Journal Article

FZJ-2023-04867

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Accelerometric Classification of Resting and Postural Tremor Amplitude

van der Linden, C. ; Berger, T. ; Brandt, G. A. ; Strelow, J. N. ; Jergas, H. ; Baldermann, J. C. ; Visser-Vandewalle, V. ; Fink, G. R.FZJ* ; Barbe, M. T. ; Petry-Schmelzer, J. N. ; Dembek, T. A. (Corresponding author)

2023
MDPI Basel

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Please use a persistent id in citations: doi:10.3390/s23208621  doi:10.34734/FZJ-2023-04867

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.

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Contributing Institute(s):

1. Kognitive Neurowissenschaften (INM-3)

Research Program(s):

1. 5251 - Multilevel Brain Organization and Variability (POF4-525) (POF4-525)
2. 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) (502436811)

Appears in the scientific report 2023

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