapies selected from the available SCS therapies using the determined pain sensory profile ([0072], [0076] – the pain score is used to determine therapy; [0080] – user provided pain information about pain scales; [0009] – spinal cord stimulation);
• programming the stimulation device, using the programming device, for controlling delivery of the neurostimulation according to the one or more stimulation waveforms and the one or more stimulation fields ([0072] – the programmer circuit implements the waveform as a stimulation signal; [0058] – specific stimulation electrodes are selected based on pain information collected and analyzed from the patient). Note the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation.
Thakur discusses the numerical pain scale as avoiding the drawbacks of using subjective pain sensation data, namely requiring extra time and personnel for interpreting how the subjective pain sensation should be treated via stimulation ([0006]). Thakur does not disclose the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies.
Grandhe, in the same field of endeavor of a spinal cord stimulation device to inhibit pain ([0002-0003], [0077]), teaches using the system in step 1002 to identify subjective symptoms by anatomical location ([0079]). Once this subjective data is entered, step 1004 details how aggregated data is used to determine a correlation between the pain condition input and a desired therapy where the recommendations are provided to the user or clinician in step 1006 (Fig. 10, [0079]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to alter Thakur’s method for applying a spinal stimulation device with a quantitative pain score by incorporating the correlation of subjective pain data with sets of treatment parameters. This would have been obvious because both Thakur and Grandhe discuss correlations to establish a localized stimulation for relieving back/spinal pain and Grandhe provides a solution/improvement to automatically interpret subjective data to produce the most effective stimulation pattern/settings. Therefore, a person of ordinary skill in the art would be motivated to improve the method of Thakur by incorporating the correlation of subjective pain data with sets of treatment parameters in Grandhe as a complement to the quantitative pain score in Grandhe.
Regarding Claim 12, the method for delivering neurostimulation according to Claim 11 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein receiving the information regarding painful symptoms of the patient comprises:
• presenting a symptom questionnaire ([0085, 0103] – specifically mentions a questionnaire about pain symptoms and scoring as part of the user input) using a presentation device ([0070]);
• receiving answers to the symptom questionnaire using a user input device ([0070] – the user interface contains a mechanism for user to enter symptom information and pain scales: “The mobile App may enable a patient to provide pain description or quantified pain scales during the pain episodes, and send the pain description or pain scales to the weight generator”); and
• producing the pain sensory profile using the received answers using the processor ([0085] – “The patient subjective pain description may then be transformed into quantitative pain scales”).
Regarding Claim 13, the method for delivering neurostimulation according to Claim 12 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein presenting the symptom questionnaire comprising:
• presenting the list of symptom types ([0085], [0103]);
• presenting measures of severity each associated with a symptom type of the list of symptom types ([0085] – “patient questionnaire that may include information of anatomical location and distribution of the pain, severity or intensity of pain at various pain locations”); and
•presenting frequencies each associated with a symptom type of the list of symptom types ([0085] - “patient questionnaire that may include … temporal pattern such as persistence of the pain at various pain locations”);
• and relating the each associated symptom type to one or more physical states of the patient ([0085] – the temporal relationships in the questionnaire provide information about the state of the patient over time).
Regarding Claim 14, the method for delivering neurostimulation according to Claim 12 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein determining the pain sensory profile for the patient comprises determining the pain sensory profile for a specified body area of the patient ([0058] – Pain is identified by anatomical location, which prompts stimulation by certain electrodes associated with that location).
Therefore, Claim 14 is anticipated by Thakur.
Regarding Claim 15, the method for delivering neurostimulation according to Claim 14 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses:
• determining the pain sensory profile for the patient comprises determining the pain sensory profile for each body area of multiple specified body areas of the patient ([0098] – generate a multisensory indicated pain score based off of the weighting in [0097]; [0058] – the controller can select electrodes for stimulation based on an “anatomical area of pain”); and
• determining the recommendation for one or more SCS therapies using the determined pain sensory profile comprises determining the recommendation for one or more SCS therapies ([0072] – the pain score is used to determine therapy; [0100] – “pain therapy may be delivered to the patient according to the multi-sensor indicated pain score”),
Thakur does not disclose the pain sensory profile results in a pain sensory map for the patient or the resultant pain sensory map is used to determine a recommendation for therapies.
As stated in claim 11, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can input areas of pain or other symptoms and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069]). Grandhe mentions the integration of the pain map into step 1004 to determine the appropriate therapy recommendation ([0079]).
Regarding Claim 16, the method for delivering neurostimulation according to Claim 15 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein determining the recommendation for one or more SCS therapies using the determined pain sensory profile comprises:
• determining a sensory subtype ([0098] – generate a multisensory indicated pain score based on the weighting in [0097]);
•determining the recommendation for the one or more SCS therapies using the determined sensory subtype ([0100] – “pain therapy may be delivered to the patient according to the multi-sensor indicated pain score”).
