Finger-specific effects of age on tapping speed and motor fatigability.

Fatigue aging behavior in-field experiment motor fatigability motor slowing tapping speed

Journal

Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954

Informations de publication

Date de publication:
2024
Historique:
received: 03 05 2024
accepted: 22 08 2024
medline: 10 10 2024
pubmed: 10 10 2024
entrez: 10 10 2024
Statut: epublish

Résumé

Increased motor fatigability is a symptom of many neuromuscular and neurodegenerative disorders. However, it is difficult to pinpoint pathological motor fatigability, since the phenomena has not yet been fully characterized in the healthy population. In this study, we investigate how motor fatigability differs across age. Given that many disorders involve supraspinal components, we characterize motor fatigability with a paradigm that has previously been associated with supraspinal mechanisms. Finger tapping at maximal speed results in a rapid decrease in movement speed, which is a measure of motor fatigability. We collected finger tapping data in a field experiment from the general population with a smartphone app, and we investigated age differences in maximal tapping speed, as well as the decrease in tapping speed for the index, middle, and little fingers. We found that the maximal tapping speed differed significantly between young (18-30 years, These findings might relate to dexterity, with more dexterous movements being more resistant to fatigue. In this study, we provide a characterization of motor fatigability in the general population which can be used as a comparison for clinical populations in the future.

Identifiants

pubmed: 39386279
doi: 10.3389/fnhum.2024.1427336
pmc: PMC11461208
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1427336

Informations de copyright

Copyright © 2024 Heimhofer, Neumann, Odermatt, Bächinger and Wenderoth.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Caroline Heimhofer (C)

Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Center for Neuroscience Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland.

Amira Neumann (A)

Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Ingrid Odermatt (I)

Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Center for Neuroscience Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland.

Marc Bächinger (M)

Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Nicole Wenderoth (N)

Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Center for Neuroscience Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland.
Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Zurich, Switzerland.

Classifications MeSH