Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 01/02/2026 have been fully considered but they are not persuasive. The applicant has successfully integrated some of the prior cited abstract ideas including “determining initial settings for the neuromodulation device”, “determining a patient's response with respect to the delivered stimulation”, “determine new settings for the neuromodulation device”, and “settings are identified as optimal by the algorithm” into practical applications, however some abstract ideas still remain, so the 35 USC 101 rejection of claim 1 and dependents is maintained.
Applicant’s arguments, filed 01/02/2026, with respect to the 35 USC 112(b) rejections of claims 1 and 16 have been fully considered and are persuasive. The 35 USC 112(b) rejections of claims 1 and 16 has been withdrawn.
Applicant's arguments filed 01/02/2026 regarding the prior art rejections have been fully considered but they are not persuasive.
Regarding claim 1, the applicant argues that Zhang does not teach “recording brain signals of the patient during stimulation and determining the patient's response based on the recorded brain signals”. The applicant argues that Zhang only teaches using a wearable sensor while the present application uses invasive brain signal recording for deep brain stimulation applications. However, this is untrue as Zhang teaches “the sensors can include wearable and/or implantable sensors” and references figure 13 to support that the sensors can be implantable
Regarding claim 1, the applicant argues that “Zhang’s clinical effect mapping is fundamentally based on manual user input and clinical observations, not on automated processing of recorded brain signals”. However, this is untrue as Zhang teaches "As shown in FIG. 13, the clinical effects can include those derived from signals sensed from the patient. In various embodiments, the clinical effects can be entered by be user and/or the patient, and/or derived automatically from measurements using various sensors.” As established previously, the sensors record brain signals and the above cited disclosure clearly states that the “clinical effects can include those derived from signals derived from the patient”.
Regarding claim 10, the applicant argues that the “specific application of color-coding to patient feedback options for neuromodulation therapy optimization is not taught or suggested and neither are pictograms”. This argument is persuasive so the previous grounds of rejection is withdrawn, however a new grounds of rejection is made under Jiang et al (US 20160045751 A1); hereinafter Jiang. In table 2, Jiang teaches “color-coded qualitative feedback”.
Regarding claim 12, the applicant argues that the cited reference does not contain a microphone to read on the limitation of collecting vocal input from the patient. This argument is persuasive so the previous grounds of rejection is withdrawn, however a new grounds of rejection is made under Vera-Portocarrero et al (US 20160045751 A1); hereinafter Vera. Vera teaches “In some instances, UI 18 may include a UI that utilizes virtual reality (VR), augmented reality (AR), or mixed reality (MR) UIs, such as those that may be implemented via a VR, AR, or MR headset. UI 18 may further include a softkeys, hard keys (e.g., physical buttons), lights, a speaker and microphone for voice commands” ([0055]).
Regarding claims 16 and 24, the applicant argues that Offrut uses the database for patient selection for therapy while the present application uses it to determine parameter settings. However, in paragraph [0097], Offrut teaches " In some examples, the population-informed data may be anonymized data stored in a database 234 on server 26 or accessible by server 26. For example, server 26 may determine different initial stimulation program settings for patients with a particular disease, e.g., fecal incontinence, with than patients with a different indication, e.g., urinary incontinence patients. These differences may be based on population-informed data, patient specific data or both. Server 26 may determine different initial stimulation program settings for patients with more severe symptoms than patients with less severe symptoms". Therefore, Offrut does teach using “population-informed data” to set parameters instead of just as a selection criteria for candidates.
Regarding claim 17, the applicant argues that Offrut does not teach searching the database for other patients with similar conditions with a filter. However, someone having ordinary skill in the art would recognize that using a filter is a simple substitution for the method used in Offrut.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-10,12-14,16-18, and 21-24 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-10,12-14 and 16-18 recite a method and claims 21-24 recite a system.
