A multimodal dataset of lower-limb kinematics, kinetics, electromyography, and musculoskeletal simulations from healthy adults during overground walking

This dataset provides a multimodal collection of lower-limb biomechanical data from 29 healthy adults during overground walking at self-selected speeds. Synchronized measurements include three-dimensional marker trajectories, ground reaction forces (GRF), and surface electromyography (EMG) signals, acquired using an optical motion capture system, force platform, and wireless EMG sensors.

In addition to raw experimental data, the dataset contains derived spatiotemporal parameters and subject-specific musculoskeletal simulation outputs generated using the AnyBody Modeling System. These include joint kinematics, joint moments, joint reaction forces, and muscle forces of the lower limb. EMG signals were processed and normalized to maximum voluntary contraction (MVC), enabling inter-subject comparisons.

The dataset is organized per subject and trial and includes standardized file formats (C3D, ASCII, HDF5, and Excel) to facilitate interoperability with common biomechanics software tools. Detailed gait event annotations—including initial contact, toe-off, foot flat, mid-stance, double support, and terminal swing—are provided for each gait cycle, supporting time-resolved biomechanical analyses.

This dataset addresses the lack of publicly available resources that integrate synchronized experimental measurements with musculoskeletal modeling outputs. It can be used for studying human locomotion, validating biomechanical models, investigating neuromuscular control strategies, and developing clinical assessment tools and assistive technologies

Key Words  Lower-limb biomechanics; gait analysis; motion capture; electromyography (EMG); ground reaction forces; musculoskeletal modeling; AnyBody; joint reaction forces; muscle forces; overground walking; multimodal dataset