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Closed-Loop Deep Brain Stimulation for Essential Tremor Based on Thalamic Local Field Potentials.
He, Shenghong; Baig, Fahd; Mostofi, Abteen; Pogosyan, Alek; Debarros, Jean; Green, Alexander L; Aziz, Tipu Z; Pereira, Erlick; Brown, Peter; Tan, Huiling.
Afiliação
  • He S; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
  • Baig F; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
  • Mostofi A; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
  • Pogosyan A; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
  • Debarros J; Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St. George's, University of London, Oxford, UK.
  • Green AL; Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St. George's, University of London, Oxford, UK.
  • Aziz TZ; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
  • Pereira E; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
  • Brown P; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
  • Tan H; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Mov Disord ; 36(4): 863-873, 2021 04.
Article em En | MEDLINE | ID: mdl-33547859
ABSTRACT

BACKGROUND:

High-frequency thalamic stimulation is an effective therapy for essential tremor, which mainly affects voluntary movements and/or sustained postures. However, continuous stimulation may deliver unnecessary current to the brain due to the intermittent nature of the tremor.

OBJECTIVE:

We proposed to close the loop of thalamic stimulation by detecting tremor-provoking movement states using local field potentials recorded from the same electrodes implanted for stimulation, so that the stimulation is only delivered when necessary.

METHODS:

Eight patients with essential tremor participated in this study. Patient-specific support vector machine classifiers were first trained using data recorded while the patient performed tremor-provoking movements. Then, the trained models were applied in real-time to detect these movements and triggered the delivery of stimulation.

RESULTS:

Using the proposed method, stimulation was switched on for 80.37 ± 7.06% of the time when tremor-evoking movements were present. In comparison, the stimulation was switched on for 12.71 ± 7.06% of the time when the patients were at rest and tremor-free. Compared with continuous stimulation, a similar amount of tremor suppression was achieved while only delivering 36.62 ± 13.49% of the energy used in continuous stimulation.

CONCLUSIONS:

The results suggest that responsive thalamic stimulation for essential tremor based on tremor-provoking movement detection can be achieved without any requirement for external sensors or additional electrocorticography strips. Further research is required to investigate whether the decoding model is stable across time and generalizable to the variety of activities patients may engage with in everyday life. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tremor Essencial / Estimulação Encefálica Profunda Limite: Humans Idioma: En Revista: Mov Disord Assunto da revista: NEUROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tremor Essencial / Estimulação Encefálica Profunda Limite: Humans Idioma: En Revista: Mov Disord Assunto da revista: NEUROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Reino Unido