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Estimation of Ankle Joint Torque and Angle Based on S-EMG Signal for Assistive Rehabilitation Robots

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Biomedical Signal Processing

Part of the book series: Series in BioEngineering ((SERBIOENG))

Abstract

Surface Electromyography (S-EMG) has shown the advantages of robotic rehabilitation. Robotic rehabilitation can be significantly improved if the intended body movement of the patients can be well identified. In this chapter, we first use the SVM classifier to identify the intended motion patterns, which are plantarflexion and dorsiflexion, by using three wireless EMG sensors placed at the tibialis anterior, gastrocnemius lateralis and gastrocnemius medialis muscles. To estimate the ankle joint torque as well as the joint angle for both plantarflexion and dorsiflexion, this chapter also develops nonlinear mathematical models for joint torque estimation and utilises Swarm Techniques to identify model parameters for each movement pattern of the ankle. During rehabilitation, once the intended motion is recognised, the activation functions extracted from an individual associated EMG channel can be used to estimate both the torque and angle by using the established nonlinear models. Experimental results demonstrated the effectiveness of the proposed approach.

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Acknowledgements

This work was supported by the Australia–China Joint Institute for Health Technology and Innovation established by the University of Technology Sydney (UTS) and Sun Yat-sen University (SYSU).

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Authors and Affiliations

  1. School of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, Ultimo, Australia

    Palayil Baby Jephil, Paras Acharaya, Lian Xu, Kairui Guo, Hairong Yu & Steven Su

  2. Department of Sports and Exercise Science, Faculty of Health, University of Technology Sydney, Ultimo, Australia

    Mark Watsford

  3. School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, 510006, China

    Song Rong

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  1. Palayil Baby Jephil
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Correspondence to Steven Su .

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  1. MARCS Institute, Western Sydney University, Penrith, NSW, Australia

    Ganesh Naik

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Baby Jephil, P. et al. (2020). Estimation of Ankle Joint Torque and Angle Based on S-EMG Signal for Assistive Rehabilitation Robots. In: Naik, G. (eds) Biomedical Signal Processing. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-9097-5_2

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  • DOI: https://doi.org/10.1007/978-981-13-9097-5_2

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