Falls are the number one cause of injury in older adults. Wearable sensor arrays (e.g. accelerometers) represent a promising technique for determining the cause and circumstances of falls in high-risk individuals. Previous studies have shown that the occurrence of a fall can be sensed reliably from the high acceleration generated at impact. This thesis extends this research, by developing and evaluating a sensor array system for determining the cause of a fall. Sixteen young adults participated in trials involving falls due to slips, trips, and “other” causes. 3D acceleration data acquired during the falling trials were input to a linear discriminant analysis (LDA) technique. This routine achieved 96% sensitivity in detecting the cause of a fall using acceleration data from three markers (left foot, right foot and sternum). These results indicate the utility of a three node accelerometer array for distinguishing the cause of falls.
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