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 .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 4-11, 14, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over McDonald(US 20190344080 A1) in view of Mehr(US 20110319961 A1) and further in view of Annoni(US 20180192943 A1).
Regarding claim 1, McDonald discloses a system for delivering neurostimulation to a patient using a stimulation device, the system comprising:
a personalization circuit including:
an assessment input configured to receive patient-specific information resulting from a patient survey, the patient-specific information including one or more patient dimensions of the neurostimulation(At 1422, the patient-specific evaluation information is analyzed with neurostimulation algorithm information. The neurostimulation algorithm information can include information representing therapeutic options available for delivery using the stimulation device. Examples of such neurostimulation algorithm information include stimulation programs and parameters used for each of the stimulation programs. The neurostimulation algorithm information can also include information such as computational models that relate the stimulation programs and parameters to possible conditions of the patient and allow for prediction of outcome of delivering the neurostimulation by simulations.[0132]); and
personalization processing circuitry configured to determine a personalized objective function using the one or more patient dimensions and to determine a personalized model having a model state personalized to the patient’s measured response to the neurostimulation(The system of claims 6, wherein the processing circuit of the patient assistance device is further configured to produce at least one recommendation for initial settings of the stimulation device including at least a type of the stimulation device, a stimulation program, and parameters used by the stimulation program, to optimize the settings of the stimulation device for the patient after the neurostimulation is delivered to the patient, and to maintain optimization of the settings of the stimulation device for the patient throughout the use of the stimulation device for the patient.[claim 7]), the determination of the personalized model including minimizing a difference between the patient's response to the neurostimulation predicted by computer simulation using the personalized model and the patient's measured response to the neurostimulation(At 1424, at least one recommendation regarding use of the stimulation device is presented to the patient using the patient assistance device. The recommendation can inform the patient with therapeutic options and/or instruct the patient on how to proceed based on the prediction made at 1423. The prediction and/or the one or more recommendation can also be transmitted to the users (e.g., through a network such as neurostimulation network 1070). Some recommendations, such as the initial settings of the stimulation device, may only be presented to designed user(s)[0134]. The one or more recommendations can include instructions for adjusting the settings of the stimulation device based on the received patient-specific customization information. Such adjustment can target on maintaining optimization of the settings of the stimulation device throughout use of the stimulation device[0137]).
a pattern optimization circuit including optimization processing circuitry configured to determine one or more optimal patterns of neurostimulation using the personalized objective function and the personalized model for programming the stimulation device to deliver the neurostimulation according to the one or more optimal patterns of neurostimulation(In various embodiments, user interface 110 can include a graphical user interface (GUI) that allows the user to set and/or adjust the values of the user-programmable parameters by creating and/or editing graphical representations of various waveforms. Such waveforms may include, for example, a waveform representing a pattern of neurostimulation pulses to be delivered to the patient as well as individual waveforms that are used as building blocks of the pattern of neurostimulation pulses, such as the waveform of each pulse in the pattern of neurostimulation pulses[0058]). However, McDonald fails to disclose “a calibration input configured to receive calibration information resulting from a calibration, the calibration information including the patient’s response to the neurostimulation measured during the calibration”.
However, Mehr teaches “The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a personalized patient controlled neurostimulation system that may (i) eliminate inadvertent stimulation, (ii) provide personalized neurostimulation, (iii) increase effectiveness of therapy by dynamic calibration of a neurostimulation signal and/or (iv) dynamically adapt the neurostimulation to a profile of the patient.[0004]. The manual input data received from the user may be used in a feedback loop of the neurostimulation. For example, manual data entered into the circuit 264 may be passed to the calibration unit 202. Concurrently, sensor data collected by the circuit 104 may be transferred to the circuit 136, transmitted to the circuit 266 and sent to the calibration unit 202. The calibration unit 202 may process the manual input data and the sensor data per the rules to generate customized data for stimulating the patient. [0069]. A rule engine within the calibration unit may compensate for any signal degradation received from the sensor array to ensure optimal neurostimulation signals on a case by case basis. Diagnostic and therapeutic data is generally collected by the implantable controller and transmitted to a remote server computer. Healthcare professionals may monitor the resulting diagnostic and therapeutic data to assist the patient in optimizing the therapy[0016]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration unit of the personalized neurostimulation of Mehr. Doing so would specify calibration of the data obtained by the system in order to produce the optimal neurostimulation for each specific patient.
