DocumentCode
3379949
Title
Prediction gait during ascending stair by using artificial neural networks
Author
Prasertsakul, Thunyanoot ; Poonsiri, Jutamanee ; Charoensuk, Warakorn
Author_Institution
Dept. of Biomed. Eng., Mahidol Univ., Nakornprathom, Thailand
fYear
2012
fDate
5-7 Dec. 2012
Firstpage
1
Lastpage
5
Abstract
Walking up or down stairs is an important activity for human lives. Gait pattern of this activity is as same as walking except the range of motion and phase of muscles activities. Many studies have been focused on behavior of this motion. Two cameras and electromyogram (EMG) are the applications used in this study and analysis the motion. To determine the relationship of the both data, it can be performed in many techniques but in this study used artificial neural network model. Nonlinear Autoregressive model with exogenous (NARX) input was applied to this study to define the relationship between the electromyogram of eight muscles and angular displacement of knee and ankle joints of both legs. The results show that the predicted data from NARX were similar to the measured data.
Keywords
autoregressive processes; bone; cameras; electromyography; gait analysis; medical signal processing; muscle; neural nets; EMG; NARX model; angular displacement; ankle joints; artificial neural networks; cameras; electromyogram; gait pattern; human lives; knee; legs; muscle activities; muscle motion; nonlinear autoregressive-with-exogenous input model; walking; Artificial neural networks; Electromyography; Joints; Knee; Legged locomotion; Muscles; EMG; gait; neural network; nonlinear autoregressive; prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering International Conference (BMEiCON), 2012
Conference_Location
Ubon Ratchathani
Print_ISBN
978-1-4673-4890-4
Type
conf
DOI
10.1109/BMEiCon.2012.6465464
Filename
6465464
Link To Document