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Tremor evaluation using smartphone accelerometry in standardized settings

Sahin, Gürdal LU orcid ; Halje, Pär LU ; Uzun, Sena LU ; Jakobsson, Andreas LU orcid and Petersson, Per LU (2022) In Frontiers in Neuroscience 16.
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... (More)

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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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
closed-loop, essential tremor, inertia sensors, neuromodulation, Parkinson’s disease
in
Frontiers in Neuroscience
volume
16
article number
861668
publisher
Frontiers Media S. A.
external identifiers
  • pmid:35979340
  • scopus:85136203856
ISSN
1662-4548
DOI
10.3389/fnins.2022.861668
language
English
LU publication?
yes
id
38e0f6dc-6109-4b6b-af19-f7a6afc4e92d
date added to LUP
2022-09-23 14:21:39
date last changed
2024-06-11 00:49:57
@article{38e0f6dc-6109-4b6b-af19-f7a6afc4e92d,
  abstract     = {{<p>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.</p>}},
  author       = {{Sahin, Gürdal and Halje, Pär and Uzun, Sena and Jakobsson, Andreas and Petersson, Per}},
  issn         = {{1662-4548}},
  keywords     = {{closed-loop; essential tremor; inertia sensors; neuromodulation; Parkinson’s disease}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Neuroscience}},
  title        = {{Tremor evaluation using smartphone accelerometry in standardized settings}},
  url          = {{http://dx.doi.org/10.3389/fnins.2022.861668}},
  doi          = {{10.3389/fnins.2022.861668}},
  volume       = {{16}},
  year         = {{2022}},
}