DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see “Applicant Arguments/Remarks”, filed 06/17/2026, with respect to the rejections under U.S.C. 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn in view of amendments to claims 1 and 14. However, upon further consideration, a new ground(s) of rejection is made in view of Gillespie and Reiner.
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 1-2, 4, 7-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over by U.S. Patent Publication 20170080234 awarded to Gillespie et al, and further in view of U.S. Patent Publication 20110041077 awarded to Reiner.
Regarding Claims 1 and 14, Gillespie teaches a system and method for providing electrostimulation to a patient (abstract), comprising: an electrostimulator configured to provide a neuromodulation therapy to a patient (Fig. 2, modulation device 212, Para. 0060); and a programmer device operable by a user to program the electrostimulator (Fig. 2, programming device 213, Para. 0060), the programmer device including: a user interface (GUI 214, Fig. 2, Para. 0060, “In various embodiments, the programming device 213 includes a graphical user interface (GUI) 214 that allows the user to set and/or adjust values of the user-programmable modulation parameters”); and a controller circuit configured to: collect user commands and contextual information during a programming session including a sequence of programming instructions from the user via the user interface (Para. 0060, “The modulation device 212 is configured to be electrically connected to electrodes 211 and deliver neuromodulation energy, such as in the form of electrical pulses, to the one or more neural targets though electrodes 211. The delivery of the neuromodulation is controlled by using a plurality of modulation parameters, such as modulation parameters specifying the electrical pulses and a selection of electrodes through which each of the electrical pulses is delivered. In various embodiments, at least some parameters of the plurality of modulation parameters are programmable by a user, such as a physician or other caregiver”); determine a programming quality indicator using the collected user commands and contextual information and based at least in part on the programming quality indicator (Para. 0088, “In addition, a user feedback subsystem 706 may be used to query a user (e.g., a patient) and obtain feedback regarding current, previous, or future programming, pain or quality of life scores, or other information”), generate an individualized programming workflow to guide the user to test and program a therapy setting to the electrostimulator (Para. 0088, “FIG. 7 illustrates, by way of example, an embodiment of data and control flow in a system that utilizes machine learning to optimize neurostimulation patterns. One or more inputs 700 may be fed into a search method 702, which may then provide one or more outputs 704. The inputs 700 may be generally grouped as patient inputs 700-1, user inputs 700-2, and automatic inputs 700-3, Outputs 704 may include programming parameters or scheduling, reports, and other actions. In addition, a user feedback subsystem 706 may be used to query a user (e.g., a patient) and obtain feedback regarding current, previous, or future programming, pain or quality of life scores, or other information”); wherein the electrostimulator is configured to provide neuromodulation therapy in accordance with the user programmed therapy setting (Para. 0094, “Some or all of the outputs 704 may be fed to the user feedback subsystem 706 for presentation to one or more users. For example, a weekly report of the programming used may be provided to a user (e.g., a patient). The output 704 may be used to drive further processing on the user feedback subsystem 706 in order to obtain patient inputs 700-1 or user inputs 700-2, which may be fed back into the search method 702 and used to determine additional outputs 704”). Gillespie does not teach the programming quality indicator representing a measure of a level of work efficiency of the user’s programming as reflected in a sequence of programming instructions.
However, in the art of medical programming (Para. 0108, Reiner teaches obtaining feedback from users and adjusting/personalizing the programming/usage of a device based on workflow monitoring (Para. 0262, “Radiologists C and D, on the other hand, have been identified by the program 110 as having low extraversion scores and would therefore react more favorably to “solo” educational programs. Radiologist C who has a great deal of computer experience and high functionality quotient, prefers to have quarterly educational CD's sent to him/her, on new technology upgrades and “short cuts” introduced. Radiologist D has minimal computer experience and a low functionality quotient. His/her educational programs are also designed by the program 110 to be “solo”, but take the form of an electronic wizard that is provided whenever a time-consuming manual task has been performed with an automated alternative. The auditing tool of the program 110 first identifies the inefficient workflow, launches the automated educational program 110 (in the form of the electronic wizard), which in turn provides a self-instructional program 110 that can be engaged or rejected by the end-user. The auditing tool of the program 110 continually monitors workflow and can provide regular feedback to the end-user as to how the educational program has produced objective changes in workflow. This feedback loop can in turn be used by the program 110 to further modify the educational program, based on combined personality and workflow of each individual user”) for the purpose of improving a user’s efficiency and performance in using the device (Para. 0129).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gillespie by Reiner, i.e. by using the workflow analysis of Reiner in the programming and programming quality detection system of Gillespie, for the predictable purpose of providing the same benefits listed in Para. 0129 of Reiner in the system of Gillespie.