Annoni teaches “ The fusion model may algorithmically combine the sensed physiological or functional signals. The system may calibrate the fusion model based on measurements from the plurality of physiological or functional signals and a reference pain quantification that corresponds to the multiple pain intensities[0008].
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration model of the patient-specific calibration of Annoni. Doing so would specify calibration would include patient response measurements during neurostimulation, in order to produce the optimal neurostimulation for each specific patient.
Regarding claim 4, McDonald in view of Mehr and Annoni teaches the system of claim 1, comprising an implantable stimulator as the stimulation device and an external system communicatively coupled to the implantable stimulator via telemetry, the external system including the personalization circuit and the pattern optimization circuit(FIG. 8 illustrates an embodiment of an external programming device 802 of an implantable neurostimulation system, such as system 600. External programming device 802 can represent an example of programming device 102. or 302, and may be implemented, for example, as CP 630 and/or RC 632. External programming device 802 includes an external telemetry circuit 852, an external storage device 818, a programming control circuit 816, and a user interface 810[0082]).
Regarding claim 5, McDonald in view of Mehr and Annoni teaches the system of claim 4, wherein the external system comprises an external programmer including the pattern optimization circuit and a remote device communicatively coupled to the external programmer via a telecommunication network and including the personalization circuit(External telemetry circuit 852 provides external programming device 802 with wireless communication with another device such as implantable stimulator 704 via wireless communication link 640, including transmitting the plurality of stimulation parameters to implantable stimulator 704 and receiving information including the patient data from implantable stimulator 704[0083])
Regarding claim 6, McDonald in view of Mehr and Annoni teaches the system of claim 4, wherein the external system comprises an external programmer including the personalization circuit and the pattern optimization circuit(Programming control circuit 816 can represent an example of programming control circuit 316 and generates the plurality of stimulation parameters, which is to be transmitted to implantable stimulator 704, based on a specified stimulation program (e.g., the pattern of neurostimulation pulses as represented by one or more stimulation waveforms and one or more stimulation fields, or at least certain aspects of the pattern). The stimulation program may be created and/or adjusted by the user using user interface 810 and stored in external storage device 818. [0086]. Fig. 8).
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Regarding claim 7, McDonald in view of Mehr and Annoni teaches the system of claim 4, but McDonald fails to disclose wherein the external system is configured to perform the patient assessment including conducting a patient survey to determine the one or more patient dimensions of the neurostimulation.
However, Mehr teaches “The circuit 140 may include a screen for displaying information to the user. The information may include, but is not limited to, the patient data collected from the sensors, coaching content received from the circuit 142, user adjustable parameters for customizing the neurostimulations, menus to receive user input data, instructions on how to use the circuits 140 and 102 and diagnostic results. The circuit 140 may also include multiple buttons, keys and/or switches configured for use by the patient. The buttons may be aligned with menus on the displays such that the patient may navigate through a menu structure, access data, enter rules parameters, make selections, response to questions (queries) and the like[0038]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the assessment of the personalized neurostimulation of Mehr. Doing so would specify questions the patient inputs answers to so the system can obtain personal data.
Regarding claim 8, McDonald in view of Mehr and Annoni teaches the system of claim 4, wherein the external system is configured to perform the calibration to determine the patient’s measured response to the neurostimulation by programming the implantable stimulator to deliver the neurostimulation to the patient and measuring one or more parameters representing the patient’s measured response to the neurostimulation(Examples of the one or more physiological signals include neural and other signals each indicative of a condition of the patient that is treated by the neurostimulation and/or a response of the patient to the delivery of the neurostimulation.[0079]). McDonald fails to explicitly state the calibration system.
However, Mehr teaches the “The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a personalized patient controlled neurostimulation system that may (i) eliminate inadvertent stimulation, (ii) provide personalized neurostimulation, (iii) increase effectiveness of therapy by dynamic calibration of a neurostimulation signal and/or (iv) dynamically adapt the neurostimulation to a profile of the patient[0004]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration unit of the personalized neurostimulation of Mehr. Doing so would specify calibration of the data obtained by the system in order to produce the optimal neurostimulation for each specific patient.
