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Tremor evaluation using smartphone accelerometry in standardized settings.
Sahin, Gürdal; Halje, Pär; Uzun, Sena; Jakobsson, Andreas; Petersson, Per.
  • Sahin G; Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Sciences, Lund University, Lund, Sweden.
  • Halje P; Department of Internal Medicine, Hässleholm Hospital, Region Skåne, Hässleholm, Sweden.
  • Uzun S; Skåneuro Neurology Clinic, Lund, Sweden.
  • Jakobsson A; Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Sciences, Lund University, Lund, Sweden.
  • Petersson P; Skåneuro Neurology Clinic, Lund, Sweden.
Front Neurosci ; 16: 861668, 2022.
Article in English | MEDLINE | ID: covidwho-2009890
ABSTRACT
Tremor can be highly incapacitating in everyday life and typically fluctuates depending on motor state, medication status as well as external factors. For tremor patients being treated with deep-brain stimulation (DBS), adapting the intensity and pattern of stimulation according the current needs therefore has the potential to generate better symptomatic relief. We here describe a procedure for how patients independently could perform self-tests in their home to generate sensor data for on-line adjustments of DBS parameters. Importantly, the inertia sensor technology needed exists in any standard smartphone, making the procedure widely accessible. Applying this procedure, we have characterized detailed features of tremor patterns displayed by both Parkinson's disease and essential tremor patients and directly compared measured data against both clinical ratings (Fahn-Tolosa-Marin) and finger-attached inertia sensors. Our results suggest that smartphone accelerometry, when used in a standardized testing procedure, can provide tremor descriptors that are sufficiently detailed and reliable to be used for closed-loop control of DBS.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Front Neurosci Year: 2022 Document Type: Article Affiliation country: Fnins.2022.861668

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Front Neurosci Year: 2022 Document Type: Article Affiliation country: Fnins.2022.861668