Regarding Claims 2 and 15, Gillespie modified by Reiner makes obvious the system of Claim 1 and 14. Gillespie further teaches wherein the sequence of programming instructions from the user during the programming session includes one or more of a timing of a programmable parameter being selected, a frequency of a programmable parameter being selected over a specific time period, or an order of selecting multiple programmable parameters, wherein the individualized programming workflow includes selection or deselection of a programmable parameter, or an order of selecting multiple programmable parameters (Para. 0097, “the patient is provided user interface element 804, which represents the third programming set P3, to insert among the ordered UI elements 800. The patient may move the UI element 804 to place it in order of perceived performance (e.g., preference). In this example, the patient opts to place UI element 804 in between UI elements 800-1 and 800-2, indicating that the programming P3 was better than P2, but worse than P1. In FIG. 8B, the subsequent state 806, after dragging and dropping the UI element 804 to the selected position, the other UI elements 800 are rearranged around the newly inserted UI element 804. If a programming set was in the last position (e.g., 800-5), then it is bumped from the list and the programming set in the fourth position (e.g., 800-4) is demoted to the last position. In addition, the user may adjust the order of the programming sets by dragging and dropping one UI element from one position to another, in which case, the other UI elements are rearranged in the new order”).
Regarding Claim 4, Gillespie modified by Reiner makes obvious system of Claim 1. Gillespie further teaches wherein the user commands and contextual information collected during the programming session further includes time elapsed during an entirety or a portion of the programming session, including time spent when the programmer device is in active communication with the electrostimulator during the programming session (Para. 0093, “Other automatic inputs 700-3 may include performance data, such as the duration of a programming session, the number of time a parameter set was tested and the related patient scores/feedback, etc”).
Regarding Claim 7, Gillespie modified by Reiner makes obvious the system of Claim 1. Gillespie further teaches wherein the user commands and contextual information collected during the programming session further includes patient responses indicative of a therapeutic effect or a side effect of the neuromodulation therapy (Para. 0066, “The remote control device may also provide a mechanism for the patient to provide feedback on the operation of the implantable neuromodulation system. Feedback may be metrics reflecting perceived pain, effectiveness of therapies, or other aspects of patient comfort or condition”).
Regarding Claim 8, Gillespie modified by Reiner makes obvious the system of Claim 1. Gillespie further teaches wherein the controller circuit is configured to determine the programming quality indicator based on a comparison of the sequence of programming instructions to a reference sequence of programming instructions (Para. 0105, “FIG. 16 illustrates, by way of example, an embodiment of a gradient descent method 1600. At block 1602, an initial value of the parameter(s) P is taken. The outcome of the parameter(s) P is evaluated (block 1604). This establishes a starting point for the rest of the evaluations. At block 1606, a descent direct (+ or −) is determined based on the results from adjacent values of P. For example, a value higher than the initial value of P is evaluated and a value lower than the initial value of P is evaluated. Based on which value shows a better result, the descent method 1600 is set to an increasing direction or a decreasing direction. At block 1608, a step size ΔP is selected. The ΔP may be a value based on the initial value of P. For example, if the initial value of P is 200, the ΔP step size may be 50% of the current value of such that the ΔP=100”).
Regarding Claims 9 and 18, Gillespie modified by Reiner makes obvious the inventions of Claims 1 and 14 above. Gillespie further teaches wherein the programming quality indicator includes a programming quality score computed using a weighted combination of various sources of the user commands and contextual information collected during the programming session (Para. 0091, “The search objective may tune the search method 702 to work toward a program that achieves a desired outcome. One or more objectives may be selected. When more than one objective is selective, the combination of objectives may be weighted or ranked”).
Regarding Claim 10, Gillespie modified by Reiner makes obvious the system of Claim 1. Gillespie further teaches wherein the controller circuit is configured to determine the programming quality indicator by applying a trained machine learning model to the user commands and contextual information collected during the programming session (Para. 0110, “It is understood that other methods may be used to determine or classify sensitive/insensitive parameter sets, such as machine learning, neural networks, or guided selection. With guided selection, a user may be presented with various stimulation parameter sets and may drop the insensitive parameters, focusing on the sensitive parameter adjustment. Users may have the option to include insensitive parameters during later stimulation testing. Using sensitivity analysis, a system may automatically choose dimensions or recommend default stimulation parameters”).
