Activities of Daily Living (ADL); Human Motion
The Human Activity Recognition (HAR) dataset comprises comprehensive data collected from various human activities including walking, running, sitting, standing, and jumping. The dataset is designed to facilitate research in the field of activity recognition using machine learning and deep learning techniques. Each activity is captured through multiple sensors providing detailed temporal and spatial data points, enabling robust analysis and model training.
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This is a comprehensive dataset of human arm motion during Activities of Daily Living (ADL). The Cartesian locations of the head, torso, and arm segments were recorded using a motion capture system (Vicon) from 12 participants (ages 18-72, 6 male, 6 female) performing 24 unique tasks. These include both standing and sitting tasks, as well as repetitions, selected based on what would be most useful for prosthesis users, resulting in 72 recorded trials per subject.
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