Step 2A, Prong 1
Claim(s) 1 and 21 recite(s) “determining an initial condition of a patient” and “determining one or more conditions and/or symptoms and/or expected outcomes for the patient”. The element is directed to the judicial exception of an abstract idea of a mental process of evaluation, judgement, or opinion that can be executed without the use of the claimed structure. A professional can:
Look at a patient and evaluate their condition
Look at a patient and determine what symptoms and conditions they have and what the expected outcome should be
Step 2A, Prong 2
Claim(s) 1 and 21 recite(s) the additional elements of :
“treatment parameters based on the determined initial health condition of the patient and/or the one or more conditions and/or symptoms and/or expected outcomes, and delivering stimulation to the patient based on the determined initial settings” – insignificant extra solution activity
“based on the determined patient response” – data gathering
Repeating steps (d) and (e) – insignificant extra solution activity
The additional elements from independent claims simply amount(s) to either insignificant extra solution activity or data gathering. These do not amount to integration of the abstract idea into a practical application.
Step 2B
As noted in Step 2A, Prong 2, The claims recite the additional elements of:
“treatment parameters based on the determined initial health condition of the patient and/or the one or more conditions and/or symptoms and/or expected outcomes, and delivering stimulation to the patient based on the determined initial settings” – insignificant extra solution activity
“based on the determined patient response” – data gathering
Repeating steps (d) and (e) – insignificant extra solution activity
The additional elements from independent claims simply amount(s) to either insignificant extra solution activity or data gathering. These do not amount to significantly more than the abstract idea itself.
Elements from dependent claims
The additional elements from the dependent claims also fail to integrate the abstract idea into a practical application or amount to significantly more than the abstract idea itself.
Claim 3 - The patient's response with respect to the delivered stimulation is determined based on the recorded brain signals – data gathering
Claim 5 - organizing the determined one or more conditions…according to predefined criteria of priority – another abstract idea since the method of defining the criteria of priority is not discussed
Claim 6 - the initial settings for the neuromodulation device are determined based on collected data – data gathering
Claim 13 - processing the collected information for use by the algorithm in determining the new settings for the neuromodulation device – generic computer implementation as the information is only described as “processed” and the exact mechanism is not disclosed
Claim 17 - allow an operator to find a group of patients having similar or identical health and therapy conditions – insignificant extra solution activity – it is explicitly claimed with a human operator so this is not a function that the system/method itself can do
Claim 18 – predict disease symptoms and/or fluctuations for the patient over time (another abstract idea) based on the determined patient's response with respect to the delivered stimulation – data gathering
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1,3,5-9,13,14,16-18, 21-23 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhang et al (US10905887B2); hereinafter Zhang.
Regarding claims 1 and 21, Zhang teaches a method for programming a neuromodulation device (fig. 3 part 302 programming, fig. 4 neuromodulation device),
comprising:
(a) determining an initial health condition of a patient (fig. 11 (1064) - health condition);
(b) determining one or more conditions and/or symptoms and/or expected outcomes for the patient (fig. 11 (1064), clinical effects mapping requires knowing that initial condition of the patient and how that condition changes);
(c) determining initial settings for the neuromodulation device including one or more treatment parameters based on the determined initial health condition of the patient and/or the one or more determined conditions and/or symptoms and/or expected outcomes, and delivering stimulation to the patient based on the determined initial settings (fig. 11 (1066) - stimulation configuration);
(d) determining a patient's response with respect to the delivered stimulation (fig. 11 (1064) - clinical effect mapping) based on a patient's feedback on the one or more treatment parameters provided through a user input device, the method further comprising monitoring the patient to detect the occurrence of deviations in real time, and/or determining a patient's response with respect to the delivered stimulation based on one or more movements and/or gestures of the patient during stimulation delivery that have been detected during stimulation delivery ("As shown in FIG. 13, the clinical effects can include those derived from signals sensed from the patient. In various embodiments, the clinical effects can be entered by be user and/or the patient, and/or derived automatically from measurements using various sensors.)
