Survey and evaluation of real-time fall detection approaches
HONET'09 Proceedings of the 6th international conference on High capacity optical networks and enabling technologies
iPrevention: towards a novel real-time smartphone-based fall prevention system
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A multi-sensor approach for fall risk prediction and prevention in elderly
ACM SIGAPP Applied Computing Review
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Physical activity monitoring of the elderly people provides valuable information for health aware services. This paper presents the implementation of a system to sense, send, display and store physiology activity. The system includes a wearable device to be worn by the individual to collect physical activity data, a wireless communication link between the patient and the monitoring network. A fall detection and heart beat measurement are also included to provide better monitoring. Testing results show the system function properly and provide accurate fall detection and data for monitoring purpose.