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Recognition of false alarms in fall detection systems

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6 Author(s)
Stefano Abbate ; IMT Institute for Advanced Studies, Lucca, Italy ; Marco Avvenuti ; Guglielmo Cola ; Paolo Corsini
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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.

Published in:

2011 IEEE Consumer Communications and Networking Conference (CCNC)

Date of Conference:

9-12 Jan. 2011