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@ARTICLE{vanderLinden:1018539,
author = {van der Linden, Christina and Berger, Thea and Brandt,
Gregor A. and Strelow, Joshua N. and Jergas, Hannah and
Baldermann, Juan Carlos and Visser-Vandewalle, Veerle and
Fink, Gereon Rudolf and Barbe, Michael T. and
Petry-Schmelzer, Jan Niklas and Dembek, Till A.},
title = {{A}ccelerometric {C}lassification of {R}esting and
{P}ostural {T}remor {A}mplitude},
journal = {Sensors},
volume = {23},
number = {20},
issn = {1424-8220},
address = {Basel},
publisher = {MDPI},
reportid = {FZJ-2023-04867},
pages = {8621 -},
year = {2023},
abstract = {Clinical rating scales for tremors have significant
limitations due to low resolution, high rater dependency,
and lack of applicability in outpatient settings. Reliable,
quantitative approaches for assessing tremor severity are
warranted, especially evaluating treatment effects, e.g., of
deep brain stimulation (DBS). We aimed to investigate how
different accelerometry metrics can objectively classify
tremor amplitude of Essential Tremor (ET) and tremor in
Parkinson's Disease (PD). We assessed 860 resting and
postural tremor trials in 16 patients with ET and 25
patients with PD under different DBS settings. Clinical
ratings were compared to different metrics, based on either
spectral components in the tremorband or pure acceleration,
derived from simultaneous triaxial accelerometry captured at
the index finger and wrist. Nonlinear regression was applied
to a training dataset to determine the relationship between
accelerometry and clinical ratings, which was then evaluated
in a holdout dataset. All of the investigated accelerometry
metrics could predict clinical tremor ratings with a high
concordance $(>70\%)$ and substantial interrater reliability
(Cohen's weighted Kappa > 0.7) in out-of-sample data.
Finger-worn accelerometry performed slightly better than
wrist-worn accelerometry. We conclude that triaxial
accelerometry reliably quantifies resting and postural
tremor amplitude in ET and PD patients. A full release of
our dataset and software allows for implementation,
development, training, and validation of novel
methods.Keywords: Parkinson’s Disease; accelerometry;
essential tremor; tremor; wearables.},
cin = {INM-3},
ddc = {620},
cid = {I:(DE-Juel1)INM-3-20090406},
pnm = {5251 - Multilevel Brain Organization and Variability
(POF4-525) / DFG project 502436811 - Prospektive Evaluation
der Bestimmung des effektivsten Kontaktes mittels
individueller Traktographie zur Kontrolle des Tremors bei
Patienten mit Tiefer Hirnstimulation (TremTract Studie)
(502436811)},
pid = {G:(DE-HGF)POF4-5251 / G:(GEPRIS)502436811},
typ = {PUB:(DE-HGF)16},
pubmed = {37896714},
UT = {WOS:001099382400001},
doi = {10.3390/s23208621},
url = {https://juser.fz-juelich.de/record/1018539},
}