TY  - CHAP
Y1  - 2011/01//
A1  - Abbate, Stefano
A1  - Avvenuti, Marco
A1  - Cola, Guglielmo
A1  - Corsini, Paolo
A1  - Light, Janet
A1  - Vecchio, Alessio
TI  - Recognition of false alarms in fall detection systems
N2  - 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.
ID  - eprints1249
PB  - IEEE
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5766464&isnumber=5766312
EP  - 28
KW  - 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;
AV  - public
SN  - 978-1-4244-8789-9
SP  - 23 
T2  - Consumer Communications and Networking Conference (CCNC)
ER  -