A multimodal gait dataset with ultrasound, EMG, and motion capture from young adults at various walking speeds

This study presents an open-source, multimodal biomechanics dataset of healthy human walking, comprising electromyography (EMG), ultrasound imaging, kinematic, and kinetic data. Data were collected under a total of 11 walking conditions: 3 self-selected speed conditions and 8 auditory cue-paced conditions. Participants walked at their preferred pace in the self-selected conditions, and synchronized their steps to auditory cues in the cue-paced conditions. This comprehensive dataset is intended to support research in gait analysis, muscle function, neuromechanics, and machine learning applications in human movement science.