Regarding claim 9, McDonald in view of Mehr and Annoni teaches the system of claim 8, wherein the external system is configured to produce one or more response curves each being a measured parameter of the measured one or more parameters plotted as a function of a stimulation parameter used by the implantable stimulator to control the delivery of the neurostimulation* As used in this document, a “stimulation program” can include the pattern of neurostimulation pulses including the one or more stimulation fields, or at least various aspects or parameters of the pattern of neurostimulation pulses including the one or more stimulation fields. In various embodiments, user interface 310 includes a GUI that allows the user to define the pattern of neurostimulation pulses and perform other functions using graphical methods. In this document, “neurostimulation programming” can include the definition of the one or more stimulation waveforms, including the definition of one or more stimulation fields[0064]).
Regarding claim 10, McDonald discloses the a non-transitory computer-readable storage medium including instructions, which when executed by a system, cause the system to perform a method for delivering neurostimulation to a patient using a stimulation device, the method comprising:
receiving patient-specific information resulting from a patient survey, the patient-specific information including one or more patient dimensions of the neurostimulation(At 1422, the patient-specific evaluation information is analyzed with neurostimulation algorithm information. The neurostimulation algorithm information can include information representing therapeutic options available for delivery using the stimulation device. Examples of such neurostimulation algorithm information include stimulation programs and parameters used for each of the stimulation programs. The neurostimulation algorithm information can also include information such as computational models that relate the stimulation programs and parameters to possible conditions of the patient and allow for prediction of outcome of delivering the neurostimulation by simulations.[0132]);
determining a personalized objective function using the received one or more patient dimensions( FIG. 14 illustrates an embodiment of a method 1420 for evaluating the patient for neurostimulation. Method 1420 can be performed during step 1301 in method 1300. In one embodiment, the processing circuit of the patient assistance device operates in the evaluation mode to perform method 14[0130]);
determining a personalized model being a computational model having a model state personalized to the patient’s measured response to the neurostimulation, including minimizing a difference between the patient's response to the neurostimulation predicted by computer simulation using the personalized model and the patient's measured response to the neurostimulation(At 1424, at least one recommendation regarding use of the stimulation device is presented to the patient using the patient assistance device. The recommendation can inform the patient with therapeutic options and/or instruct the patient on how to proceed based on the prediction made at 1423. The prediction and/or the one or more recommendation can also be transmitted to the users (e.g., through a network such as neurostimulation network 1070). Some recommendations, such as the initial settings of the stimulation device, may only be presented to designed user(s)[0134]. The one or more recommendations can include instructions for adjusting the settings of the stimulation device based on the received patient-specific customization information. Such adjustment can target on maintaining optimization of the settings of the stimulation device throughout use of the stimulation device[0137]).
determining one or more optimal patterns of neurostimulation using the personalized objective function and the personalized model(The system of claims 6, wherein the processing circuit of the patient assistance device is further configured to produce at least one recommendation for initial settings of the stimulation device including at least a type of the stimulation device, a stimulation program, and parameters used by the stimulation program, to optimize the settings of the stimulation device for the patient after the neurostimulation is delivered to the patient, and to maintain optimization of the settings of the stimulation device for the patient throughout the use of the stimulation device for the patient.[claim 7]); and
generating information for programming the stimulation device to deliver the neurostimulation according to the one or more optimal patterns of neurostimulation(At 1422, the patient-specific evaluation information is analyzed with neurostimulation algorithm information. The neurostimulation algorithm information can include information representing therapeutic options available for delivery using the stimulation device. Examples of such neurostimulation algorithm information include stimulation programs and parameters used for each of the stimulation programs. The neurostimulation algorithm information can also include information such as computational models that relate the stimulation programs and parameters to possible conditions of the patient and allow for prediction of outcome of delivering the neurostimulation by simulations.[0132]. The system of claims 6, wherein the processing circuit of the patient assistance device is further configured to produce at least one recommendation for initial settings of the stimulation device including at least a type of the stimulation device, a stimulation program, and parameters used by the stimulation program, to optimize the settings of the stimulation device for the patient after the neurostimulation is delivered to the patient, and to maintain optimization of the settings of the stimulation device for the patient throughout the use of the stimulation device for the patient.[claim 7]. An example (e.g., “Example 26”) of a non-transitory machine readable medium including instructions, which when operated on by a machine, cause the machine to perform a method, is also provided.[0030]). McDonald fails to disclose “receiving calibration information resulting from a calibration, the calibration information including the patient’s response to the neurostimulation measured during the calibration”.
