TY - GEN
T1 - Human postural stability model and artificial neural network for prediction the center of pressure
AU - Prasertsakul, Thunyanoot
AU - Wongsawat, Yodchanan
AU - Charoensuk, Warakorn
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/15
Y1 - 2014/10/15
N2 - Human postural stability is the necessary function for human livings. This function controls the whole body into the upright position. To understand the behavior of human balance control can be achieved by many methods. The mathematical model is a general technique for explanation the mechanism of biomechanics. The human postural stability system has been designed into the mathematical model. The model at sagittal and coronal plane utilized to describe the motion. This study focused on the model at coronal plane. There were two methods which performed. The first method was to use the mathematical formula for determination the COP. Second, there was the human postural stability model and artificial neural network to predict the COP. The result indicated that both methods could determine the COP, but the neural network has less error than the other method. However, there was some limitation to define the suitable parameter of neural network for getting better output.
AB - Human postural stability is the necessary function for human livings. This function controls the whole body into the upright position. To understand the behavior of human balance control can be achieved by many methods. The mathematical model is a general technique for explanation the mechanism of biomechanics. The human postural stability system has been designed into the mathematical model. The model at sagittal and coronal plane utilized to describe the motion. This study focused on the model at coronal plane. There were two methods which performed. The first method was to use the mathematical formula for determination the COP. Second, there was the human postural stability model and artificial neural network to predict the COP. The result indicated that both methods could determine the COP, but the neural network has less error than the other method. However, there was some limitation to define the suitable parameter of neural network for getting better output.
KW - Human postural stability
KW - NARX
KW - center of pressure
KW - mathematical model
UR - http://www.scopus.com/inward/record.url?scp=84911912567&partnerID=8YFLogxK
U2 - 10.1109/iEECON.2014.6925900
DO - 10.1109/iEECON.2014.6925900
M3 - Conference contribution
AN - SCOPUS:84911912567
T3 - 2014 International Electrical Engineering Congress, iEECON 2014
BT - 2014 International Electrical Engineering Congress, iEECON 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Electrical Engineering Congress, iEECON 2014
Y2 - 19 March 2014 through 21 March 2014
ER -