A Kinematic and EMG Dataset for Upper Limb and Hand Movement Analysis in Post-Stroke and Healthy Subjects

This paper presents a kinematic and electromyographic (EMG) dataset of movements of upper limbs and hands during functional tasks in 3D space, such as reaching, grasping, lifting, and rotating objects. The study includes a sample of 10 healthy subjects (aged 24 to 73 years) and 10 individuals with upper limb motor deficits subsequent to stroke (aged 62 to 82 years). For each task, raw data and computed variables are provided, including: 3D coordinates of external markers, joint angles of the upper limb in sagittal, transverse, and horizontal planes, phalangeal angles, and surface EMG signals from the main upper limb muscles. The dataset presented in this study, collected from both healthy and post-stroke subjects of various ages, serves as a valuable resource for future research on motor function in humans. It can be used as a normative reference for analyzing pathological movement of people with stroke, thus addressing their recovery trajectory, for testing motor control simulation models, and for developing control algorithms for robots or active upper limb exoskeletons in rehabilitation.