Adaptive Stimulation Profiles Modulation for Foot Drop Correction Using Functional Electrical Stimulation: A Proof of Concept Study

Yurong Li, Xu Yang, Yuezhu Zhou, Jun Chen, Min Du, Yuan Yang

Research output: Contribution to journalArticlepeer-review

Abstract

Functional electrical stimulation (FES) provides an effective way for foot drop (FD) correction. To overcome the redundant and blind stimulation problems in the state-of-the-art methods, this study proposes a closed-loop scheme for an adaptive electromyography (EMG)-modulated stimulation profile. The developed method detects real-time angular velocity during walking. It provides feedbacks to a long short-term memory (LSTM) neural network for predicting synchronous tibialis anterior (TA) EMG. Based on the prediction, it modulates the stimulation intensity, taking into account of the subject-specific dead zone and saturation of the electrically evoked activation. The proposed method is tested on ten able-bodied participants and six FD subjects as proof of concept. The experimental results show that the proposed method can successfully induce the dorsiflexion of the ankle joint, and generate an activation pattern similar to a natural gait, with the mean Correlation Coefficient of 0.9021. Thus, the proposed method has the potential to help patients to retrieve normal gait.

Original languageEnglish (US)
Article number9076839
Pages (from-to)59-68
Number of pages10
JournalIEEE Journal of Biomedical and Health Informatics
Volume25
Issue number1
DOIs
StatePublished - Jan 2021
Externally publishedYes

Keywords

  • electromyography
  • foot drop
  • Functional electrical stimulation
  • saturation value
  • threshold value
  • tibialis anterior

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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