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.

中文翻译：

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使用功能性电刺激进行足下垂矫正的自适应刺激曲线调制：概念验证研究

功能性电刺激 (FES) 提供了一种有效的足下垂 (FD) 矫正方法。为了克服最先进方法中的冗余和盲目刺激问题，本研究提出了一种用于自适应肌电图 (EMG) 调制刺激配置文件的闭环方案。开发的方法检测步行过程中的实时角速度。它向长短期记忆 (LSTM) 神经网络提供反馈，用于预测同步胫前肌 (TA) EMG。根据预测，它会调节刺激强度，同时考虑到受试者特定的死区和电诱发激活的饱和度。所提出的方法在十名身体健全的参与者和六名 FD 受试者身上进行了测试，作为概念证明。实验结果表明，该方法可以成功诱导踝关节背屈，并产生类似于自然步态的激活模式，平均相关系数为0.9021。因此，所提出的方法有可能帮助患者恢复正常步态。