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 .
Receipt of Applicant’s Amendment filed April 7, 2026, is acknowledged.
Response to Amendment
Claims 1, 2, 3, 6. 7, 9, 11, 12, 14, 16, 17, and 19 have been amended. Claims 1-20 are pending and are provided to be examined upon their merits.
Response to Arguments
Applicant’s arguments with respect to claims April 7, 2026, have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. A response is provided below in bold where appropriate.
Applicant argues 35 USC §101 Rejection, starting pg. 8 of Remarks:
The Rejection of Claims Under § 101
Claims 1-20 were rejected under 35 U.S.C. @ 101 as allegedly being directed to non- statutory subject matter. Specifically, it was alleged that the recited elements of the independent claims were directed to the abstract idea of "certain methods of organizing human activity", with the allegation that "Diagnosing or determining a patient's health status falls under the abstract concept of managing personal behavior." (Office Action, p. 3).
Applicant respectfully traverses this construction of the claim but submits that this interpretation is rendered moot by the present amendments entered above. These amendments clarify how the underlying technology elements-the interaction workflow in the software platform that receives user interactions-are modified to automatically control the software platform to collect additional data and perform additional tasks. As discussed in paragraph [0061] of the originally filed specification, modifying software in this iterative fashion has the accompanying technical benefits of "reducing user interaction burden, improving the content and types of data presentation, capturing more accurate and more useful data, and ultimately using such data to improve the outcomes of neurostimulation programming and treatment" (emphasis added).
Respectfully, using a software platform or a computer is not enough to make abstract claims statutory.
Applicant also submits that actions performed in the claims are distinguishable from either abstract idea categories of "mental processes" and "organizing of human activity", and that it is incorrect that a "person in their mind and/or with pen and paper" could perform the claimedoperations (See Office Action, p. 4). The human mind or the use of pen and paper will notautomatically control a software platform since both involve manual (human) action. The automatic control recited in the claim requires software technology capabilities and directly excludes human activity.
Applicant has amended their claim where “modifying an interaction workflow in the software platform, to automatically control the software platform to…” Even if this is not abstract, it is not enough to make abstract claims statutory. This is too high level and using software (workflow) to automatically control software platform to perform tasks is essentially using a programmed computer to perform functions.
Finally, even if the claims can be characterized as some type of abstract idea-which is not conceded-Applicant submits that the claims are directed to a practical application of any alleged abstract idea and therefore meet the Step 2A, Prong Two criteria for subject matter eligibility. The recited technique for modifying a software platform to operate in a certain fashion and track certain neurostimulation treatment data provides an improvement to the functioning of technology or technical field as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a). The improved accuracy in collecting data including "user feedback relating to the neurostimulation treatment" and updating a "patient state...associated with the neurostimulation treatment" is used for improving the operation of a neurostimulation system that delivers the neurostimulation treatment. The delivery of neurostimulation is a "particular treatment or prophylaxis for a disease or medical condition" as discussed in MPEP § 2106.04(d)(2). As discussed in paragraphs [0078], [0090], [0092], [0121], and many other paragraphs of Applicant's specification, the use of neurostimulation via spinal cord stimulation or deep brain stimulation can provide improved therapies and treatment for pain and related physiological or psychological conditions. The specialized use of a neurostimulation system and neurostimulation treatment, improved by the claimed software platform, advances the claims well beyond a generic diagnosis or determined health status.
A judicial exception cannot provide that practical application. Respectfully, using a software platform to collect user data is not improving a technology. If accuracy is improved, this would be considered an effect or result of using a software platform, and not an improvement to computer technology itself.
Regarding particular treatment, respectfully, there is no particular treatment claimed for a particular disease. Neurostimulation treatment is a not particular treatment and could be many things.
Based on at least these points and the amendments provided herein, Applicant respectfully requests reconsideration and withdrawal of the rejections under 35 U.S.C. § 101.
The rejection is respectfully maintained but modified for the claim amendments.
Applicant argues 35 USC §112 Rejection, starting pg. 9 of Remarks:
The Rejection of Claims Under § 112
Claims 6 and 16 were rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Specifically, the term "complexity" was alleged to be "relative" and "determination of complexity of a question would be subjectively determined and could be anything." While Applicant respectfully disagrees with this conclusion, claims 6 and 16 are presently amended to recite one aspect of measured complexity discussed in paragraph [0109] of the original specification: the anticipated interaction time with a respective question:
[0109] Other aspects of timing of current or future user interaction tasks may also be modified. Questions can be assigned with an anticipated interaction time (e.g., a total user average and current user average). Questions where a user lingers excessively or frequently skips could be replaced with a similar question or several questions of different wording/less complexity. If questions are still reviewed extensively or skipped, and the questions are gauged to be simple, the user may be uncomfortable answering the question. Additional questions could be included to clarify this, or the question could be removed entirely...
Based on this amendment and the unambiguous explanation provided in the specification of this term, it is believed that the indefiniteness rejection has been rendered moot. Applicant respectfully requests reconsideration and withdrawal of the rejection under § 112(b).
Withdrawn based on the claim amendments.
Applicant argues 35 USC §103 Rejection, starting pg. 10 of Remarks:
The Rejection of Claims Under 103
Claims 1-3, 8-13, and 18-20 were rejected under 35 U.S.C. § 103 as purportedly obvious under Choi (U.S. 2023/0117166).
Claims 4 and 14 were rejected under 35 U.S.C. § 103 as purportedly obvious under Choi in view of Bauhahn (U.S. 2004/0181262).
Claims 5-6 and 15-16 were rejected under 35 U.S.C. § 103 as purportedly obvious under Choi in view of Bauhahn, further in view of Gnanasambandam (U.S. 2022/0384003).
Claims 7 and 17 were rejected under 35 U.S.C. § 103 as purportedly obvious under Choi in view of Bauhahn in view of Johnson (U.S. 2022/0134118).
Applicant respectfully submits that the present obviousness rejection cannot be maintained because there is no teaching, suggestion, or other rationale of obviousness of all claimed elements, which can be established or maintained from the cited combination of references.
