Rapid response elderly safety monitoring (RESAM) system architecture. Credit: IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024). DOI: 10.1109/TNSRE.2024.3409197 When older adults fall at home, every second counts—especially when they are alone. New research from Binghamton University aims to cut reaction times with a human action recognition (HAR) algorithm that uses local computing power to analyze sensor data and detect abnormal movements without transmitting to a processing center offsite. Professor Yu Chen and Ph.D. student Han Sun from the Thomas J. Watson College of Engineering and Applied Science’s Department Read More