A multimodal biomechanics and electromyography dataset of drop vertical jump under virtual-reality visual height perturbations in individuals with and without chronic ankle instability

Chronic ankle instability (CAI) is associated with altered sensorimotor control during jump–landing, but open biomechanics datasets rarely combine clinically relevant cohorts with controlled visual perturbations. We present a multimodal drop vertical jump dataset from 28 young adults (12 with CAI and 16 non-CAI controls). Participants completed one real-world 30-cm condition and four virtual-reality (VR) visual-height conditions (0, 10, 30 and 50 cm), while physical drop height remained 30 cm. Kinematic data and ground reaction forces were synchronously recorded for all participants, and bilateral surface electromyography (EMG) from six lower-limb muscles is available for 17 participants (6 with CAI and 11 non-CAI controls). The EMG acquisition protocol was designed to capture task-evoked muscle activity during high-velocity drop vertical jumps, with separate maximum voluntary isometric contraction (MVIC) assessments outside its scope. The released EMG signals were band-pass filtered by the acquisition hardware but remain unrectified and unnormalized. Participant-specific MVIC reference measurements are not available for amplitude normalization. Motion-capture data were acquired using a 38-marker Plug-in-Gait–compatible set. The resource contains labeled and quality-checked C3D files, format-converted TRC, MOT, and ASCII files, anonymized metadata, an OpenSim model, and a MATLAB kinematic-processing script. Metadata include group classification, limb dominance and affected side, demographics, anthropometrics, body composition, and bilateral lower-limb morphometrics. The dataset can support secondary analyses of landing biomechanics, neuromuscular responses to visual-height perturbations, and musculoskeletal-modeling workflows.