Mehr teaches “The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a personalized patient controlled neurostimulation system that may (i) eliminate inadvertent stimulation, (ii) provide personalized neurostimulation, (iii) increase effectiveness of therapy by dynamic calibration of a neurostimulation signal and/or (iv) dynamically adapt the neurostimulation to a profile of the patient.[0004]. The manual input data received from the user may be used in a feedback loop of the neurostimulation. For example, manual data entered into the circuit 264 may be passed to the calibration unit 202. Concurrently, sensor data collected by the circuit 104 may be transferred to the circuit 136, transmitted to the circuit 266 and sent to the calibration unit 202. The calibration unit 202 may process the manual input data and the sensor data per the rules to generate customized data for stimulating the patient. [0069]. A rule engine within the calibration unit may compensate for any signal degradation received from the sensor array to ensure optimal neurostimulation signals on a case by case basis. Diagnostic and therapeutic data is generally collected by the implantable controller and transmitted to a remote server computer. Healthcare professionals may monitor the resulting diagnostic and therapeutic data to assist the patient in optimizing the therapy[0016]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration unit of the personalized neurostimulation of Mehr. Doing so would specify calibration of the data obtained by the system in order to produce the optimal neurostimulation for each specific patient.
Annoni teaches “ The fusion model may algorithmically combine the sensed physiological or functional signals. The system may calibrate the fusion model based on measurements from the plurality of physiological or functional signals and a reference pain quantification that corresponds to the multiple pain intensities[0008].
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration model of the patient-specific calibration of Annoni. Doing so would specify calibration would include patient response measurements during neurostimulation, in order to produce the optimal neurostimulation for each specific patient.
Regarding claim 11, McDonald discloses a method for delivering neurostimulation to a patient, the method comprising:
receiving patient-specific information resulting from a patient survey, the patient-specific information including one or more patient dimensions of the neurostimulation(The patient-specific evaluation information includes portions of the patient-specific information that are received by the patient assistance device and analyzed as part of performing method 1420 (e.g., during the evaluation mode). The patient-specific evaluation information can include input from the patient. For example, a questionnaire can be presented to the patient, and answers can be received from the patient, using a user interface of the patient assistance device[0131]);
determining a personalized objective function using the received one or more patient dimensions(At 1422, the patient-specific evaluation information is analyzed with neurostimulation algorithm information. The neurostimulation algorithm information can include information representing therapeutic options available for delivery using the stimulation device. Examples of such neurostimulation algorithm information include stimulation programs and parameters used for each of the stimulation programs. The neurostimulation algorithm information can also include information such as computational models that relate the stimulation programs and parameters to possible conditions of the patient and allow for prediction of outcome of delivering the neurostimulation by simulations[0132]);
determining a personalized model being a computational model having a model state personalized to the patient’s measured response to the neurostimulation, including minimizing a difference between the patient's response to the neurostimulation predicted by computer simulation using the personalized model and the patient's measured response to the neurostimulation(The neurostimulation algorithm information can also include information such as computational models that relate the stimulation programs and parameters to possible conditions of the patient and allow for prediction of outcome of delivering the neurostimulation by simulations[0132]. At 1424, at least one recommendation regarding use of the stimulation device is presented to the patient using the patient assistance device. The recommendation can inform the patient with therapeutic options and/or instruct the patient on how to proceed based on the prediction made at 1423. The prediction and/or the one or more recommendation can also be transmitted to the users (e.g., through a network such as neurostimulation network 1070). Some recommendations, such as the initial settings of the stimulation device, may only be presented to designed user(s)[0134]. The one or more recommendations can include instructions for adjusting the settings of the stimulation device based on the received patient-specific customization information. Such adjustment can target on maintaining optimization of the settings of the stimulation device throughout use of the stimulation device[0137]);
determining one or more optimal patterns of neurostimulation using the personalized objective function and the personalized model(The system of claims 6, wherein the processing circuit of the patient assistance device is further configured to produce at least one recommendation for initial settings of the stimulation device including at least a type of the stimulation device, a stimulation program, and parameters used by the stimulation program, to optimize the settings of the stimulation device for the patient after the neurostimulation is delivered to the patient, and to maintain optimization of the settings of the stimulation device for the patient throughout the use of the stimulation device for the patient.[claim 7]); and
programming a stimulation device to deliver the neurostimulation according to the one or more optimal patterns of neurostimulation(In various embodiments, user interface 110 can include a graphical user interface (GUI) that allows the user to set and/or adjust the values of the user-programmable parameters by creating and/or editing graphical representations of various waveforms. Such waveforms may include, for example, a waveform representing a pattern of neurostimulation pulses to be delivered to the patient as well as individual waveforms that are used as building blocks of the pattern of neurostimulation pulses, such as the waveform of each pulse in the pattern of neurostimulation pulses[0058]). However, McDonald fails to disclose “a calibration input configured to receive calibration information resulting from a calibration, the calibration information including the patient’s response to the neurostimulation measured during the calibration”.