Thakur does not disclose a sensory subtype based on the pain sensory map.
As stated in claim 11, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can input areas of pain or other symptoms and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069]). Grandhe mentions the integration of the pain map into step 1004 to determine the appropriate therapy recommendation ([0079]).
Regarding Claim 17, the method for delivering neurostimulation according to Claim 16 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein:
• determining the sensory subtype comprises selecting the sensory subtype from known sensory subtypes ([0073] – “In addition to or in lieu of the pain score which may be used to quantify severity of pain, the pain analyzer 231 may include circuits, or a processor executing instructions, for characterizing various types of pain, such as by differentiating chronic pain from acute pain […] The pain therapy may be delivered, withheld, or otherwise modified in accordance with the pain type), and
• determining the recommendation for the one or more SCS therapies comprises selecting the one or more SCS therapies from available SCS therapies using predetermined relationships the known sensory subtypes to the available SCS therapies ([0073] – the pain data is interpreted as being categorized into specific pain types, which require specific SCS therapies).
However, Thakur does not explicitly disclose a sensory subtype based on the pain sensory map or predetermined relationship mapping.
As stated in claim 11, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002 and integrated into step 1004). Grandhe also teaches a clinical effects map using aggregated patient data to establish a predetermined relationship between patient symptoms and recommended therapies ([0070-0071]), as incorporated in step 1004 ([0079]).
Regarding Claim 18, the method for delivering neurostimulation according to Claim 17 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses wherein determining the recommendation for the one or more SCS therapies using the determined sensory subtype further comprises determining a suitability for the sensory subtype ([0066] – the weight generator is used to interpret input data in terms of correlation with a pain condition, where input data can be: sensor data [0067], patient history/demographics [0069], and user-supplied data [0086]; [0087] – the functional measure have a pre-determined correlation with the pain scales (P)) associated with each therapy of the one or more SCS therapies ([0059] – “In an example, the controller 214 may control the generation and delivery of electrostimulation in a closed-loop fashion by adaptively adjusting one or more stimulation parameters or stimulation electrode configuration based on the detected signal metrics in response to the pain”).
However, Thakur does not explicitly state a subtype based on the pain sensory map or compute the likelihood of suitability.
As stated in claim 11, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target
volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002). A clinical effects map with aggregated patient data establishes a predetermined relationship between patient symptoms and recommended therapies, where the clinical effects map is used to determine a recommendation for the probabilistically most effective treatment ([0070-0071]; [0079] - as incorporated in step 1004).
Regarding Claim 19, the method for delivering neurostimulation according to Claim 18 is obvious over Thakur in view of Grandhe, as indicated hereinabove. Thakur further discloses comprising presenting the recommendation for the one or more SCS therapies ([0070] – the therapy is presented and controlled from the display, with a variety of display features disclosed), including presenting:
• the determined sensory subtype ([0070] - the pain type via the pain score is displayed: “The user interface 234 may include an output unit, which may include a display, to present to a system user such as a clinician the multi-sensor indicated pain score”),
• the recommended one or more SCS therapies ([0070] – the selected therapy is visible on the user interface; [0040], [0076] - recommendations), and
• one or more suitability each associated with a therapy of the recommended one or more SCS therapies ([0070] – displays correlations between pain score/scales, which determine the treatment, and inputs; [0040], [0076] - recommendations).
However, Thakur does not explicitly state a subtype based on the pain sensory map or compute the likelihood of suitability.
As stated in claim 11, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002). A clinical effects map with aggregated patient data establishes a predetermined relationship between patient symptoms and recommended therapies, where the clinical effects map is used to determine a recommendation for the probabilistically most effective treatment ([0070-0071]; [0079] - as incorporated in step 1004).
Regarding Claim 20, Thakur discloses a non-transitory computer-readable storage medium including instructions ([0062] – microprocessor circuit), which when executed by a system, cause the system to perform a method for delivering neurostimulation from a stimulation device to a patient ([0062] – the external system uses a microprocessor to control the pain analyzer, user interface, and programmer circuit), the method comprising:
• receiving information provided by the patient regarding painful symptoms of the patient (analysis from sensor measurements of patients for severity [0065] and pain type [0073]; [0080] – user provided pain information about pain scales and [0085] – data from questionnaire is input into pain score generator with parameters such as pain severity, body area, and pain type);
• determining a pain sensory profile for a body area of the patient using the received information ([0085] – pain map; [0058] – electrodes can be automatically selected based on pain profile), the pain sensory profile including one or more symptom types for the body area ([0085] – subjective symptoms are listed where subjective values are quantified into a score in the pain profile/scales; [0073] – data separated into acute and chronic pain categories to determine therapy),
• determining a recommendation for one or more spinal cord stimulation (SCS) therapies selected from available SCS therapies using the determined pain sensory profile ([0072], [0076] – the pain score is used to determine therapy; [0080] – user provided pain information about pain scales; [0009] – spinal cord stimulation);
• determining one or more stimulation waveforms and one or more stimulation fields using the recommended one or more SCS therapies ([0056-0057] – the electrostimulator controller translates the determined settings into a SCS therapy waveform; [0058] – specific stimulation electrodes are selected based on pain information collected and analyzed from the patient); and
• programming the stimulation device for controlling delivery of the neurostimulation according to one or more stimulation waveforms and one or more stimulation fields ([0072] – parameter and electrode configurations are entered, where characterization of the stimulation waveform is described in [0056]; [0058] – specific stimulation electrodes are selected based on pain information collected and analyzed from the patient). Note the pain sensory profile merely needs to include symptom types which include sensation types, but not necessarily that these sensation types are directly used to form the therapy recommendation.
