Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase

Taejin Choi; Chang Hwan Im; Seung Jong Kim; Hyungmin Kim; Jong Min Lee

doi:10.1109/EMBC.2018.8512867

Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase

Taejin Choi
, Chang Hwan Im
, Seung Jong Kim
, Hyungmin Kim
, Jong Min Lee

Department of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2308-2311
Number of pages	4
ISBN (Electronic)	9781538636466
DOIs	https://doi.org/10.1109/EMBC.2018.8512867
Publication status	Published - 2018 Oct 26
Event	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States Duration: 2018 Jul 18 → 2018 Jul 21

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2018-July
ISSN (Print)	1557-170X

Other

Other	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/Territory	United States
City	Honolulu
Period	18/7/18 → 18/7/21

Bibliographical note

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.

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2018.8512867

Cite this

Choi, T., Im, C. H., Kim, S. J., Kim, H., & Lee, J. M. (2018). Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 2308-2311). Article 8512867 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8512867

Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase. / Choi, Taejin; Im, Chang Hwan; Kim, Seung Jong et al.
40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2308-2311 8512867 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Choi, T, Im, CH, Kim, SJ, Kim, H & Lee, JM 2018, Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8512867, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 2308-2311, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 18/7/18. https://doi.org/10.1109/EMBC.2018.8512867

Choi T, Im CH, Kim SJ, Kim H, Lee JM. Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2308-2311. 8512867. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2018.8512867

Choi, Taejin ; Im, Chang Hwan ; Kim, Seung Jong et al. / Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 2308-2311 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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abstract = "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.",

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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.

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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.

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Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase

Abstract

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