Sensor-Based Fall Detection Dataset with 2017 Activities from 29 Subjects

This dataset comprises a diverse collection of 2,017 video recordings for fall detection, captured from various subjects. It includes 999 falls and 1,017 Activities of Daily Living (ADL), providing a balanced and realistic representation of real-world scenarios. Fall events cover a range of conditions, including falls to the left, right, front, and back, as well as complex situations such as falling while attempting to sit or from elevated positions. ADL activities include walking, running, standing up from the ground, and other daily movements. This dataset serves as a valuable resource for developing and evaluating advanced video-based fall detection models.