A hand biomechanics dataset of kinematics, kinetics, electromyography, and imaging in healthy adults

Developing musculoskeletal hand models requires a variety of experimental biomechanics data. However, collecting robust biomechanics hand data is a time intensive process leading to a lack of widely available datasets. To address this issue the biomechanics hand modeling database (BHaM) was made as a collection of experimental data to aid the development, testing, and validation of musculoskeletal models and simulations. BHaM includes two datasets: (1) a population dataset (n = 726 adults) describing hand strength (pinch and grip), self-reported hand function (Michigan Hand Questionnaire), and anthropometric measurements (from photographs), and (2) a biomechanics dataset (n = 30 adults) describing kinematics (marker-based motion capture), kinetics (isometric and isokinetic data), and electromyography (surface and fine wire) during 19 tasks across the elbow, wrist, and hand. A subset of the biomechanics dataset (n = 15 adults) also includes magnetic resonance imaging of the shoulder through wrist. Participants for both datasets were recruited to represent a diverse population of healthy adults, ranging from 18 to 91 years.

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Publication Details

Journal
Scientific Data
Published
2026-03-11
DOI
https://doi.org/10.1038/s41597-026-06939-4
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.00

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article

A hand biomechanics dataset of kinematics, kinetics, electromyography, and imaging in healthy adults

Joel B. Harley, Maximillian T. Diaz, Jennifer A. Nichols, Erica M. Lindbeck et al.
Scientific Data
Motor Control and Adaptation
article

A hand biomechanics dataset of kinematics, kinetics, electromyography, and imaging in healthy adults

Joel B. Harley, Maximillian T. Diaz, Jennifer A. Nichols, Erica M. Lindbeck, Kalyn M. Kearney, Troy F Kelly, Alexis Benoit, Isaly Tappan, Lavanya Durai, Michael B Officer, Justin B. Nunag, William S. Bowers
article en

Abstract

Developing musculoskeletal hand models requires a variety of experimental biomechanics data. However, collecting robust biomechanics hand data is a time intensive process leading to a lack of widely available datasets. To address this issue the biomechanics hand modeling database (BHaM) was made as a collection of experimental data to aid the development, testing, and validation of musculoskeletal models and simulations. BHaM includes two datasets: (1) a population dataset (n = 726 adults) describing hand strength (pinch and grip), self-reported hand function (Michigan Hand Questionnaire), and anthropometric measurements (from photographs), and (2) a biomechanics dataset (n = 30 adults) describing kinematics (marker-based motion capture), kinetics (isometric and isokinetic data), and electromyography (surface and fine wire) during 19 tasks across the elbow, wrist, and hand. A subset of the biomechanics dataset (n = 15 adults) also includes magnetic resonance imaging of the shoulder through wrist. Participants for both datasets were recruited to represent a diverse population of healthy adults, ranging from 18 to 91 years.

Scientific Data
University of Florida (US)
National Science Foundation, Division of Materials Research, National Center for Advancing Translational Sciences
Openalex Percentile: Top 31%
Motor Control and Adaptation
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