Regarding Claims 11 and 19, Gillespie modified by Reiner makes obvious the inventions of Claims 1 and 14. Gillespie further teaches wherein the controller circuit is configured to present on the user interface the individualized programming workflow, including to prompt the user to select or deselect one or more programmable parameters, or to select multiple programmable parameters in a specific order (Para. 0097, “The number of user interface elements in FIG. 8A is five, but it is understood that other numbers of user interface elements may be used, such as, but not limited to ten, twenty, or fifty. In the first instance 802, the UI elements 800 include P1 and P2, which correspond to the first and second programming sets that the patient experienced. The patient is provided user interface element 804, which represents the third programming set P3, to insert among the ordered UI elements 800. The patient may move the UI element 804 to place it in order of perceived performance (e.g., preference)”).
Regarding Claim 12, Gillespie modified by Reiner makes obvious the system of Claim 11. Gillespie further teaches wherein the programmable parameters include at least one of a signal analysis parameter (Para. 0109), or a neuromodulation therapy parameter (Para. 0125).
Regarding Claims 13 and 20, Gillespie modified by Reiner makes obvious the inventions of Claims 1 and 14. Gillespie further teaches wherein the programmer device includes a communication circuit to communicate with a cloud computing system, and to use one or more cloud services provided by the cloud computing system to perform one or more operations including collecting the user commands and contextual information during the programming session, determining the programming quality indicator, or generating the individualized programming workflow (Para. 0087, “The algorithm may reside on the CP, the IPG, the ETS, the RC or other external device used by the patient, or in the cloud or remote servers connected to patient external via Wi-Fi, Bluetooth, cellular data, or other wired/wireless scheme. There may be a GUI on the CP, remote control, or other external device, that enables selection of algorithm as well as manual input. Training of the algorithm may take place in the clinic or in daily life, and may be set to be execute continually or only at certain times. Optimization data may be stored in the cloud so that optimized patterns and history can be transferred when the patient moves from trial to permanent implant and also if the IPG is replaced”).
Regarding Claim 16, Gillespie modified by Reiner makes obvious the system of Claim 14. Gillespie further teaches wherein the user commands and contextual information collected during the programming session includes at least one of: time elapsed during an entirety or a portion of the programming session, including time spent when the programmer device is in active communication with the electrostimulator during the programming session (Para. 0093, “Other automatic inputs 700-3 may include performance data, such as the duration of a programming session, the number of time a parameter set was tested and the related patient scores/feedback, etc.”).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Gillespie et al in view of Reiner, as applied to the claims above, and further in view of U.S. Patent Publication 20110106213 awarded to Davis et al.
Regarding Claim 3, Gillespie modified by Reiner makes obvious the system of Claim 1. Gillespie does not teach wherein the controller circuit is configured to receive image or video data from an imaging system during the programming session, and to extract information about the sequence of programming instruction from the received image or video data (Para. 0063, “The information stored in the memory 52 may be an image captured and downloaded into the implantable stimulator 34 by a programmer, such as clinician programmer 20 by wireless telemetry. As an example, the image may be obtained during an in-clinic programming session, and may show, for example, lead configuration and placement within a therapy region targeted by one or more leads implanted in the therapy region. Information stored in memory 52 may be retrieved by the programmer to effectively deliver therapy in subsequent sessions”).
However, in the art of neurostimulation (abstract), Davis teaches wherein the controller circuit is configured to receive image or video data from an imaging system during the programming session, and to extract information about the sequence of programming instruction from the received image or video data to improve the placement of leads for further treatments (Para. 0063, “The information stored in the memory 52 may be an image captured and downloaded into the implantable stimulator 34 by a programmer, such as clinician programmer 20 by wireless telemetry. As an example, the image may be obtained during an in-clinic programming session, and may show, for example, lead configuration and placement within a therapy region targeted by one or more leads implanted in the therapy region. Information stored in memory 52 may be retrieved by the programmer to effectively deliver therapy in subsequent sessions”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gillespie by Davis, i.e. by using the imaging system of Davis above in the system of Gillespie, for the predictable purpose of allowing the adjustment of the lead placements to improve further treatment.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Gillespie et al in view of Reiner, as applied to the claim 1 above, and further in view of U.S. Patent Publication 20240139527 awarded to Taff et al, hereinafter Taff.
Regarding Claim 5, Gillespie modified by Reiner makes obvious the system of Claim 1, wherein Gillespie further teaches the need to minimize power consumption of the device (Para. 0125). Gillespie does not teach wherein the user commands and contextual information collected during the programming session further includes wherein the user commands and contextual information collected during the programming session further includes an estimate of power consumption during an entirety or a specific portion of the programming session, including an estimate of power consumption when the programmer device is in active communication with the electrostimulator during the programming session.