However, Mehr teaches “The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a personalized patient controlled neurostimulation system that may (i) eliminate inadvertent stimulation, (ii) provide personalized neurostimulation, (iii) increase effectiveness of therapy by dynamic calibration of a neurostimulation signal and/or (iv) dynamically adapt the neurostimulation to a profile of the patient.[0004]. The manual input data received from the user may be used in a feedback loop of the neurostimulation. For example, manual data entered into the circuit 264 may be passed to the calibration unit 202. Concurrently, sensor data collected by the circuit 104 may be transferred to the circuit 136, transmitted to the circuit 266 and sent to the calibration unit 202. The calibration unit 202 may process the manual input data and the sensor data per the rules to generate customized data for stimulating the patient. [0069]. A rule engine within the calibration unit may compensate for any signal degradation received from the sensor array to ensure optimal neurostimulation signals on a case by case basis. Diagnostic and therapeutic data is generally collected by the implantable controller and transmitted to a remote server computer. Healthcare professionals may monitor the resulting diagnostic and therapeutic data to assist the patient in optimizing the therapy[0016]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration unit of the personalized neurostimulation of Mehr. Doing so would specify calibration of the data obtained by the system in order to produce the optimal neurostimulation for each specific patient.
Annoni teaches “ The fusion model may algorithmically combine the sensed physiological or functional signals. The system may calibrate the fusion model based on measurements from the plurality of physiological or functional signals and a reference pain quantification that corresponds to the multiple pain intensities[0008].
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration model of the patient-specific calibration of Annoni. Doing so would specify calibration would include patient response measurements during neurostimulation, in order to produce the optimal neurostimulation for each specific patient.
Regarding claim 14, McDonald in view of Mehr and Annoni teaches the method of claim 11, wherein determining the one or more optimal patterns of neurostimulation comprises selecting the one or more optimal patterns of neurostimulation from predefined patterns of neurostimulation(The one or more stimulation waveforms may each be associated with one or more stimulation fields and represent a pattern of neurostimulation pulses to be delivered to the one or more stimulation field during the neurostimulation therapy session. In various embodiments, each of the one or more stimulation waveforms can be selected for modification by the user and/or for use in programming a stimulation device such as implantable stimulator 704 to deliver a therapy[0085]).
Regarding claim 16, McDonald in view of Mehr and Annoni teaches the method of claim 11, but McDonald fails to disclose further comprising conducting a patient survey to determine the one or more patient dimensions of the neurostimulation.
However, Mehr teaches “The circuit 140 may include a screen for displaying information to the user. The information may include, but is not limited to, the patient data collected from the sensors, coaching content received from the circuit 142, user adjustable parameters for customizing the neurostimulations, menus to receive user input data, instructions on how to use the circuits 140 and 102 and diagnostic results. The circuit 140 may also include multiple buttons, keys and/or switches configured for use by the patient. The buttons may be aligned with menus on the displays such that the patient may navigate through a menu structure, access data, enter rules parameters, make selections, response to questions (queries) and the like[0038]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the assessment of the personalized neurostimulation of Mehr. Doing so would specify questions the patient inputs answers to so the system can obtain personal data.
Regarding claim 17, McDonald in view of Mehr and Annoni teaches the method of claim 11, further comprising determining the patient’s measured response to the neurostimulation by programming an implantable stimulator to deliver the neurostimulation to the patient and measuring one or more parameters representing the patient’s response(Examples of the one or more physiological signals include neural and other signals each indicative of a condition of the patient that is treated by the neurostimulation and/or a response of the patient to the delivery of the neurostimulation.[0079]). McDonald fails to explicitly state the calibration system.