In rejecting the previous version of the independent claims, Pages 9-12 of the Office Action cite numerous paragraphs of Choi. For instance, the Office Action extensively discusses Choi's "Patient Report Processing Platform" from its FIG. 12, including the use of a "patient controller application to facilitate patient input/feedback with respect to a trial therapy or treatment involving an IMD or a NIMI device." (See Office Action, p. 9, citing Choi at paragraph [0097]). All of the examples in Choi of "patient input/feedback" involve some measurement of clinical attributes from questionnaires, such as pain levels, sense of well-being, or physiologic and behavioral markers (e.g., in Choi at paragraph [0103]). In contrast, the claimed device and method are used to measure user interactions in the software platform itself. A person of ordinary skill in the art would appreciate a difference between tracking the claimed "attributes of the one or more user interactions that collect user feedback" versus tracking user feedback about a particular aspect of medical treatment.
From Applicant’s argument above…
>>”All of the examples in Choi of "patient input/feedback" involve some measurement of clinical attributes from questionnaires, such as pain levels, sense of well-being, or physiologic and behavioral markers (e.g., in Choi at paragraph [0103]). In contrast, the claimed device and method are used to measure user interactions in the software platform itself.”<<
From Applicant’s specification…
“In Example 2, the subject matter of Example 1 optionally includes subject matter where the user feedback is collected from the patient using one or more questions during each session of the one or more user interactions, and wherein one or more answers corresponding to the one or more questions provide a state of the patient undergoing the neurostimulation treatment.”
Therefore, Applicant’s interactions include questions.
From Applicant’s argument above…
>>”In contrast, the claimed device and method are used to measure user interactions in the software platform itself. A person of ordinary skill in the art would appreciate a difference between tracking the claimed "attributes of the one or more user interactions that collect user feedback" versus tracking user feedback about a particular aspect of medical treatment.”<<
Respectfully, a person answering questions from a mobile device is interacting with a software platform, as taught in Applicant’s own specification.
Second, regarding feedback Choi et al. teaches, as one example…
“The exemplary flow shown in FIG. 13 may be used to provide real-time feedback on the patient's condition. This allows changes to be quantified in real-time and associated with neuromodulation or other therapies, such as by quantifying changes to measure features or characteristics over time. This can be achieved through high-definition capture and comparison of multiple frames of media content (e.g., multiple sequential images or frames of video content). Additionally, multiple types of captured data may be utilized to provide multiple independent data points or to a combination of different data points for analysis/evaluation (e.g., a combination of captured data associated with vascular change data coupled with rigidity data). In aspects where media content is utilized for analysis and evaluation, multiple types of cameras may be used (e.g., media content may be captured using one or more imaging cameras, video cameras, and/or thermal-based cameras, such as infrared cameras) during a session.” [0120]
To clarify this distinction, the elements of the independent and dependent claims are amended as follows:
generate a customized interaction task to collect additional user feedback relating to the neurostimulation treatment, the customized interaction task being customized to the patient based on the attributes of the one or more user interactions
modify an interaction workflow in the software platform, to automatically control the software platform to (i)perform the customized interaction task in the software platform, (ii) collect the additional user feedback relating to the neurostimulation treatment, and (iii) update a patient state, based on the additional user feedback, to track additional attributes associated with the neurostimulation treatment
(amendments underlined). Claim 11 is similarly amended. Applicant respectfully submits that Choi does not teach the claimed identification of "attributes of one or more user interactions" that collect feedback, the generation of a "customized interaction task" to collect additional user feedback, and the modification of an "interaction workflow in the software platform, to automatically control" the interaction task and "collect the additional user feedback" with the software platform, as claimed. As discussed in paragraph [0061] of the originally filed specification, this iterative approach can be used to generate customized tasks and question workflows, based on how a particular user interacts with the software platform.
From Applicant’s argument above…
>>”Applicant respectfully submits that Choi does not teach the claimed identification of "attributes of one or more user interactions" that collect feedback, the generation of a "customized interaction task" to collect additional user feedback, and the modification of an "interaction workflow in the software platform, to automatically control" the interaction task and "collect the additional user feedback" with the software platform, as claimed.”<<
From Choi and identification of attributes…
“In some example arrangements, baseline data regarding pain levels (e.g., as a whole and/or for identified bodily regions), sense of well-being, measurements of physiologic and behavioral markers may be established for the patients, wherein each patient may select a varying trial period, e.g., each day, each week, 2 weeks, etc. Patients may answer a plurality of questions with respect to each baseline, wherein the answers may be alphanumeric input (e.g., on a scale of 0 to 10), graphic input, or A/V input, or any combination thereof (as shown in GUI 1100E and GUI 1100H in FIGS. 11E and 11H respectively as examples). One or more questionnaires 1170, 1172 may be provided as part of a GUI display screen 1100G for purposes of obtaining patient input(s), as exemplified in FIG. 11G, at least some of which may be presented in a set of hierarchical or nested pull-down menus or dialog boxes.” [0103]
As Applicant’s own specification teaches and their claims read on, this identification can be provided from questions.
From Applicant’s argument above…
>>”Applicant respectfully submits that Choi does not teach the claimed identification of "attributes of one or more user interactions" that collect feedback, the generation of a "customized interaction task" to collect additional user feedback, and the modification of an "interaction workflow in the software platform, to automatically control" the interaction task and "collect the additional user feedback" with the software platform, as claimed.”<<
From Choi on generation of a customized interaction task…
“In some aspects, exercise programs (moves) may have different difficulty levels. For patients who have more severe disease conditions or faster progressive severity, the program may start with the easiest level(s) and work their way up to higher difficulties. The AI can also correspondingly offer more feedback and support as the exercise difficulties increase.” [0176]
Therefore, exercise program customized for patients and the program start with (generating) various levels of difficulties.