(e) implementing an algorithm that is set to modify, based on the determined patient response, the one or more treatment parameters within a predefined range and determine new settings for the neuromodulation device (fig. 29 - generating stimulation parameters part 2990, the neurostimulation system can allow target volumes of stimulation to be defined and refined by clinical effect mapping, provide guidance to a clinician on optimized program settings based on existing clinical effect maps, algorithm-generated guidance, and/or marked positions, and/or automatically configure stimulation settings (col. 7 lines 4-10));
(f) repeating steps (d) and (e) at predefined time intervals and/or in response to a user input until obtaining one or more treatment parameters settings that are identified as optimal by the algorithm based on the patient's[[ (P)]] response to stimulation (col. 24, par. 2 - iterative process), and
(g) maintaining the one or more treatment parameters settings identified as optimal by the algorithm (col. 24, par. 2 - target volume = optimal)
Regarding claim 3, Zhang teaches the method according to claim 1, wherein the patient's response with respect to the delivered stimulation is determined based on a patient's feedback on the one or more treatment parameters (The manually entered information can include observations by the user and/or feedback provided by the patient, The GUI may also allow the user to perform any functions discussed in this document where graphical presentation and/or editing are suitable as may be appreciated by those skilled in the art) provided through a user input device (user input device 858), the method further comprising monitoring the patient to detect the occurrence of deviations in real time (Sensing circuit 742, when included and needed, senses one or more physiological signals for purposes of patient monitoring and/or feedback control of the neurostimulation).
Regarding claim 5, Zhang teaches the method according to claim 1, wherein the method further comprises the step of organizing the determined one or more conditions and/or symptoms and/or expected outcomes for the patient according to predefined criteria of priority (existing clinical effect maps).
Regarding claim 6, Zhang teaches the method according to claim 1, wherein the initial settings for the neuromodulation device are determined based on collected data from one or more groups of patients having identical or similar health conditions than the patient subject to treatment (determined a first clinical effect set resulting from the first test volume being activated by the neurostimulation, and marked the first test volume as a first mark volume (mark “1”). FIG. 11 shows an example in which an initial (the first) stimulation configuration (e.g., with monopolar electrode configuration as shown) is defined by the user (e.g., manually), the stimulation configuration can be generated automatically using a library including data mapping volumes of activation to stimulation configurations, and/or generated automatically using an analytical derivation of the stimulation configuration from the stimulation volume).
Regarding claim 7, Zhang teaches the method according to claim 1, wherein the one or more treatment parameters (fig. 10 part 1066) include one or more of:
- neuromodulation frequency ranges (electrode configuration including polarity and fractionalization, and stimulation pulse parameters including amplitude, width, and frequency);
- neuromodulation current or voltage ranges (stimulation pulse parameters including amplitude);
- electrode selection (electrode configuration including polarity and fractionalization);
- burst modes and patterns (electrode configuration including polarity and fractionalization)
Regarding claim 8, Zhang teaches the method according to claim 2, wherein the user input device is a portable or wearable device (User interface 810 represents an embodiment of user interface 310 and allows the user to define the pattern of neurostimulation pulses and perform various other monitoring and programming tasks. User interface 810 includes a display screen 856, a user input device 858, and an interface control circuit 854. Display screen 856 may include any type of interactive or non-interactive screens, and user input device 858 may include any type of user input devices that supports the various functions discussed in this document, such as touchscreen, keyboard, keypad, touchpad, trackball, joystick, and mouse). Regarding claim 9, Zhang teaches the method according to claim 8, wherein the user input device includes a touch-sensitive display that is configured and adapted to display a user interface including a plurality of selectable options and allow selection of one or more of the displayed selectable options through a touch input (User interface 810 represents an embodiment of user interface 310 and allows the user to define the pattern of neurostimulation pulses and perform various other monitoring and programming tasks. User interface 810 includes a display screen 856, a user input device 858, and an interface control circuit 854. Display screen 856 may include any type of interactive or non-interactive screens, and user input device 858 may include any type of user input devices that supports the various functions discussed in this document, such as touchscreen, keyboard, keypad, touchpad, trackball, joystick, and mouse, navigator button).
