PhysioMio: bilateral and longitudinal HD-sEMG dataset of 16 hand gestures from 48 stroke patients

The PhysioMio dataset presented in this paper provides longitudinal high-density surface electromyography (HD-sEMG) recordings from both the healthy and impaired forearms of 48 stroke patients with arm paresis, captured during the performance of 16 distinct hand gestures. Patients were recorded at regular intervals during their individual inpatient rehabilitation stay, resulting in an average of three recording sessions at different stages of post-stroke rehabilitation per patient. The HD-sEMG signals were collected using a dry 64-electrode array positioned around the forearm, enabling observation of muscle activation patterns. The healthy arm was recorded during the first week to serve as a reference, while subsequent recordings focused solely on the impaired arm. This data can offer insights into neuromuscular deficits related to stroke and allow for comparative analysis between healthy and impaired arms. This dataset serves as a valuable resource for studying motor impairment and recovery potential in stroke-induced arm paresis, supporting advancements in personalized rehabilitation and assistive technologies.

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Journal
Scientific Data
Published
2026-01-09
DOI
https://doi.org/10.1038/s41597-026-06557-0
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.00

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article

PhysioMio: bilateral and longitudinal HD-sEMG dataset of 16 hand gestures from 48 stroke patients

Tim Christian Lueth, Peter Rieckmann, Julian Ilg, Alexander C. R. Oldemeier et al.
Scientific Data
Muscle activation and electromyography studies
article

PhysioMio: bilateral and longitudinal HD-sEMG dataset of 16 hand gestures from 48 stroke patients

Tim Christian Lueth, Peter Rieckmann, Julian Ilg, Alexander C. R. Oldemeier, Sabine Krause, Marie Fieweger, Peter Young, Luca Deuschel
article en

Abstract

The PhysioMio dataset presented in this paper provides longitudinal high-density surface electromyography (HD-sEMG) recordings from both the healthy and impaired forearms of 48 stroke patients with arm paresis, captured during the performance of 16 distinct hand gestures. Patients were recorded at regular intervals during their individual inpatient rehabilitation stay, resulting in an average of three recording sessions at different stages of post-stroke rehabilitation per patient. The HD-sEMG signals were collected using a dry 64-electrode array positioned around the forearm, enabling observation of muscle activation patterns. The healthy arm was recorded during the first week to serve as a reference, while subsequent recordings focused solely on the impaired arm. This data can offer insights into neuromuscular deficits related to stroke and allow for comparative analysis between healthy and impaired arms. This dataset serves as a valuable resource for studying motor impairment and recovery potential in stroke-induced arm paresis, supporting advancements in personalized rehabilitation and assistive technologies.

Scientific DataVol. 13(1)
Refonet (DE), Technical University of Munich (DE)
Bundesministerium für Bildung und Forschung, Bundesministerium für Wirtschaft und Energie
Openalex Percentile: Top 93%
Muscle activation and electromyography studies
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PhysioMio: bilateral and longitudinal HD-sEMG dataset of 16 hand gestures from 48 stroke patients — Tim Christian Lueth, Peter Rieckmann, et al. · Scientific Data (2026) | TGRS Research Map | TGRS