From Applicant’s argument above…
>>”Applicant respectfully submits that Choi does not teach the claimed identification of "attributes of one or more user interactions" that collect feedback, the generation of a "customized interaction task" to collect additional user feedback, and the modification of an "interaction workflow in the software platform, to automatically control" the interaction task and "collect the additional user feedback" with the software platform, as claimed.”<<
From Choi…
Person makes the wrong move during patient performance of tasks or activities (modifying interaction workflow), a vibration can take place (automatically control the software platform)…
“In step 2004, feedback may be provided during patient performance of the task(s) or activities. Having this measurement in turn offers opportunities for the AI in the physical therapy application to offer feedback to the patient if the patient repetitively makes the wrong move or mistimes the move. The feedback can be achieved via actuators embedded into the fabrics of the patient's clothing, or special clothing articles (such as gloves, socks, shoes) that have embedded actuators. For example, if the patient is supposed to shift his weight to the left foot but failed to do so, a vibration can take place on the left foot to remind the patient. The cadence and frequency of the feedback can be driven by the AI or set by the patient. Presumably, as the patient gets better via practicing, the haptic feedback can change to a different vibration pattern to signal more complex feedback, such as to accelerate movements, deaccelerate movements, or even signaling a “good job”.” [0175]
The patient’s neurostimulation titrated (customized) with performance of task of activities (interaction task), in a closed loop manner (collect user feedback), adjustments (update) therapeutic [patient] state when performing various exercises (track additional attributes)…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
The Office Action on Pages 9-12 cites many examples in Choi involving "recommendations/reconfigurations" of some neurostimulation therapy. For example, paragraph [0059] of Choi discusses "context-sensitive selection of neuromodulation programming/settings." However, Choi does not teach any approach for modifying the interaction workflow of what questions and interaction tasks are being asked. Choi's modification of therapy workflows is different than the claimed approach for modifying interaction workflows and the manner in which data is collected. Choi's use of "questions", "questionnaires", "pull-down menus", or "dialog boxes" does not appear to have any ability to be customized or modified.
Respectfully, Applicant is also using questions in their specification.
From Choi…
“Patient aggregate data (PAD) 1250 may include basic patient data including patient name, age, and demographic information, etc. PAD 1250 may also include information typically contained in a patient's medical file such as medical history, diagnosis, results from medical testing, medical images, etc. The data may be inputted directly into system 1200 by a clinician or medical professional. Alternatively, this data may be imported from digital health records of patients from one or more health care providers or institutions.” [0106]
From Fig.12, ref. 1250…
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Therefore, patient data includes patient name and includes device use/events data and sensor data.
The claimed approach is also not taught or suggested in the other cited references (Bauhahn, Gnanasambandam, or Johnson) that are cited for the various rejections of the dependent claims. Thus, for at least these reasons, the combination of the cited references fails to teach or suggest each and every element of claims 1 and 11, and a prima facie case of obviousness under the art cannot be maintained for these independent claims. Dependent claims 2-10 and 12-20 ultimately depend from one of independent claims 1 or 11 and are allowable over the cited references, alone or in any combination, for at least the reasons set forth above for the independent claims.
Accordingly, the pending claims are not obvious and are allowable over the references cited in the present rejection. Applicant respectfully requests reconsideration and withdrawal of the rejections under 35 U.S.C. § 103 for the pending claims, and that the Examiner allow these claims.
The rejection has been modified but respectfully maintained based on the claim amendments.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-20 are directed to a system or method, which are statutory categories of invention. (Step 1: YES).
The Examiner has identified method Claim 11 as the claim that represents the claimed invention for analysis and is similar to system claim 1.
Claim 11 recites the limitations of:
A method for analyzing user interaction associated with a neurostimulation treatment, comprising:
receiving user interaction data associated with a patient undergoing the neurostimulation treatment, wherein the user interaction data indicates attributes of one or more user interactions in a software platform that collect user feedback relating to the neurostimulation treatment;
identifying attributes of the one or more user interactions, from the user interaction data;
generating a customized interaction task to collect additional user feedback relating to the neurostimulation treatment, the customized interaction task being customized to the patient based on the attributes of the one or more user interactions; and
modifying an interaction workflow in the software platform, to automatically control the software platform to (i) perform the customized interaction task in the software platform, (ii) collect the additional user feedback relating to the neurostimulation treatment, and (iii) update a patient state, based on the additional user feedback, to track additional attributes associated with the neurostimulation treatment.
These above limitations, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. The claim recites elements, in non-bold above, which covers performance of the limitation as managing personal behavior. Diagnosing or determining a patient’s health status falls under the abstract concept of managing personal behavior. It is important to note that the examples provided by the MPEP such as social activities, teaching, and following rules or instructions are provided as examples and not an exclusive listing and that MPEP 2106.04(a)(2) II stating certain activity between a person and a computer may fall within the “certain methods of organizing human activity” grouping. Receiving user interaction data associated with a patient undergoing neurostimulation treatment, collect user feedback relating to the neurostimulation treatment, identifying attributes of the one or more user interactions from the user interaction data, generating a customized interaction task to collect additional user feedback, and modifying a workflow to perform the customized interaction task, collect additional feedback relating to neurostimulation treatment, and update a patient state based on user feedback is managing personal behavior including determining the health status of a patient and following rules or instructions (receiving user interaction data, collect user feedback, collect additional user input relating to treatment) and teaching (generating a task to collect additional user input and modifying an interaction workflow to perform the task). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as managing personal behavior, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Claim 1 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
In as much as a person in their mind and/or with pen and paper can receive interaction data, identify attributes of the user interactions, generate a task to collect additional user input, and modify an interaction workflow to perform a task, the claims are also abstract under Mental Processes grouping of abstract ideas.