Regarding claim 13, Zhang teaches the method according to claim 1, wherein the method further comprises to following steps:
- collecting information on physiological conditions and/or one or more movements and/or gestures of the patient in real time (the sensors can include wearable and/or implantable sensors that senses signals such as movement signal (acceleration), local field potential signal, electroencephalogram (EEG) signal (e sensed using a wearable sensor), single unit activity signal (e.g., sensed using an implantable sensor), electromyogram (EMG) signal (e.g., for indicating rigidity and/or tremor, sensed using a wearable sensor), a posture signal (e.g., for indicating spinal alignment, sensed using a wearable sensor), dopamine/neurotransmitter level signal (e.g., sensed using an implantable sensor placed in certain nuclei), and/or signal indicative of inflammatory factors or other markers of glial cell activity or death (e.g., sensed using an implantable sensor placed in certain nuclei)), and
- processing the collected information for use by the algorithm in determining the new settings for the neuromodulation device (As shown in FIG. 13, the clinical effects can include those derived from signals sensed from the patient - the clinical effects are the data used to determine the new settings for the neuromodulation device).
Regarding claim 14, Zhang teaches the method according to claim 13, wherein said information on environmental and/or physiological conditions and/or one or more movements and/or gestures of the patient is collected through sensor means and/or a camera and/or a microphone or voice command module, wherein said sensor means and/or camera are embedded in a portable device of the patient (the sensors can include wearable and/or implantable sensors that senses signals such as movement signal (acceleration), local field potential signal, electroencephalogram (EEG) signal (e sensed using a wearable sensor), single unit activity signal (e.g., sensed using an implantable sensor), electromyogram (EMG) signal (e.g., for indicating rigidity and/or tremor, sensed using a wearable sensor), a posture signal (e.g., for indicating spinal alignment, sensed using a wearable sensor), dopamine/neurotransmitter level signal (e.g., sensed using an implantable sensor placed in certain nuclei), and/or signal indicative of inflammatory factors or other markers of glial cell activity or death (e.g., sensed using an implantable sensor placed in certain nuclei)).
Regarding claim 22, Zhang teaches the method according to claim 1, wherein the patient's response with respect to the delivered stimulation is determined based on a patient's feedback on the one or more treatment parameters (The manually entered information can include observations by the user and/or feedback provided by the patient, The GUI may also allow the user to perform any functions discussed in this document where graphical presentation and/or editing are suitable as may be appreciated by those skilled in the art) provided through a user input device (user input device 858), the method further comprising monitoring the patient to detect the occurrence of deviations in real time (Sensing circuit 742, when included and needed, senses one or more physiological signals for purposes of patient monitoring and/or feedback control of the neurostimulation).
Regarding claim 23, Zhang teaches the system according to claim 22, wherein the user input device is a portable or wearable device including a touch-sensitive display that is configured and adapted to display a user interface including a plurality of selectable options and allow selection of one or more of the displayed selectable options through a touch input (User interface 810 represents an embodiment of user interface 310 and allows the user to define the pattern of neurostimulation pulses and perform various other monitoring and programming tasks. User interface 810 includes a display screen 856, a user input device 858, and an interface control circuit 854. Display screen 856 may include any type of interactive or non-interactive screens, and user input device 858 may include any type of user input devices that supports the various functions discussed in this document, such as touchscreen, keyboard, keypad, touchpad, trackball, joystick, and mouse, navigator button).
