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Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S.
Fra Czek, Tomasz M; Ferleger, Benjamin I; Brown, Timothy E; Thompson, Margaret C; Haddock, Andrew J; Houston, Brady C; Ojemann, Jeffrey G; Ko, Andrew L; Herron, Jeffrey A; Chizeck, Howard J.
Afiliación
  • Fra Czek TM; Neuroscience Program, University of Washington, Seattle, WA, United States.
  • Ferleger BI; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.
  • Brown TE; Department of Philosophy, University of Washington, Seattle, WA, United States.
  • Thompson MC; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.
  • Haddock AJ; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.
  • Houston BC; Neuroscience Program, University of Washington, Seattle, WA, United States.
  • Ojemann JG; Department of Neurological Surgery, University of Washington, Seattle, WA, United States.
  • Ko AL; Department of Neurological Surgery, University of Washington, Seattle, WA, United States.
  • Herron JA; Department of Neurological Surgery, University of Washington, Seattle, WA, United States.
  • Chizeck HJ; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.
Front Neurosci ; 15: 749705, 2021.
Article en En | MEDLINE | ID: mdl-34955714
Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to "close the loop" on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. "Graded" aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Aspecto: Ethics Idioma: En Revista: Front Neurosci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Aspecto: Ethics Idioma: En Revista: Front Neurosci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza