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Design and Development of a Lower Extremity Rehabilitation Training System for Myoelectric Assessment

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Communications, Signal Processing, and Systems (CSPS 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1033))

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Abstract

In order to provide a more scientific rehabilitation training plan for patients with lower limb paralysis caused by illness or accidents when they train independently or at home, a lower limb rehabilitation training system with myoelectric assessment was hereby designed to improve the therapeutic effect and to reduce the difficulty of nursing care. The collected electromyographic signals of the target muscle surface after homogenization and standardization were used as the evaluation standard, and suitable training plans were given for different muscle functional states of different patients, which were combined with the mobile terminal to realize the visualization of data and training guidance. According to the repeated experiments, the accuracy of the judgment of the functional status of the target muscle of the patient could reach more than 85% without resistance, and the judgment accuracy was increased to more than 92% after adding resistance appropriately. The design can directly feedback and guide rehabilitation training through EMG and visual interface, which will further improve the effectiveness and convenience of training for patients with lower limb dysfunction.

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References

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Acknowledgements

This work was supported in part by Tianjin Municipal Education Commission Scientific Research Program Project (2022ZD009, 2022ZD035, 2022ZD036, 2021KJ011) and Central Government Guided Local Science and Technology Development Funds Project Plan (22ZYCGSN00480).

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Correspondence to Zhuanping Qin .

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Qin, Z., Tao, X., Guo, T., Sun, W., Zhao, Z. (2024). Design and Development of a Lower Extremity Rehabilitation Training System for Myoelectric Assessment. In: Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2023. Lecture Notes in Electrical Engineering, vol 1033. Springer, Singapore. https://doi.org/10.1007/978-981-99-7502-0_59

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  • DOI: https://doi.org/10.1007/978-981-99-7502-0_59

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7555-6

  • Online ISBN: 978-981-99-7502-0

  • eBook Packages: EngineeringEngineering (R0)

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