SmartFall: An Automatic Fall Detection System Based on Subsequence Matching for the SmartCane

Fall-induced injury has become a leading cause of death for the elderly. Many elderly people rely on canes as an assis- tive device to overcome problems such as balance disorder and leg weakness, which are believed to have led to many incidents of falling. In this paper, we present the design and the implementation of SmartFall, an automatic fall de- tection system for the SmartCane system we have developed previously. SmartFall employs subsequence matching, which di®ers fundamentally from most existing fall detection sys- tems based on multi-stage thresholding. The SmartFall sys- tem achieves a near perfect fall detection rate for the four types of fall conducted in the experiments. After augment- ing the algorithm with an assessment on the peak impact force, we have successfully reduced the false-positive rate of the system to close to zero for all six non-falling activities performed in the experiment.