Research Article
Advanced Patient or Elder Fall Detection based on Movement and Sound Data
@INPROCEEDINGS{10.4108/ICST.PERVASIVEHEALTH2008.2520, author={Charalampos Doukas and Ilias Maglogiannis}, title={Advanced Patient or Elder Fall Detection based on Movement and Sound Data}, proceedings={2nd International ICST Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2008}, month={7}, keywords={component; patient monitoring fall detection movement and sound analysis SVM classification}, doi={10.4108/ICST.PERVASIVEHEALTH2008.2520} }- Charalampos Doukas
Ilias Maglogiannis
Year: 2008
Advanced Patient or Elder Fall Detection based on Movement and Sound Data
PERVASIVEHEALTH
ICST
DOI: 10.4108/ICST.PERVASIVEHEALTH2008.2520
Abstract
The paper presents am initial implementation of a patient monitoring system that may be used for patient activity recognition and emergency treatment in case a patient or an elder falls. Sensors equipped with accelerometers and microphones are attached on the body of the patients and transmit patient movement and sound data wirelessly to the monitoring unit. Applying Short Time Fourier Transform (STFT) and spectrogram analysis on sounds detection of fall incidents is possible. The classification of the sound and movement data is performed using Support Vector Machines. Evaluation results indicate the high accuracy and the effectiveness of the proposed implementation.
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