However, Mehr teaches the “The objects, features and advantages of the present invention include providing a method and/or apparatus for implementing a personalized patient controlled neurostimulation system that may (i) eliminate inadvertent stimulation, (ii) provide personalized neurostimulation, (iii) increase effectiveness of therapy by dynamic calibration of a neurostimulation signal and/or (iv) dynamically adapt the neurostimulation to a profile of the patient[0004]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the calibration unit of the personalized neurostimulation of Mehr. Doing so would specify calibration of the data obtained by the system in order to produce the optimal neurostimulation for each specific patient.
Regarding claim 18, McDonald in view of Mehr and Annoni teaches the method of claim 17, wherein determining the patient’s measured response to the neurostimulation comprises producing one or more response curves each being a measured parameter of the measured one or more parameters plotted as a function of a stimulation parameter used by the implantable stimulator to control the delivery of the neurostimulation(As used in this document, a “stimulation program” can include the pattern of neurostimulation pulses including the one or more stimulation fields, or at least various aspects or parameters of the pattern of neurostimulation pulses including the one or more stimulation fields. In various embodiments, user interface 310 includes a GUI that allows the user to define the pattern of neurostimulation pulses and perform other functions using graphical methods. In this document, “neurostimulation programming” can include the definition of the one or more stimulation waveforms, including the definition of one or more stimulation fields[0064]).
Regarding claim 19, McDonald in view of Mehr teaches the method of claim 11, further comprising: delivering the neurostimulation to the patient according to the one or more optimal patterns of neurostimulation for a prolonged time period; receiving updated one or more patient dimensions during the prolong period according to a schedule; adjusting the personalized objective function using the updated one or more patient dimensions; adjusting the one or more optimal patterns of neurostimulation using the adjusted personalized objective function; and programming the stimulation device to deliver the neurostimulation according to the adjusted one or more optimal patterns of neurostimulation(At 1532, the patient-specific customization information is analyzed with the neurostimulation algorithm information. This analysis can be similar to the analysis at step 1422. At 1533, one or more recommendations are produced based on one or more outcomes of the analysis. The one or more recommendations can include instructions for adjusting the settings of the stimulation device based on the received patient-specific customization information. Such adjustment can target on maintaining optimization of the settings of the stimulation device throughout use of the stimulation device. Examples of the one or more recommendations include instructions for switching between the stimulation programs, instructions for changing parameters used for each of the stimulation programs, instructions for changing schedule of delivering the neurostimulation (e.g., stating time for each stimulation program, such as for daytime/nighttime and/or weekday/weekend deliveries), instructions for creating an evaluation strategy/algorithm for optimizing stimulation device settings for the patient by testing the one or more stimulation programs and the parameters by delivering the stimulation using the stimulation device, and instructions for changing the settings of the stimulation device in response to changes in conditions of the patient and/or the stimulation device over time to increase longevity of the stimulation device.[0137]).
Regarding claim 20, McDonald in view of Mehr and Annoni teaches the method of claim 19, further comprising: receiving updated patient’s measured response to the neurostimulation; adjusting the personalized model to the updated patient’s response to the neurostimulation; adjusting the one or more optimal patterns of neurostimulation using the adjusted personalized model; and programming the stimulation device to deliver the neurostimulation according to the adjusted one or more optimal patterns of neurostimulation(In various embodiments, external programming device 802 can have operation modes including a composition mode and a real-time programming mode. Under the composition mode (also known as the pulse pattern composition mode), user interface 810 is activated, while programming control circuit 816 is inactivated. Programming control circuit 816 does not dynamically updates values of the plurality of stimulation parameters in response to any change in the one or more stimulation waveforms. Under the real-time programming mode, both user interface 810 and programming control circuit 816 are activated. Programming control circuit 816 dynamically updates values of the plurality of stimulation parameters in response to changes in the set of one or more stimulation waveforms, and transmits the plurality of stimulation parameters with the updated values to implantable stimulator 704[0089]).
Regarding claim 21, McDonald in view of Mehr and Annoni teaches the system of claim 1, wherein the personalization processing circuitry is configured to determine the personalized model by selecting a model state from stored predefined model states(The recommendation for the initial settings of the stimulation device can include, for example, selection of a type or model of the stimulation device, selection of one or more stimulation programs from the neurostimulation algorithm information, values of parameters for each selected stimulation program[0133]).
Regarding claim 22, McDonald in view of Mehr and Annoni teaches the system of claim 1, wherein the personalization processing circuitry is configured to determine the personalized model by adjusting parameters of a stored model(If the patient assistance device is capable of communicating with the stimulation device directly, programming instructions can be transmitted to the stimulation device for adjusting its settings of the stimulation device based on the response received from the patient[0138]).
