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

• Published in: IEEE journal of biomedical and health informatics Vol. 25; no. 1; pp. 59 - 68
• Main Authors: Li, Yurong, Yang, Xu, Zhou, Yuezhu, Chen, Jun, Du, Min, Yang, Yuan
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Angular velocity; Ankle; Correlation coefficient; Correlation coefficients; Electrical stimulation; Electrical stimuli; Electromyography; Feet; Foot; foot drop; Functional electrical stimulation; Gait; Iron; Long short-term memory; Muscles; Neural networks; Predictions; Real-time systems; saturation value; State-of-the-art reviews; Stimulation; threshold value; tibialis anterior; Walking
• ISSN: 2168-2194; 2168-2208
• DOI: 10.1109/JBHI.2020.2989747

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.