However, in the art of stimulation devices (abstract), Taff teaches wherein the user commands and contextual information collected during the programming session further includes wherein the user commands and contextual information collected during the programming session further includes an estimate of power consumption during an entirety or a specific portion of the programming session, including an estimate of power consumption when the programmer device is in active communication with the electrostimulator during the programming session to maintain battery health of the apparatus (Para. 0013, “A remote monitoring device that utilizes RF telemetry for communication thus has the potential to prematurely deplete the battery of an implantable device. Described below are power management schemes that may be implemented in the patient management system for optimizing, limiting, and/or monitoring RF telemetry usage by the implantable device to avoid premature battery depletion and/or raise an alert if excessive battery depletion is beginning to occur”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gillespie by Taff, i.e. by using the power monitoring system of Taff in the system of Gillespie, for the predictable purpose of improving the battery management of Gillespie in the same manner as in Taff.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable Gillespie et al in view of Reiner and Taff, as applied to the claim 5 above, and further view of U.S. Patent Publication 20070150028 awarded to Parkinson et al, hereinafter Parkinson.
Regarding Claim 6, Gillespie modified by Reiner and Taff makes obvious the system of Claim 5. Gillespie further teaches the need to minimize power consumption of the device (Para. 0125). Gillespie does not teach wherein the individualized programming workflow includes an ordered selection of multiple programmable parameters based on their respective dependencies on an active communication during the programming session, such that a first group of programmable parameters that do not require active communication during the programming session are selected prior to a second group of programmable parameters that require active communication during the programming session.
However, in the art of stimulation therapy (abstract), Parkinson teaches wherein the individualized programming workflow includes an ordered selection of multiple programmable parameters based on their respective dependencies on an active communication during the programming session, such that a first group of programmable parameters that do not require active communication during the programming session are selected prior to a second group of programmable parameters that require active communication during the programming session (Para. 0029, “In the following, the processing state is also called the ‘busy state’. When the IMD's communication support is not in the ‘busy state’ but engaged in a communication link with the external device it simply resides in an ‘active state’ (where the transceiver is ON and the IMD is ready for further interaction with the external device). In the active state, the processor is not ‘busy’ and is capable of receiving requests from an external device that may be subsequently handled. Conditions where the processor may change from the ‘active state’ (i.e., an initial standby state) to the ‘processing state’ may be predefined and, for example, stored in a data memory of the IMD or the handling of any specific request from the external device and the emergent, resulting durations needed for such handling may simply instate such transitions. After finishing the respective task that has held the IMD in a ‘busy state” the processor switches back to the ‘active state’”) for the purpose of improving battery longevity and allowing smaller batteries/smaller device sizes (Para. 0005-0006).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gillespie by Parkinson, i.e. by using the ordering system of Parkinson above in the system of Gillespie, for the predictable purpose of improving the battery management of Gillespie in the same manner as in Parkinson.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Gillespie et al in view of Reiner, as applied to the claims 14 and 16 above, and further in view of U.S. Patent Publication 20070150028 awarded to Parkinson et al, hereinafter Parkinson.
Regarding Claim 17, Gillespie modified by Reiner makes obvious the method of Claim 16, wherein Gillespie teaches the need to minimize power consumption of the device (Para. 0125). Gillespie does not teach wherein the individualized programming workflow includes an ordered selection of multiple programmable parameters based on their respective dependencies on an active communication during the programming session, such that a first group of programmable parameters that do not require active communication during the programming session are selected prior to a second group of programmable parameters that require active communication during the programming session.
However, in the art of stimulation therapy (abstract), Parkinson teaches wherein the individualized programming workflow includes an ordered selection of multiple programmable parameters based on their respective dependencies on an active communication during the programming session, such that a first group of programmable parameters that do not require active communication during the programming session are selected prior to a second group of programmable parameters that require active communication during the programming session (Para. 0029, “In the following, the processing state is also called the ‘busy state’. When the IMD's communication support is not in the ‘busy state’ but engaged in a communication link with the external device it simply resides in an ‘active state’ (where the transceiver is ON and the IMD is ready for further interaction with the external device). In the active state, the processor is not ‘busy’ and is capable of receiving requests from an external device that may be subsequently handled. Conditions where the processor may change from the ‘active state’ (i.e., an initial standby state) to the ‘processing state’ may be predefined and, for example, stored in a data memory of the IMD or the handling of any specific request from the external device and the emergent, resulting durations needed for such handling may simply instate such transitions. After finishing the respective task that has held the IMD in a ‘busy state” the processor switches back to the ‘active state’”) for the purpose of improving battery longevity and allowing smaller batteries/smaller device sizes (Para. 0005-0006).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gillespie by Parkinson, i.e. by using the ordering system of Parkinson above in the system of Gillespie, for the predictable purpose of improving the battery management of Gillespie in the same manner as in Parkinson.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JLM/
Examiner, Art Unit 3792
/UNSU JUNG/Supervisory Patent Examiner, Art Unit 3792
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