%P 23 -28
%K accelerometer; elderly population; fall detection systems; fall recognition; false alarms; health services costs; hospitalization; injury-related deaths; specific movement patterns; wearable device;accelerometers;biomechanics;biomedical measurement;geriatrics;health care;injuries;medical signal detection;patient monitoring;telemedicine;
%R 10.1109/CCNC.2011.5766464
%I IEEE
%D 2011
%A Stefano Abbate
%A Marco Avvenuti
%A Guglielmo Cola
%A Paolo Corsini
%A Janet Light
%A Alessio Vecchio
%L eprints1249
%B Consumer Communications and Networking Conference (CCNC)
%T Recognition of false alarms in fall detection systems
%X Falls are a major cause of hospitalization and injury-related deaths among the elderly population. The detrimental effects of falls, as well as the negative impact on health services costs, have led to a great interest on fall detection systems by the health-care industry. The most promising approaches are those based on a wearable device that monitors the movements of the patient, recognizes a fall and triggers an alarm. Unfortunately such techniques suffer from the problem of false alarms: some activities of daily living are erroneously reported as falls, thus reducing the confidence of the user. This paper presents a novel approach for improving the detection accuracy which is based on the idea of identifying specific movement patterns into the acceleration data. Using a single accelerometer, our system can recognize these patterns and use them to distinguish activities of daily living from real falls; thus the number of false alarms is reduced.