This judicial exception is not integrated into a practical application. In particular, the claims only recite: computing device, processor, memory device (Claim 1). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The software platform appears to be just software recited at a high level of generality (para. [0120] in the specification). Automatically control the software platform to perform tasks is claimed at too high a level and is what a software program or computer rules do to control a computer. Control a software platform is also incidental to the claim as the claimed invention is not directed to controlling software platforms. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1 and 11 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Steps such as receiving are steps that are considered insignificant extra solution activity and mere instructions to apply the exception using general computer components (see MPEP 2106.05(d), II). Thus claims 1 and 11 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 2-10 and 12-20 further define the abstract idea that is present in their respective independent claims 1 and 11 and thus correspond to Certain Methods of Organizing Human Activity and Mental Processes and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. The claims themselves recite abstract steps or further limit abstract concepts. Claims 3, 7, 8, 13, 17, and 18 recite a software platform, which is just software recited at a high level of generality. Claims 8 and 18 recite personal computer, tablet, smartphone, remote control, or wearable device which are generic computer components at a high level of generality. Claim 9 recites processor at a high level of generality. Therefore, the claims 2-10 and 12-20 are directed to an abstract idea. Thus, the claims 1-20 are not patent-eligible.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for amendments to claims should Applicant amend. The purpose of this is to reduce potential 35 U.S.C. §112(a) or §112 1st paragraph issues that can arise when claims are amended without support in the specification. The Examiner thanks the Applicant in advance.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 8-13, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Pub. No. US 2023/0117166 to Choi et al.
Regarding claims 1 and 11
(claim 11) A method for analyzing user interaction associated with a neurostimulation treatment, comprising:
receiving user interaction data associated with a patient undergoing the neurostimulation treatment, wherein the user interaction data indicates attributes of one or more user interactions in a software platform that collect user feedback relating to the neurostimulation treatment;
Choi et al. teaches:
Interactions involving entities…
“Additional details with respect to the various constituent components of the digital health infrastructure 1212, example external devices 1206 comprising clinician programmer devices 1208, patient controller devices 1210 and/or third-party devices 1211, as well as various interactions involving the network-based entities and the end points (also referred to as edge devices) will be set forth immediately below in order to provide an example architectural framework wherein one or more of the foregoing embodiments may be implemented and/or augmented according to the teachings herein.” [0064]
Fig. 12 teaches example of patients and receiving user interaction (double arrows between devices/platforms)…
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Input/feedback (receiving feedback) involving implantable medical device (IMD) or noninvasive/minimally invasive (NIMI) device….
“… In still further embodiments, one or more code portions may be provided with the patient controller application to facilitate patient input/feedback with respect to a trial therapy or treatment involving an IMD or a NIMI device, which may be augmented with one or more data labeling buttons, icons, pictograms, etc., wherein the patient input/feedback data may be provided to a network-based AI/ML model for facilitating intelligent decision-making with respect to whether the IMD/NIMI device should be deployed in a more permanent manner (e.g., implantation) and/or whether a particular therapy setting or a set of settings, including context-sensitive therapy program selection, may need to be optimized or otherwise reconfigured.” [0097]
Neurostimulation therapy (treatment) using IMD…
“In some arrangements involving neurostimulation therapy, different stimulation settings and/or programs may be configured for providing varied levels of comfort to the patients, wherein respective patients may likely need to change individual settings depending on a number of factors (e.g., time of day, type(s) and/or level(s) of activities or tasks being engaged by the patients, and the like). Further, continued use of a stimulation program or setting over an extended period of time could result in habituation that may reduce the benefits of therapy. Some example embodiments herein may therefore relate to a system and method for providing recommendations/reconfigurations of program settings based on the patient's usage of the IMD and clinical observations/recommendations, which may facilitate context-sensitive selection of neuromodulation programs/settings.” [0059]
Using software (software platform)…
“A controller for neurostimulation may be implemented in a number of system locations for any of the embodiments discussed herein. For example, a processor or suitable circuit may implement the operations of a suitable controller (using software instructions and/or embedded circuit logic) and the processor or suitable circuit may be included within an implantable pulse generator, a patient controller device, a clinician programmer device, a wearable electronic device, a remote health digital platform/server, or any other suitable computing system.” [0202]
Implement the disclosure using memory and processors…
“One or more embodiments of the present patent disclosure may be implemented using different combinations of software, firmware, and/or hardware. Thus, one or more of the techniques shown in the Figures (e.g., flowcharts) may be implemented using code and data stored and executed on one or more electronic devices or nodes (e.g., a subscriber client device or end station, a network element, etc.). Such electronic devices may store and communicate (internally and/or with other electronic devices over a network) code and data using computer-readable media, such as non-transitory computer-readable storage media (e.g., magnetic disks, optical disks, random access memory, read-only memory, flash memory devices, phase-change memory, etc.), transitory computer-readable transmission media (e.g., electrical, optical, acoustical or other form of propagated signals—such as carrier waves, infrared signals, digital signals), etc. In addition, such network elements may typically include a set of one or more processors coupled to one or more other components, such as one or more storage devices (e.g., non-transitory machine-readable storage media) as well as storage database(s), user input/output devices (e.g., a keyboard, a touch screen, a pointing device, and/or a display), and network connections for effectuating signaling and/or bearer media transmission.” [0052]
See Software Platform below.
identifying attributes of the one or more user interactions, from the user interaction data;
Example of individual settings (identifying attributes) based on user activities or tasks (interactions)…
“In some arrangements involving neurostimulation therapy, different stimulation settings and/or programs may be configured for providing varied levels of comfort to the patients, wherein respective patients may likely need to change individual settings depending on a number of factors (e.g., time of day, type(s) and/or level(s) of activities or tasks being engaged by the patients, and the like). Further, continued use of a stimulation program or setting over an extended period of time could result in habituation that may reduce the benefits of therapy. Some example embodiments herein may therefore relate to a system and method for providing recommendations/reconfigurations of program settings based on the patient's usage of the IMD and clinical observations/recommendations, which may facilitate context-sensitive selection of neuromodulation programs/settings.” [0059]
Another example of established (identifying) pain levels, sense of well-being, etc. (attributes) based on trail periods with patients answer questions (user interaction)…
“In some example arrangements, baseline data regarding pain levels (e.g., as a whole and/or for identified bodily regions), sense of well-being, measurements of physiologic and behavioral markers may be established for the patients, wherein each patient may select a varying trial period, e.g., each day, each week, 2 weeks, etc. Patients may answer a plurality of questions with respect to each baseline, wherein the answers may be alphanumeric input (e.g., on a scale of 0 to 10), graphic input, or A/V input, or any combination thereof (as shown in GUI 1100E and GUI 1100H in FIGS. 11E and 11H respectively as examples). One or more questionnaires 1170, 1172 may be provided as part of a GUI display screen 1100G for purposes of obtaining patient input(s), as exemplified in FIG. 11G, at least some of which may be presented in a set of hierarchical or nested pull-down menus or dialog boxes.” [0103]
generating a customized interaction task to collect additional user feedback relating to the neurostimulation treatment, the customized interaction task being customized to the patient based on the attributes of the one or more user interactions; and
Patient data…
“Patient aggregate data (PAD) 1250 may include basic patient data including patient name, age, and demographic information, etc. PAD 1250 may also include information typically contained in a patient's medical file such as medical history, diagnosis, results from medical testing, medical images, etc. The data may be inputted directly into system 1200 by a clinician or medical professional. Alternatively, this data may be imported from digital health records of patients from one or more health care providers or institutions.” [0106]
From Fig.12, ref. 1250 with patient data, device use/event data and sensor data (customized interaction)…
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Program may start (generating) different exercise level difficulties (tasks) based on patients (customized interaction)…
“In some aspects, exercise programs (moves) may have different difficulty levels. For patients who have more severe disease conditions or faster progressive severity, the program may start with the easiest level(s) and work their way up to higher difficulties. The AI can also correspondingly offer more feedback and support as the exercise difficulties increase.” [0176]
Providing (generating) recommendations/reconfigurations (tasks) to facilitate context-sensitive selection (task customized to the patient) based on use of stimulation program (attributes of user interactions)….
