Patient fall detection using support vector machines
C Doukas, I Maglogiannis, P Tragas, D Liapis… - Artificial Intelligence and …, 2007 - Springer
Artificial Intelligence and Innovations 2007: from Theory to Applications …, 2007•Springer
This paper presents a novel implementation of a patient fall detection system that may be
used for patient activity recognition and emergency treatment. Sensors equipped with
accelerometers are attached on the body of the patients and transmit patient movement data
wirelessly to the monitoring unit. The methodology of support Vector Machines is used for
precise classification of the acquired data and determination of a fall emergency event. Then
a context-aware server transmits video from patient site properly coded according to both …
used for patient activity recognition and emergency treatment. Sensors equipped with
accelerometers are attached on the body of the patients and transmit patient movement data
wirelessly to the monitoring unit. The methodology of support Vector Machines is used for
precise classification of the acquired data and determination of a fall emergency event. Then
a context-aware server transmits video from patient site properly coded according to both …
Abstract
This paper presents a novel implementation of a patient fall detection system that may be used for patient activity recognition and emergency treatment. Sensors equipped with accelerometers are attached on the body of the patients and transmit patient movement data wirelessly to the monitoring unit. The methodology of support Vector Machines is used for precise classification of the acquired data and determination of a fall emergency event. Then a context-aware server transmits video from patient site properly coded according to both patient and network status. Evaluation results indicate the high accuracy of the classification method and the effectiveness of the proposed implementation.
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