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

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.