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.
journal_name
IEEE J Biomed Health Informjournal_title
IEEE journal of biomedical and health informaticsauthors
Li Y,Yang X,Zhou Y,Chen J,Du M,Yang Ydoi
10.1109/JBHI.2020.2989747subject
Has Abstractpub_date
2021-01-01 00:00:00pages
59-68issue
1eissn
2168-2194issn
2168-2208journal_volume
25pub_type
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