TY - GEN
T1 - Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase
AU - Choi, Taejin
AU - Im, Chang Hwan
AU - Kim, Seung Jong
AU - Kim, Hyungmin
AU - Lee, Jong Min
N1 - Funding Information:
* Research supported by the Industrial Core Technology Development Program through the Ministry and Trade Industry and Energy (Grant Number: 10045164) and the Korea Institute of Science and Technology Institutional Program (Grant Number: 2E27980).
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/26
Y1 - 2018/10/26
N2 - A recent research has proposed a prediction method of walking speed with soleus electromyogram (EMG) signal activation level at push-off phase. However, the prediction of walking speed at low speed is inaccurate and the coefficients of determination (R2 values) of the used linear regression model is low. In this study, we propose a new method for predicting walking speed during swing phase with soleus EMG signal activation levels at pre-load and push-off phases, and square root value is used as a feature. The proposed method is verified by walking experiment with 5 nondisabled subjects. (R2 values) of the new method is improved by 10.3 % than that of the method used in the previous study. And the proposed method improves accuracy mainly at low speed and precision at high speed to predict a correct walking speed throughout walking speed range. Thus, the proposed method enhances the performance of the prediction model of walking speed without being biased in the range of high or low speed. The proposed method has potential to be used to control the gait speed of a lower-limb exoskeleton according to wearer's gait intention.
AB - A recent research has proposed a prediction method of walking speed with soleus electromyogram (EMG) signal activation level at push-off phase. However, the prediction of walking speed at low speed is inaccurate and the coefficients of determination (R2 values) of the used linear regression model is low. In this study, we propose a new method for predicting walking speed during swing phase with soleus EMG signal activation levels at pre-load and push-off phases, and square root value is used as a feature. The proposed method is verified by walking experiment with 5 nondisabled subjects. (R2 values) of the new method is improved by 10.3 % than that of the method used in the previous study. And the proposed method improves accuracy mainly at low speed and precision at high speed to predict a correct walking speed throughout walking speed range. Thus, the proposed method enhances the performance of the prediction model of walking speed without being biased in the range of high or low speed. The proposed method has potential to be used to control the gait speed of a lower-limb exoskeleton according to wearer's gait intention.
UR - http://www.scopus.com/inward/record.url?scp=85056653823&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2018.8512867
DO - 10.1109/EMBC.2018.8512867
M3 - Conference contribution
C2 - 30440868
AN - SCOPUS:85056653823
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2308
EP - 2311
BT - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Y2 - 18 July 2018 through 21 July 2018
ER -