Erik Post
Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait
Post, Erik; Van Laarhoven, Twan; Raykov, Yordan P.; Little, Max A.; Nonnekes, Jorik; Heskes, Tom M.; Bloem, Bastiaan R.; Evers, Luc J. W.
Authors
Twan Van Laarhoven
Dr YORDAN RAYKOV Yordan.Raykov@nottingham.ac.uk
ASSISTANT PROFESSOR IN DATA SCIENCE/STATISTICS
Max A. Little
Jorik Nonnekes
Tom M. Heskes
Bastiaan R. Bloem
Luc J. W. Evers
Contributors
Dr YORDAN RAYKOV Yordan.Raykov@nottingham.ac.uk
Supervisor
Abstract
Background
Accurately measuring hypokinetic arm swing during free-living gait in Parkinson’s disease (PD) is challenging due to other concurrent arm activities. We developed a method to isolate gait segments without these arm activities.
Methods
Wrist accelerometer and gyroscope data were collected from 25 individuals with PD and 25 age-matched controls while performing unscripted activities in their home environment. This was done after overnight withdrawal of dopaminergic medication (‘pre-medication’) and approximately one hour after intake (‘post-medication’). Using video annotations as ground truth, we trained and evaluated two classifiers: one for detecting gait and one for detecting gait segments without other arm activities. Based on the filtered gait segments, arm swing was quantified using the median and 95th percentile range of motion (RoM). These arm swing parameters were evaluated in three ways: (1) the agreement between predicted and video-annotated gait segments without other arm activities, (2) the sensitivity to differences between PD and controls, and (3) the sensitivity to the effects of dopaminergic medication.
Results
On the most affected side, the mean (SD) balanced accuracy for detecting gait without other arm activities was 0.84 (0.10) pre-medication and 0.88 (0.09) post-medication. The agreement between arm swing parameters of predicted and video-annotated gait segments without other arm activities was high irrespective of medication state (intra-class correlation coefficients: median RoM: 0.99; 95th percentile RoM: 0.97). Both the median and 95th percentile RoM were smaller in PD pre-medication compared to controls (median:
, 95% CI [
30.63,
10.60], p < 0.001; 95th percentile:
, 95% CI [
38.26,
18.18], p < 0.001), and smaller in pre- compared to post-medication (median:
, 95% CI [
21.35,
5.59], p < 0.001; 95th percentile:
, 95% CI [
28.48,
11.14], p < 0.001). The differences in RoM between pre- and post-medication were larger after filtering gait for the median (p < 0.01) and 95th percentile RoM (p = 0.01).
Conclusions
Filtering out gait segments with other concurrent arm activities is feasible and increases the change in arm swing parameters following dopaminergic medication in free-living conditions. This approach may be used to monitor treatment effect and disease progression in daily life.
Citation
Post, E., Van Laarhoven, T., Raykov, Y. P., Little, M. A., Nonnekes, J., Heskes, T. M., Bloem, B. R., & Evers, L. J. W. (2025). Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait. Journal of NeuroEngineering and Rehabilitation, 22(1), Article 37. https://doi.org/10.1186/s12984-025-01578-z
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 14, 2025 |
Online Publication Date | Feb 26, 2025 |
Publication Date | Feb 26, 2025 |
Deposit Date | Feb 10, 2025 |
Publicly Available Date | Feb 28, 2025 |
Journal | Journal of NeuroEngineering and Rehabilitation |
Print ISSN | 1743-0003 |
Electronic ISSN | 1743-0003 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 22 |
Issue | 1 |
Article Number | 37 |
DOI | https://doi.org/10.1186/s12984-025-01578-z |
Keywords | Parkinson’s disease; Gait; Arm swing; Hypokinesia; Wearables; Wrist-worn sensors; Digital biomarkers |
Public URL | https://nottingham-repository.worktribe.com/output/45305213 |
Publisher URL | https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-025-01578-z |
Additional Information | Received: 27 December 2024; Accepted: 14 February 2025; First Online: 26 February 2025; : ; : The Parkinson@Home Validation study was approved by the local medical ethics committee (Commissie Mensgebonden Onderzoek, region Arnhem-Nijmegen, file number 2016-1776). All participants received verbal and written information about the study protocol and signed a consent form prior to participation, in line with the Declaration of Helsinki. Written consent was obtained from all participants for participation and publication.; : The authors declare no competing interests. |
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Quantifying arm swing in Parkinson’s disease: a method accounting for arm activities during free-living gait
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