Claim(s) 2, 12-13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over McDonald in view of Mehr, Annoni, and further in view of Grill(US 10213605 B2).
Regarding claim 2, McDonald in view of Mehr and Annoni teaches the system of claim 1, but fails to disclose wherein the personalization processing circuitry is configured to determine a personalized cost function as the personalized objective function, the personalized cost function being a quantitative measure of a condition of the patient expressed as a function of the one or more patient dimensions.
However, Grill teaches the “At any time afterwards, a qualified user may override the system through the user interface and toggle the optimization algorithm on and off, alter the parameters of the optimization cost function within reasonable limits, and/or change the temporal pattern(s) being delivered by the SCS device 650 using the remote control device 600 and associated graphical interface(Detailed Descriptions, paragraph 37)”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the cost function of the stimulation of Grill. Doing so would include a cost function in the system to further personalize the neurostimulation system.
Regarding claim 12, McDonald in view of Mehr and Annoni teaches the method of claim 11, but fails to disclose wherein determining the personalized objective function comprises determining a personalized cost function being a quantitative measure of a condition of the patient expressed as a function of the one or more patient dimensions.
However, Grill teaches the “At any time afterwards, a qualified user may override the system through the user interface and toggle the optimization algorithm on and off, alter the parameters of the optimization cost function within reasonable limits, and/or change the temporal pattern(s) being delivered by the SCS device 650 using the remote control device 600 and associated graphical interface(Detailed Descriptions, paragraph 37)”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the cost function of the stimulation of Grill. Doing so would include a cost function in the system to further personalize the neurostimulation system.
Regarding claim 13, McDonald in view of Mehr, Annoni, and Grill teaches the method of claim 12, but McDonald fails to further comprising optimizing the personalized model by matching the patient’s response to the neurostimulation as predicted by simulation using the personalized model to the received patient’s response to the neurostimulation.
However, Mehr teaches “A method for personalized patient controlled neurostimulation, comprising the steps of: (A) obtaining (i) physical data of an individual and (ii) one or more manual inputs from said individual; (B) generating compare data in a processor circuit by comparing said physical data with profile data of said individual; (C) generating customized data by processing said one or more manual inputs and said compared data using a set of rules, wherein said rules are (i) reprogrammable and (ii) govern generation of a nerve stimulation signal having predetermined control characteristics applicable to said individual; and (D) controlling said neurostimulation of said individual with said nerve stimulation signal based on said customized data[claim 1]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the predicted comparisons of the personalized neurostimulation of Mehr. Doing so would specify comparing the predetermined and measured data in the system to generate personalized stimulation.
Regarding claim 15, McDonald in view of Mehr and Annoni teaches the method of claim 11, but fails to explicitly state wherein determining the personalized model comprises determining parameters of a predefined model. However, Grill teaches the “Optimization may be conducted using a computational model prior to treatment of a human subject and further optimization may occur using feedback from the subject(abstract)”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the neurostimulation system of McDonald with the models of the stimulation of Grill. Doing so would specify optimizing the initial model of stimulation with the feedback from the user.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 2, and 4-22 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. Applicant argues prior art fails to disclose the amended claim limitations, specifically the limitation that the “the calibration information including the patient's response to the neurostimulation measured during the calibration”. However, new art Annoni teaches calibration occurring during “neurostimulation and patient response being taken into account for calibration[0096]. Regarding the amendments “the determination of the personalized model including minimizing a difference between the patient's response to the neurostimulation predicted by computer simulation using the personalized model and the patient's measured response to the neurostimulation”. McDonald does in fact teach this limitation as it is an obvious type limitation. McDonald teaches predicting the outcome of neurostimulation based on a patient condition model, creating a recommendation based on said prediction, and adjusting the patient stimulation model based on the recommendation to optimize therapy[0133]. If therapy is optimized, it is obvious the therapy is being adjusted to match the successful prediction outcome, therefore the difference between the response and the prediction would be minimized. McDonald, Annoni, and Mehr can be naturally combined to disclose all the claimed material of the independent claims and combined with all prior art to disclose all claims. Therefore, the 103 rejections for all claims stand.
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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/MARIA CATHERINE ANTHONY/Examiner, Art Unit 3796
/TAMMIE K MARLEN/Primary Examiner, Art Unit 3796
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