OPTIMAL DEEP BRAIN STIMULATION THERAPY WITH Q LEARNING
First Claim
1. A closed loop Deep Brain Stimulation (DBS) system comprising:
- a physiological sensor, said physiological sensor comprising at least one of a brain activity sensor and a mechanical body motion sensor;
an adaptive control system in communication with said physiological sensor; and
an implantable pulse generator (IPG), said IPG arranged to provide pulses selectively to one or more electrodes of a multi-electrode DBS lead responsive to stimulation parameters provided by said adaptive control system,said adaptive control system comprising;
a learning module arranged to determine stimulation parameters to be output to said IPG responsive to feedback received from said physiological sensor wherein said stimulation parameters comprise a selection of a particular set of said one or more electrodes of said multi-electrode DBS lead; and
a deterministic algorithmic module arranged to maintain safety limits for determined stimulation parameters provided to said IPG.
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Abstract
A closed loop Deep Brain Stimulation (DBS) system constituted of: a physiological sensor; a multi-electrode DBS lead; an adaptive control system in communication with the physiological sensor; and an implantable pulse generator (IPG) responsive to the adaptive control system, the adaptive control system comprising a learning module operable to learn to find the optimal stimulation parameters, classify and associate patient conditions responsive to the physiological sensor with optimal stimulation parameters in a plurality of patient conditions. The adaptive DBS device control system learns to deliver the optimal stimulation parameters based on Watkins and Dayan Q learning recursive formula, the closed loop adaptive DBS control system thus finds the optimal stimulation parameters online.
59 Citations
20 Claims
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1. A closed loop Deep Brain Stimulation (DBS) system comprising:
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a physiological sensor, said physiological sensor comprising at least one of a brain activity sensor and a mechanical body motion sensor; an adaptive control system in communication with said physiological sensor; and an implantable pulse generator (IPG), said IPG arranged to provide pulses selectively to one or more electrodes of a multi-electrode DBS lead responsive to stimulation parameters provided by said adaptive control system, said adaptive control system comprising; a learning module arranged to determine stimulation parameters to be output to said IPG responsive to feedback received from said physiological sensor wherein said stimulation parameters comprise a selection of a particular set of said one or more electrodes of said multi-electrode DBS lead; and a deterministic algorithmic module arranged to maintain safety limits for determined stimulation parameters provided to said IPG. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method for deep brain stimulation (DBS) delivered to a patient in a closed loop system, said method comprising:
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providing a physiological sensor; providing a multi-electrode DBS lead; determining stimulation parameters to be provided via said provided multi-electrode DBS lead responsive to feedback received from said provided physiological sensor wherein said stimulation parameters comprise a selection of a particular set of said one or more electrodes of said provided multi-electrode DBS lead; and maintaining safety limits for said stimulation parameters provided to said multi-electrode DBS lead. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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Specification