“In some arrangements involving neurostimulation therapy, different stimulation settings and/or programs may be configured for providing varied levels of comfort to the patients, wherein respective patients may likely need to change individual settings depending on a number of factors (e.g., time of day, type(s) and/or level(s) of activities or tasks being engaged by the patients, and the like). Further, continued use of a stimulation program or setting over an extended period of time could result in habituation that may reduce the benefits of therapy. Some example embodiments herein may therefore relate to a system and method for providing recommendations/reconfigurations of program settings based on the patient's usage of the IMD and clinical observations/recommendations, which may facilitate context-sensitive selection of neuromodulation programs/settings.” [0059]
The patient’s therapy (customized interaction) with closed-loop (feedback) and titrated during performance of tasks or activities (attributes of user interactions)…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
modifying an interaction workflow in the software platform, to automatically control the software platform to (i) perform the customized interaction task in the software platform, (ii) collect the additional user feedback relating to the neurostimulation treatment, and (iii) update a patient state, based on the additional user feedback, to track additional attributes associated with the neurostimulation treatment.
{
From Applicant’s Specification on “task”…
[0008] In Example 4, the subject matter of any one or more of Examples 1-3 optionally includes subject matter where the task includes multiple questions to provide to the patient in a subsequent user interaction, wherein the interaction workflow controls presentation of the multiple questions to the patient, and wherein a number, type, or order of the multiple questions is customized to the patient based on the attributes.
Therefore, questions may be a task.
}
Person makes the wrong move during patient performance of tasks or activities (modifying interaction workflow), a vibration can take place (automatically control the software platform)…
“In step 2004, feedback may be provided during patient performance of the task(s) or activities. Having this measurement in turn offers opportunities for the AI in the physical therapy application to offer feedback to the patient if the patient repetitively makes the wrong move or mistimes the move. The feedback can be achieved via actuators embedded into the fabrics of the patient's clothing, or special clothing articles (such as gloves, socks, shoes) that have embedded actuators. For example, if the patient is supposed to shift his weight to the left foot but failed to do so, a vibration can take place on the left foot to remind the patient. The cadence and frequency of the feedback can be driven by the AI or set by the patient. Presumably, as the patient gets better via practicing, the haptic feedback can change to a different vibration pattern to signal more complex feedback, such as to accelerate movements, deaccelerate movements, or even signaling a “good job”.” [0175]
The patient’s neurostimulation titrated (customized) with performance of task of activities (interaction task), in a closed loop manner (collect user feedback), adjustments (update) therapeutic [patient] state when performing various exercises (track additional attributes)…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
Settings and/or programs may be configured (controlling interaction workflow) for varied levels of comfort (tasks)…
“In some arrangements involving neurostimulation therapy, different stimulation settings and/or programs may be configured for providing varied levels of comfort to the patients, wherein respective patients may likely need to change individual settings depending on a number of factors (e.g., time of day, type(s) and/or level(s) of activities or tasks being engaged by the patients, and the like). Further, continued use of a stimulation program or setting over an extended period of time could result in habituation that may reduce the benefits of therapy. Some example embodiments herein may therefore relate to a system and method for providing recommendations/reconfigurations of program settings based on the patient's usage of the IMD and clinical observations/recommendations, which may facilitate context-sensitive selection of neuromodulation programs/settings.” [0059]
Example of user interface to provide feedback or commands (controlling an interaction workflow) to patient to move their face, hands (perform a task), using a GUI component (in the software platform) …
“As shown in FIG. 18C, the user interface 1820 may display the landmark graphical features corresponding to the kinematic components selected by the clinician, enabling the patient to view the same kinematics as the clinician. Additionally, user interface 1820 may be used to provide feedback or commands to the patient, such as instructions for the patient to move their face, hands, limbs, torso, etc. into an optimal position for generation of the selected analytics. For example, user interface 1820 includes GUI component 1821, shown as a box, around the patient's right hand. In some aspects, the GUI component 1821 may provide a visual indication regarding whether the patient or a portion of the patient's body, is in a desired or optimal visual location. For example, the GUI component 1821 may be colored “green” to indicate the patient is in the optimal location and colored “red” to indicate the need to reposition. Further, the GUI component 1821 may include one or more indicators, shown as an arrow in FIG. 18C, to indicate a direction of movement to place the patient into the optimal location.” [0160]
Another example of guided instructions for tasks to complete using instructions…
“In step 2003, the patient is provided guided instructions for one or more physical tasks or activities to be completed by the patient. In some aspects, the guided instructions may include video and/or audio presentations. For example, a video or images and text may be displayed to the user to illustrate the types of tasks or activities the patient is to perform.” [0166]
“Patients with movement disorders such as Parkinson's disease often report difficulties with everyday tasks such as buttoning (e.g., a shirt), brushing, and/or writing. In some embodiments, the physical therapy application may be tailored to the specific condition or disorder of the patient in order to train the patient on activities impacted by their specific condition or disorder, which may provide substantial improvements in the patient's quality of life.” [0167]
Software Platform
Choi et al. teaches software. They do not literally teach software platform. However, one of ordinary skill in the art would recognize that a software platform could consist just of software on a computer.
