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sEMG bias-driven functional electrical stimulation system for upper-limb stroke rehabilitation

  • Yu Zhou
  • , Yinfeng Fang
  • , Kai Gui
  • , Kairu Li
  • , Dingguo Zhang
  • , Honghai Liu

    Research output: Contribution to journalArticlepeer-review

    1017 Downloads (Pure)

    Abstract

    It is evident that the dominant therapy of functional electrical stimulation (FES) for stroke rehabilitation suffers from heavy dependency on therapists experience and lack of feedback from patients status, which decrease the patients’ voluntary participation, reducing the rehabilitation efficacy. This paper proposes a closed loop FES system using surface electromyography (sEMG) bias feedback from bilateral arms for enhancing upper-limb stroke rehabilitation. This wireless portable system consists of sEMG data acquisition and FES modules, the former is used to measure and analyze the subject’s bilateral arm motion intention and neuromuscular states in terms of their sEMG, the latter of multi-channel FES output is controlled via the sEMG bias of the bilateral arms. The system has been evaluated with experiments proving that the system can achieve 39.9 dB signal-to-noise ratio (SNR) in the lab environment, outperforming existing similar systems. The results also show that voluntary and active participation can be effectively employed to achieve different FES intensity for FES-assisted hand motions, demonstrating the potential for active stroke rehabilitation.
    Original languageEnglish
    Pages (from-to)6812-6821
    JournalIEEE Sensors Journal
    Volume18
    Issue number16
    Early online date18 Jun 2018
    DOIs
    Publication statusPublished - 15 Aug 2018

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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