Sensor-Based Fall Detection Dataset with 8,953 Activities from 29 Subjects

This dataset presents a robust collection of 8,953 recorded activities for video and sensor-based fall detection, gathered from 29 diverse subjects. It includes 2,791 falls and 6,162 Activities of Daily Living (ADL), offering extensive coverage of real-world scenarios. Fall cases span a variety of situations, including falls to the left, right, front, back, and complex scenarios such as falling while attempting to sit on a chair or from elevated positions. ADL activities include walking, running, standing up from the ground, and driving, making this dataset a valuable resource for developing and testing advanced fall detection models.