DocumentCode :
1757369
Title :
Embedded DSP-Based Telehealth Radar System for Remote In-Door Fall Detection
Author :
Garripoli, Carmine ; Mercuri, Marco ; Karsmakers, Peter ; Soh, Ping Jack ; Crupi, Giovanni ; Vandenbosch, Guy A. E. ; Pace, Calogero ; Leroux, Paul ; Schreurs, Dominique
Author_Institution :
Dept. of Electr. Eng., KU Leuven, Leuven, Belgium
Volume :
19
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
92
Lastpage :
101
Abstract :
Telehealth systems and applications are extensively investigated nowadays to enhance the quality-of-care and, in particular, to detect emergency situations and to monitor the well-being of elderly people, allowing them to stay at home independently as long as possible. In this paper, an embedded telehealth system for continuous, automatic, and remote monitoring of real-time fall emergencies is presented and discussed. The system, consisting of a radar sensor and base station, represents a cost-effective and efficient healthcare solution. The implementation of the fall detection data processing technique, based on the least-square support vector machines, through a digital signal processor and the management of the communication between radar sensor and base station are detailed. Experimental tests, for a total of 65 mimicked fall incidents, recorded with 16 human subjects (14 men and two women) that have been monitored for 320 min, have been used to validate the proposed system under real circumstances. The subjects´ weight is between 55 and 90 kg with heights between 1.65 and 1.82 m, while their age is between 25 and 39 years. The experimental results have shown a sensitivity to detect the fall events in real time of 100% without reporting false positives. The tests have been performed in an area where the radar´s operation was not limited by practical situations, namely, signal power, coverage of the antennas, and presence of obstacles between the subject and the antennas.
Keywords :
accidents; biomechanics; biomedical electronics; biomedical telemetry; digital signal processing chips; embedded systems; emergency services; geriatrics; health care; least squares approximations; medical signal detection; medical signal processing; patient care; patient monitoring; quality management; radar antennas; remote sensing; signal classification; support vector machines; telemedicine; age range; antenna coverage; automatic monitoring; continuous monitoring; cost-effective healthcare solution; cost-efficient healthcare solution; digital signal processor; elderly people independence; elderly people well-being monitoring; embedded DSP-based telehealth radar system; embedded telehealth system; emergency situation detection; fall detection data processing technique; false positive; least square support vector machine; mass 55 kg to 90 kg; mimicked fall incident; obstacle effect; quality-of-care; radar operation limitation; radar sensor-base station communication management; real-time fall emergency monitoring; real-time fall event detection sensitivity; remote in-door fall detection; remote monitoring; signal power; size 1.65 m to 1.82 m; subject height; subject weight; telehealth system application; time 320 min; Base stations; Digital signal processing; Radar; Real-time systems; Testing; Training; Zigbee; Contactless; DSP platform; Zigbee communication; fall detection; health monitoring; least-square support vector machines (LS-SVM); movement classification; radar remote sensing; telehealth systems;
fLanguage :
English
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
Publisher :
ieee
ISSN :
2168-2194
Type :
jour
DOI :
10.1109/JBHI.2014.2361252
Filename :
6914524
Link To Document :
بازگشت