A multimodal gait dataset with ultrasound, EMG, and motion capture from young adults at various walking speeds
2026-09-02
Human gait is a widely studied motor behavior, yet direct observation of skeletal muscle dynamics during walking remains limited. We present a novel multimodal gait dataset that integrates real-time B-mode ultrasound imaging with synchronized motion and surface electromyography (EMG) data. Twenty-six healthy adults (13 male, 13 female) completed walking trials across a range of conditions: three self-selected speeds (self-fast, self-paced, self-slow) and eight auditory-cued pacing conditions (60–130 beat per minute (bpm) in 10 bpm increments). Whole-body motion and ground reaction forces (GRFs) during gait were captured using a 3D motion capture system and two force plates, with a standardized 36-marker lower-body marker set. Surface EMG was recorded bilaterally from the tibialis anterior (TA), soleus, medial gastrocnemius, and lateral gastrocnemius muscles. Ultrasound probes were secured over the bilateral TA muscles to capture continuous fascicle dynamics throughout the gait cycle. Based on the motion capture data, inverse kinematics and inverse dynamics analyses were performed in musculoskeletal modelling software OpenSim to obtain joint kinematics and joint moments for each trial. This dataset enables the investigation of lower-limb muscle mechanics during gait, allowing exploration of the pathway from neural activation through muscle mechanics to musculoskeletal behavior.