It would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s filing to modify Choi et al. with the knowledge available to such an artisan that software would include a computer and could be considered a software platform. This would have been known work in the field of endeavor prompting variations of it in the same field based on use of software and would provide predictable results.
Regarding claims 2 and 12
(claim 12) The method of claim 11, wherein the user feedback relating to the neurostimulation treatment is collected from the patient using one or more questions during each session of the one or more user interactions, and wherein one or more answers corresponding to the one or more questions provide a state of the patient undergoing the neurostimulation treatment.
Choi et al. teaches:
Patients asked questions to provide baseline data (state of patient)…
“In some example arrangements, baseline data regarding pain levels (e.g., as a whole and/or for identified bodily regions), sense of well-being, measurements of physiologic and behavioral markers may be established for the patients, wherein each patient may select a varying trial period, e.g., each day, each week, 2 weeks, etc. Patients may answer a plurality of questions with respect to each baseline, wherein the answers may be alphanumeric input (e.g., on a scale of 0 to 10), graphic input, or A/V input, or any combination thereof (as shown in GUI 1100E and GUI 1100H in FIGS. 11E and 11H respectively as examples). One or more questionnaires 1170, 1172 may be provided as part of a GUI display screen 1100G for purposes of obtaining patient input(s), as exemplified in FIG. 11G, at least some of which may be presented in a set of hierarchical or nested pull-down menus or dialog boxes.” [0103]
Regarding claims 3 and 13
(claim 13) The method of claim 12, wherein the attributes of the one or more user interactions relate to at least one of:
a number of tasks completed in each session;
a number of questions completed in each session;
an ongoing or historical usage of the software platform;
an ongoing or historical pattern of use of the software platform;
an amount of time of engagement in each session;
an amount of time of engagement with respective types of questions in each session;
a time of day of engagement in each session; or
Choi et al. teaches:
Example of time of day…
“In some arrangements involving neurostimulation therapy, different stimulation settings and/or programs may be configured for providing varied levels of comfort to the patients, wherein respective patients may likely need to change individual settings depending on a number of factors (e.g., time of day, type(s) and/or level(s) of activities or tasks being engaged by the patients, and the like). Further, continued use of a stimulation program or setting over an extended period of time could result in habituation that may reduce the benefits of therapy. Some example embodiments herein may therefore relate to a system and method for providing recommendations/reconfigurations of program settings based on the patient's usage of the IMD and clinical observations/recommendations, which may facilitate context-sensitive selection of neuromodulation programs/settings.” [0059]
a pattern of engagement in each session.
Example of different simulation patterns for patient…
“Clinician controller device 1208 may permit programming of IPG 170 to provide a number of different stimulation patterns or therapies to the patient as appropriate for a given patient and/or disorder. Examples of different stimulation therapies include conventional tonic stimulation (continuous train of stimulation pulses at a fixed rate), BurstDR stimulation (burst of pulses repeated at a high rate interspersed with quiescent periods with or without duty cycling), “high frequency” stimulation (e.g., a continuous train of stimulation pulses at 10,000 Hz), noise stimulation (series of stimulation pulses with randomized pulse characteristics such as pulse amplitude to achieve a desired frequency domain profile). Any suitable stimulation pattern or combination thereof can be provided by IPG 170 according to some embodiments. Controller device 1208 communicates the stimulation parameters and/or a series of pulse characteristics defining the pulse series to be applied to the patient to IPG 170 to generate the desired stimulation therapy.” [0054]
Regarding claims 8 and 18
(claim 18) The method of claim 11, wherein the interaction workflow is a patient interaction workflow to occur with the patient, and wherein the software platform is implemented on a patient computing device provided by a personal computer, tablet, smartphone, remote control, or wearable device.
Choi et al. teaches:
Example of smartphone…
“As previously discussed, a patient may employ a patient controller “app” on the patient's smartphone or other electronic device to control the operations of the patient's IMD or minimally invasive device. For example, for spinal cord stimulation or dorsal root stimulation, the patient may use the patient controller app to turn the therapy on and off, switch between therapy programs, and/or adjust stimulation amplitude, frequency, pulse width, and/or duty cycle, among other operations. The patient controller app is adapted to log such events (“Device Use/Events Data”) and communicate the events to system 1200 to maintain a therapy history for the patient for review by the patient's clinician(s) to evaluate and/or optimize the patient's therapy as appropriate.” [0107]
Regarding claims 9 and 19
(claim 19) The method of claim 11, further comprising:
identifying the patient state based on one or more of the user feedback or objective data associated with the patient;
Choi et al. teaches:
Example of patient self-reported (feedback, objective data) and state…
“PAD 1250 may include “Patient Self-Report Data” obtained using a digital health care app operating on patient controller devices 1210. The patient self-report data may include patient reported levels of pain, patient well-being scores, emotional states, activity levels, and/or any other relevant patient reported information. The data may be obtained using the MYPATH app from Abbott as one example.” [0108]
causing a change to the interaction workflow based on the identified patient state; and
Feedback and therapy setting or set of setting optimized (change to interaction workflow)…
“… In still further embodiments, one or more code portions may be provided with the patient controller application to facilitate patient input/feedback with respect to a trial therapy or treatment involving an IMD or a NIMI device, which may be augmented with one or more data labeling buttons, icons, pictograms, etc., wherein the patient input/feedback data may be provided to a network-based AI/ML model for facilitating intelligent decision-making with respect to whether the IMD/NIMI device should be deployed in a more permanent manner (e.g., implantation) and/or whether a particular therapy setting or a set of settings, including context-sensitive therapy program selection, may need to be optimized or otherwise reconfigured.” [0097]
causing a change in a closed-loop programming therapy of a neurostimulation device based on the identified patient state, wherein the patient state relates to one or more of:
Parameters of neurostimulation therapy titrated (changed) in a closed-loop manner…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
sleep, actigraphy, accelerometry, pain, movement, stress, disease-related symptoms, emotional state, medication state, or activity during use of at least one neurostimulation program.
