Literature DB >> 32340970

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.   

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.

Entities:  

Year:  2021        PMID: 32340970     DOI: 10.1109/JBHI.2020.2989747

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  2 in total

1.  An Algorithm for Time Prediction Signal Interference Detection Based on the LSTM-SVM Model.

Authors:  Ningbo Xiao; Zuxun Song
Journal:  Comput Intell Neurosci       Date:  2022-03-11

2.  An adaptive reflexive control strategy for walking assistance system based on functional electrical stimulation.

Authors:  Hongtao Dong; Jie Hou; Zhaoxi Song; Rui Xu; Lin Meng; Dong Ming
Journal:  Front Neurosci       Date:  2022-08-24       Impact factor: 5.152

  2 in total

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