TY - GEN
T1 - Walk detection with a kinematic sensor
T2 - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
AU - Barralon, Pierre
AU - Vuillerme, Nicolas
AU - Noury, Norbert
PY - 2006
Y1 - 2006
N2 - This study is included in the framework of Health Smart Homes which monitor some physiological or not physiological parameters of elderly people living independently at home. In this study we will focus on the walk detection. Walk activity is one parameter to evaluate the health of patient. For example, the total time of walk during a day allows assessing quickly if the subject is mobile rather than immobile. To reach this goal we used a kinematic sensor placed on the chest recording the movements of the subject. The data are analyzed by six algorithms to detect walk phases: two based on Fourier analysis and the others using a wavelet decomposition (DWT and CWT). All algorithms are described and the performances are evaluated on real data recorded with 20 elderly people. Results show that the method using the DWT decomposition is the most efficient (78.5% in sensitivity and 67.6% in specificity).
AB - This study is included in the framework of Health Smart Homes which monitor some physiological or not physiological parameters of elderly people living independently at home. In this study we will focus on the walk detection. Walk activity is one parameter to evaluate the health of patient. For example, the total time of walk during a day allows assessing quickly if the subject is mobile rather than immobile. To reach this goal we used a kinematic sensor placed on the chest recording the movements of the subject. The data are analyzed by six algorithms to detect walk phases: two based on Fourier analysis and the others using a wavelet decomposition (DWT and CWT). All algorithms are described and the performances are evaluated on real data recorded with 20 elderly people. Results show that the method using the DWT decomposition is the most efficient (78.5% in sensitivity and 67.6% in specificity).
UR - https://www.scopus.com/pages/publications/34047152899
U2 - 10.1109/IEMBS.2006.260770
DO - 10.1109/IEMBS.2006.260770
M3 - Conference contribution
C2 - 17945661
AN - SCOPUS:34047152899
SN - 1424400325
SN - 9781424400324
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 1711
EP - 1714
BT - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Y2 - 30 August 2006 through 3 September 2006
ER -