Example of performance of activities and exercises…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
Regarding claims 10 and 20
(claim 20) The method of claim 19, wherein the closed-loop programming therapy causes an automatic change to neurostimulation programming settings on the neurostimulation device, and wherein the automatic change to the neurostimulation programming settings controls one or more of:
pulse patterns, pulse shapes, a spatial location of pulses, electric fields or activating functions of active electrodes, waveform shapes, or a spatial location of waveform shapes, for modulated energy provided with a plurality of leads of the neurostimulation device.
Choi et al. teaches:
Example of waveform for specific exercise…
“In step 2005, the stimulation parameters of the patient's neurostimulation therapy may be titrated during the performance of the tasks or activities. For example, if a patient has an implanted device such as DBS, the device can interact with the exercise platform in a closed-loop manner. The efficacy of neurostimulation for a neurological disorder can be state-dependent, as exercising could potentially change the efficacy of certain programmed settings. In such a situation, the implanted device can be controlled (e.g., by the patient controller device) to make small adjustments to programmed parameters to “explore” the therapeutic state space when patient performs various exercises, and the data can be used as training data for a deep learning algorithm to predict which parameter set is best suited for each exercise for this particular patient, thereby enabling an “exercise mode” to be individually developed for each patient. This can also include explorations of known and/or novel stimulation waveforms and paradigms that could be better suited for the patient given a specific exercise.” [0178]
Pattern of pulses and leads (plural)…
“…The variation in parameters changes the pattern of pulses applied to the patient via electrodes of one or more stimulation leads 2704. One or more of the stimulation parameters may be varied including pulse amplitude, pulse width, pulse frequency, burst frequency, noise profile, electrode polarities, etc. In some embodiments, different pulse patterns are applied such as tonic stimulation, burst stimulation, high frequency stimulation, multi-frequency stimulation, and/or the like. As parameters and/or patterns are varied, the AI/ML classification of the patient is repeated to determine whether the change in the neurostimulation therapy causes the patient to be “closer” to a “healthy” state (e.g., without pain). When stimulation parameters are identified where the patient's EEG data more closely matches the EEG data of a healthy control population, the variation of the parameters may cease and the stimulation therapy may be considered optimized. Although control of neurostimulation is described using operations of device 2702, control of neurostimulation may be implemented in other locations such as IPG 2701 or elsewhere according to other embodiments.” [0195]
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over the reference in section (6) in further view of Pub. No. US 2004/0181262 to Bauhahn
Regarding claims 4 and 14
(claim 14) The method of claim 11, wherein the customized interaction task includes multiple questions to provide to the patient in a subsequent user interaction, wherein the interaction workflow controls presentation of the multiple questions to the patient, and wherein a number, type, or order of the multiple questions is customized to the patient based on the attributes.
Choi et al. teaches:
Plurality of questions answered by patient…
“In some example arrangements, baseline data regarding pain levels (e.g., as a whole and/or for identified bodily regions), sense of well-being, measurements of physiologic and behavioral markers may be established for the patients, wherein each patient may select a varying trial period, e.g., each day, each week, 2 weeks, etc. Patients may answer a plurality of questions with respect to each baseline, wherein the answers may be alphanumeric input (e.g., on a scale of 0 to 10), graphic input, or A/V input, or any combination thereof (as shown in GUI 1100E and GUI 1100H in FIGS. 11E and 11H respectively as examples). One or more questionnaires 1170, 1172 may be provided as part of a GUI display screen 1100G for purposes of obtaining patient input(s), as exemplified in FIG. 11G, at least some of which may be presented in a set of hierarchical or nested pull-down menus or dialog boxes.” [0103]
Choi et al. teaches neurostimulation. They also teach question. They do not teach multiple questions based on order.
Bauhahn also in the business of neurostimulation teaches:
Particular questions (plural) based on therapy contexts (customized to the patient) and prearranged (ordered) according to context…
“In addition, memory 64 may store question set 66, selection criteria 68, contextual data 69 and stimulation settings 71. Question set 66 may contain a set of questions formulated by a clinician for presentation to patient 12 via patient programmer 22. Selection criteria 68 maps questions in question set 66 to specific neurostimulation therapy contexts. Accordingly, upon determination of a particular context, processor 60 accesses selection criteria 68 to select particular questions from question set 66 for presentation to patient 12. As an alternative, question set 66 may contain groups of questions that are prearranged according to context. In this case, processor 60 selects a prearranged group of questions rather than selecting individual questions to form a group.” [0041]
Questions based on context that includes symptoms or patient events or activities (patient attributes)…
“In general, the invention is directed to techniques for collection and management of information relating to operation of an implantable neurostimulation device and efficacy of neurostimulation therapy based on user input. The techniques may involve selection of questions for the user to answer based on the context of the therapy delivered by the neurostimulation device at the time the questions are presented. In this manner, appropriate data may be collected on a timely basis for specific contexts, e.g., specific therapy settings, symptoms, or patient events or activities. The neurostimulation therapy may treat pain, movement disorders or other health problems.” [0005]
It would have been obvious to one of ordinary skill in the art before the effective filing date to include in the method and system of Choi et al. the ability to have multiple questions as taught by Bauhahn since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Further motivation is provided by Bauhahn who teaches the benefits of using multiple questions for therapy.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over the combined references in section (7) in further view of Pub. No. US 2022/0384003 to Gnanasambandam et al.
Regarding claims 5 and 15
(claim 15) The method of claim 14, wherein a priority is determined for each question of the multiple questions, and wherein the number, type, or order of the multiple questions is further customized to the patient based on the priority of each question.
The combined references teach question and order. They do not teach priority.
