Design and implementation of a distributed fall detection system--personal server.
In this paper, the main results related to a fall detection system are shown by means of a personal server for the control and processing of the data acquired from multiple intelligent biomedical sensors. This server is designed in the context of a telehealthcare system for the elderly, to whom falls represent a high-risk cause of serious injuries, and its architecture can be extended to patients suffering from chronic diseases. The main design issues and developments in terms of the server hardware and software are presented with the aim of providing a real-time analysis of the processed biosignals. As a result, the evaluation study of the implemented algorithm for fall detection through a set of laboratory experiments is presented, together with some important issues in terms of the device's consumption. The proposed algorithm exhibits excellent outcomes in fall detection.
Biomedical Engineering Group, and the Spanish Network Center of Biomedical Research in Bioengineering, Biomaterials and Nanomedicine, University of Seville, Seville 41092, Spain. mestudillo@us.es
Miguel Angel
MA
Estudillo-Valderrama
Laura M
LM
Roa
Javier
J
Reina-Tosina
David
D
Naranjo-Hernández
D000054:Acceleration; D000058:Accidental Falls; D000465:Algorithms; D003195:Computer Communication Networks / Q000295:instrumentation*; D005260:Female; D006801:Humans; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D009068:Movement / Q000502:physiology; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013686:Telemetry / Q000295:instrumentation* / Q000379:methods*; D014159:Transducers