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:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang and Jiang et al (US 20160045751 A1); hereinafter Jiang. Zhang teaches the method according to claim 9. Jiang further teaches color-coded qualitative feedback. It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Zhang with Jiang to make the selectable options color coded as this is the use of a known technique to a known device. Many graphical user interfaces of medical devices use color coded screen selection and even outside of medical devices, pretty much any user facing interface will color-code the options as long as the screen is color enabled.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang and Vera-Portocarrero (US 20200368518 A1); hereinafter Vera. Zhang teaches the method according to claim 8. Zhang fails to teach that there is a means for receiving vocal input. Vera teaches the user input device further includes means for receiving a vocal input from the patient ([0055] UI 18 may further include a softkeys, hard keys (e.g., physical buttons), lights, a speaker and microphone for voice commands). It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Zhang with Vera because it constitutes the use of a known technique to a known device ready for improvement to yield similar results. Voice controlled/activated medical devices are common in the art and implementing voice control into this particular device is an obvious improvement, especially because potential patients of this device may have movement disorders that preclude them from using a touch-based user interface.
Claim(s) 16, 17, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang in view of Offutt et al (US20210316145A1); hereinafter Offut.
Regarding claims 16 and 24, Zhang teaches the method according to claim 1. Zhang fails to teach a searchable database with information about a population of patients. Offutt teaches the method further comprises the following steps:
Storing in a database, data regarding different groups of patients ([0092] the population-informed information may be stored in a database 234), each of the groups including patients having similar or identical health and therapy conditions ([0095] determine whether other patients with similar first information were successfully treated as they moved along the care pathway from baseline to trial to implant);
processing said data according predefined criteria ([0095] processor circuitry 228 of server 26 determine whether patient 14 is a candidate for neurostimulation based on the first information. For example, processor circuitry 228 may compare the first information of the patient to first information of other patients in the population-informed information in the database 234 in memory 226 - comparison implies a threshold), wherein the predefined criteria include criteria for selecting initial settings for the neuromodulation device for patients having similar or identical health and therapy conditions ([0097] the population-informed data may be anonymized data stored in a database 234 on server 26 or accessible by server 26. For example, server 26 may determine different initial stimulation program settings for patients with a particular disease) and
defining the initial settings of the neuromodulation device and the algorithm based on data of a group of patients having similar or identical health and therapy conditions than the patient subject to treatment ([0095] Server 26 may utilize first information to determine a recommended therapy approach including an implant target, initial programming characteristics and behavioral recommendations).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Zhang with Offutt because there is some teaching, suggestion, or motivation to do so. Offutt teaches that accessing a database can help “determine whether patient 14 is a candidate for neurostimulation based on the first information” ([0095]).
Regarding claim 17, the combination of Zhang and Offutt teaches the method of claim 16. Offutt further teaches the method further comprises the following step: setting one or more filters in said database to allow an operator to find a group of patients having similar or identical health and therapy conditions than the patient subject to treatment based on the determined initial health condition of the patient and/or the determined one or more conditions and/or symptoms and/or expected outcomes for the patient ([0095] other patients with similar first information - there must be some search feature to find other patients with similar first information).
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang in view of Hamner et al (US 20210379374 A1); hereinafter Hamner. Zhang teaches the method of claim 1. Zhang fails to teach predicting disease symptoms. Hamner teaches the algorithm is further set to: predict disease symptoms and/or fluctuations for the patient over time based on the determined patient's response with respect to the delivered stimulation ([0093] improve prediction of migraine or headache attacks by determining correlations between biological measures and other recorded symptom events and migraine or headache events). It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Zhang with Hamner because there is some teaching, suggestion, or motivation to do so. Hamner teaches that using the database of other patients can be used to improve prediction of migraine or headache attacks” ([0093]).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dhrasti SNEHAL Dalal whose telephone number is (571)272-0780. The examiner can normally be reached Monday - Thursday 8:30 am - 6:00 pm, Alternate Friday off, 8:30 am - 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carl Layno can be reached at (571) 272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/D.S.D./Examiner, Art Unit 3796
/CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796