Gnanasambandam et al. also in the business of question and order teaches:
Questions based on parameters (customized) of inquirer (patient)…
“In particular, during the first round of analysis, the cognitive agent 110 parses aspects of the originating question into associated parameters. The parameters represent variables useful for answering the originating question. For example, the question “is a blood sugar of 90 normal” may be parsed and associated parameters may include, an age of the inquirer, the source of the value 90 (e.g., in home test or a clinical test), a weight of the inquirer, and a digestive state of the user when the test was taken (e.g., fasting or recently eaten). The parameters identify possible variables that can impact, inform, or direct an answer to the originating question.” [0245]
Parameters (attributes) for question…
“For purposes of the example illustrated in FIG. 4, in the first round of analysis, the cognitive intelligence platform 102 inserts each parameter into the workspace associated with the originating question (line 402). Additionally, based on the identified parameters, the cognitive intelligence platform 102 identifies a customized set of follow up questions (“a first set of follow-up questions). The cognitive intelligence platform 102 inserts first set of follow-up questions in the workspace associated with the originating question.” [0246]
Ranking (order) of questions and based on relevant (priority) to originating question…
“With regards to the second set of follow-up questions (or any set of follow-up questions), the cognitive intelligence platform 102 calculates a relevance index, where the relevance index provides a ranking of the questions in the second set of follow-up questions. The ranking provides values indicative of how relevant a respective follow-up question is to the originating question. To calculate the relevance index, the cognitive intelligence platform 102 can use conversations analysis techniques described in HPS ID20180901-01_method. In some embodiments, the first set or second set of follow up questions is presented to the user in the form of the microsurvey 116.” [0253]
It would have been obvious to one of ordinary skill in the art before the effective filing date to include in the method and system of the combined references the ability to prioritize questions as taught by Gnanasambandam et al. since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Further motivation is provided by Gnanasambandam et al. who teaches the benefits of ranking questions based on relevancy and this allows for providing meaningful questions to users.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over the combined references in section (7) in further view of Pub. No. US 2013/0211848 to Stupp.
Regarding claims 6 and 16
(claim 16) The method of claim 14, wherein an anticipated interaction time is determined for each question of the multiple questions, and wherein the number, type, or order of the multiple questions is further customized to the patient based on the anticipated interaction time of each question.
The combined references teach questions. They do not teach interaction time.
Stupp also in the business of questions teaches:
Temporal onset in an individual (anticipated interaction time), question about exposure (question type) is provided, and where additional dependent questions with temporal sampling rate occur…
“Embodiments of a computer system, a user interface, a technique for collecting information, and an associated computer-program product (e.g., software) for use with the computer system are described. During the collection technique, after receiving information specifying an occurrence of a temporal onset of an episodic manifestation of a chronic disease in an individual during a time interval, a question and associated categorical answers about exposure of the individual to a potential trigger of the episodic manifestation are provided. Note that the categorical answers include time intervals, and both the time interval and the time intervals correspond to a first temporal sampling rate. If an answer to the question specifies one of the time intervals that is the same as the time interval, another question (which is sometimes referred to as a `dependent question`) and additional associated categorical answers about the exposure of the individual to the potential trigger of the episodic manifestation are provided. These additional categorical answers include additional time intervals corresponding to a second temporal sampling rate, which may be within the time interval, and which allows a causal relationship between the exposure to the potential trigger and the occurrence of the temporal onset to be specified.” [0029]
It would have been obvious to one of ordinary skill in the art before the effective filing date to include in the method and system of the combined references the ability to have interaction time with questions as taught by Stupp since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Further motivation is provided by Stupp who teaches the benefits of association information when asking questions based on time interaction in order to obtain better questions.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over the reference in section (6) in further view of Pub. No. US 2004/0181262 to Bauhahn
Pub. No. US 2022/0134118 to Johnson.
Regarding claims 7 and 17
(claim 17) The method of claim 11, wherein the customized interaction task includes a scheduled time period to be presented in the software platform, wherein the scheduled time period includes a start time and an end time, and wherein the scheduled time period is customized to the patient based on the attributes.
Choi et al. teaches:
Stimulation start and termination (end) controls…
“In still further embodiments, separate remote therapy session intervention controls (e.g., pause and resume controls) may be provided in addition to stimulation start and termination controls, which may be operative independent of or in conjunction with AV communication session controls, in a manner similar to example patient controller GUI embodiments set forth hereinbelow. Still further, data labeling buttons or controls may also be provided in a separate overlay or window of GUI screen 600 (not shown in FIG. 6) to allow or otherwise enable the clinician to provide different types of data labels for the AV data and therapy settings data for purposes of some embodiments of the present patent disclosure.” [0084]
Choi et al. teaches neurostimulation. They also teach start and end time. They do not teach schedule.
Johnson also in the business of nerve stimulation teaches:
Prescribed therapy (customized to the patient) and begin and turns off time and exact dosing schedule…
“The techniques of this disclosure generally relate to systems and methods for managing duty cycled electrical nerve stimulation. In some embodiments, the duty cycling can be used to fill the notion of a “prescribed therapy regimen,” thereby enabling a user defined stimulation regimen for patients, or stimulation therapy can be provided at particular times or occurring within a desired window of time for a defined interval (e.g., stimulation therapy begins at 10 PM and turns off at 6 AM, Monday through Friday, but shifts to 11 PM to 7 AM Saturday through Sunday). Accordingly, in some embodiments, the user can specify an exact dosing schedule that may vary from day-to-day. Further, some embodiments enable the patient to “pause” or temporarily turn the therapy off within a prescribed duty cycle. Moreover, some embodiments of the present disclosure enable duty cycle tracking to compare the electrical nerve stimulation actually delivered to the patient to the clinician prescribed therapeutic regimen.” [0008]
It would have been obvious to one of ordinary skill in the art before the effective filing date to include in the method and system of Choi et al. the ability to have a schedule as taught by Johnson since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Further motivation is provided by Johnson who teaches the benefits of using a prescribed therapy for patients with a schedule and this allows for exact dosing.
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 KENNETH BARTLEY whose telephone number is (571)272-5230. The examiner can normally be reached Mon-Fri: 7:30 - 4:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SHAHID MERCHANT can be reached at (571) 270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KENNETH BARTLEY/Primary Examiner, Art Unit 3684
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