Pre-impact Fall Detection using Wearable Sensor Unit
Soonjae Ahn, Isu Shin, Bora Jeong, Youngho Kim · 2014
In this study, we verified our pre-impact fall detection algorithm through a clinical trials using wearable sensor (accelerometer and gyro sensor) at waist. Forty male volunteers participated in the clinical trial (three types of falls and seven types of ADLs). Results show that falls could be detected with an average lead-time of 530ms before the impact occurs, with no false alarms (100% specificity) and no incorrect detects (100% sensitivity). Our algorithm for pre-impact fall detection with a wearable sensor unit could be very helpful to minimize fall risk.