Automated Deep Brain Stimulation Programming for Tremor

被引:29
作者
Haddock, Andrew [1 ,2 ]
Mitchell, Kyle T. [3 ,4 ]
Miller, Andrew [3 ]
Ostrem, Jill L. [3 ]
Chizeck, Howard J. [1 ,2 ]
Miocinovic, Svjetlana [5 ]
机构
[1] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
[2] Univ Washington, Ctr Sensorimotor Neural Engn, Seattle, WA 98195 USA
[3] Univ Calif San Francisco, Dept Neurol, San Francisco, CA 94143 USA
[4] Duke Univ, Dept Neurol, Durham, NC 27704 USA
[5] Emory Univ, Dept Neurol, Atlanta, GA 30322 USA
关键词
Deep brain stimulation; Parkinson's disease; essential tremor; intelligent systems; movement disorders; neuromodulation; wearable sensors; PARKINSONS-DISEASE;
D O I
10.1109/TNSRE.2018.2852222
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Deep brain stimulation (DBS) programming, the systematic selection of fixed electrical stimulation parameters that deliver maximal therapeutic benefit while limiting side effects, poses several challenges in the treatment of movement disorders. DBS programming requires the expertise of trained neurologists or nurses who assess patient symptoms according to standardized clinical rating scales and use patient reports of DBS-related side effects to adjust stimulation parameters and optimize therapy. In this paper, we describe and validate an automated software platform for DBS programming for tremor associated with Parkinson's disease and essential tremor. DBS parameters are changed automatically through a direct computer interface with implanted neurostimulators. Each tested DBS setting is ranked according to its effect on tremor, which is assessed using smartwatch inertial measurement unit data, and side effects, which are reported through a user interface. Blinded neurologist assessments showed the automated programming method performed at least as well as clinician mediated programming in selecting the optimal settings for tremor therapy. This proof of concept study describes a novel DBS programming paradigm that may improve programming efficiency and outcomes, increase access to programming outside specialty clinics, and aid in the development of adaptive and closed-loop DBS strategies.
引用
收藏
页码:1618 / 1625
页数:8
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