Thakur discusses the numerical pain scale as avoiding the drawbacks of using subjective pain sensation data, namely requiring extra time and personnel for interpreting how the subjective pain sensation should be treated via stimulation ([0006]). However, Thakur does not disclose the one or more symptom types selected from a list of symptom types each including one or more types of sensation and each being an indication for a therapy of available SCS therapies.
Grandhe, in the same field of endeavor of a spinal cord stimulation device to inhibit pain ([0002-0003], [0077]), teaches using the system in step 1002 to identify subjective symptoms by anatomical location ([0079]). Once this subjective data is entered, step 1004 details how aggregated data is used to determine a correlation between the pain condition input and a desired therapy where the recommendations are provided to the user or clinician in step 1006 (Fig. 10, [0079]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to alter Thakur’s spinal stimulation device with a quantitative pain score by incorporating the correlation of subjective pain data with sets of treatment parameters. This would have been obvious because both Thakur and Grandhe discuss correlations to establish a localized stimulation for relieving back/spinal pain and Grandhe provides a solution/improvement to automatically interpret subjective data to produce the most effective stimulation pattern/settings. Therefore, a person of ordinary skill in the art would be motivated to improve the system of Thakur by incorporating the correlation of subjective pain data with sets of treatment parameters in Grandhe as a complement to the quantitative pain score in Grandhe.
Claim 9 is rejected under U.S.C 103 as being unpatentable over Thakur (US 2018/0085584 A1, see previously cited) in view of Grandhe (US 2016/0136443) and Parker (US 2013/0261697 A1).
Regarding Claim 9, the system for delivering neurostimulation according to Claim 8 is obvious over Thakur in view of Grandhe and Parker, as indicated hereinabove. Thakur further discloses wherein the stimulation control circuit is further configured to determine the suitability for the sensory subtype ([0073] – pain is categorized by type, where type determines a stimulation profile; [0087] – correlations used to categorize pain type based on sensor [0086] and user inputs [0085]) associated with each therapy of the recommended one or more SCS therapies ([00).
Thakur does not disclose using a predetermined lookup table providing the likelihood of suitability for each sensory subtype of the known sensory subtypes associated with each therapy of the available SCS therapies. Additionally, Thakur does not explicitly state a subtype based on the pain sensory map or compute the likelihood of suitability.
As stated in claim 1, the proposed combination with Grandhe yields an anatomical pain map which the patient or clinician can use to input areas of pain or other symptoms (the determined sensory subtype) and the system uses this pain map to provide recommendations for tissue target volumes and stimulation parameters ([0069], [0079] – symptom types described in step 1002). A clinical effects map with aggregated patient data establishes a predetermined relationship between patient symptoms and recommended therapies, where the clinical effects map is used to determine a recommendation for the probabilistically most effective treatment ([0070-0071]; [0079] - as incorporated in step 1004).
Parker, in the same field of endeavor of a spinal cord stimulation device to inhibit pain ([0002]), teaches the use of pre-established modulation programs (setting stimulation parameters such as electrode position relative to the spine, frequency, pulse width, interpulse interval, and amplitude) selected based on a correlation between settings and treatment efficacy established in a database ([0123]). The pre-established modulation programs correspond to patient indicators, which include information related to the location of pain ([0122]). When entered, the location of pain as a patient indicator correlates to a specific electrode stimulation activation pattern ([0123]). Parker further teaches the use of a look-up table for establishing correlations between a selected pain type and corresponding treatment ([0123]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to alter Thakur’s correlation between patient feedback and pain type (associated with a specific treatment) by incorporating the lookup table to select the appropriate modulation program in Parker. This would have been obvious because both Thakur and Parker discuss correlations to establish which preset stimulation category is needed and Parker provides a solution/improvement to compare a variety of potential categorizations in one tabular location and determine the appropriate treatment category based on patient feedback. Therefore, a person of ordinary skill in the art would be motivated to improve the system of Thakur by incorporating the lookup table to select the appropriate modulation program in Parker.
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/Benjamin A. Schmitt/
Examiner
Art Unit 3796
/CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796
Prosecution Insights