Closed‐Loop Wearable Device Network of Intrinsically‐Controlled, Bilateral Coordinated Functional Electrical Stimulation for Stroke

Author:

Xu Shuxing123,Li Chengyu13,Wei Conghui4,Kang Xinfang4,Shu Sheng13,Liu Guanlin2,Xu Zijie13,Han Mengdi5,Luo Jun4,Tang Wei136ORCID

Affiliation:

1. Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 101400 China

2. Center on Nanoenergy Research School of Physical Science & Technology Guangxi University Nanning 530004 China

3. School of Nanoscience and Technology University of Chinese Academy of Sciences Beijing 100049 China

4. Rehabilitation Medicine Department The Second Affiliated Hospital of Nanchang University Nanchang City 330006 P. R. China

5. Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China

6. Institute of Applied Nanotechnology Jiaxing Zhejiang 314031 China

Abstract

AbstractInnovative functional electrical stimulation has demonstrated effectiveness in enhancing daily walking and rehabilitating stroke patients with foot drop. However, its lack of precision in stimulating timing, individual adaptivity, and bilateral symmetry, resulted in diminished clinical efficacy. Therefore, a closed‐loop wearable device network of intrinsically controlled functional electrical stimulation (CI‐FES) system is proposed, which utilizes the personal surface myoelectricity, derived from the intrinsic neuro signal, as the switch to activate/deactivate the stimulation on the affected side. Simultaneously, it decodes the myoelectricity signal of the patient's healthy side to adjust the stimulation intensity, forming an intrinsically controlled loop with the inertial measurement units. With CI‐FES assistance, patients’ walking ability significantly improved, evidenced by the shift in ankle joint angle mean and variance from 105.53° and 28.84 to 102.81° and 17.71, and the oxyhemoglobin concentration tested by the functional near‐infrared spectroscopy. In long‐term CI‐FES‐assisted clinical testing, the discriminability in machine learning classification between patients and healthy individuals gradually decreased from 100% to 92.5%, suggesting a remarkable recovery tendency, further substantiated by performance on the functional movement scales. The developed CI‐FES system is crucial for contralateral‐hemiplegic stroke recovery, paving the way for future closed‐loop stimulation systems in stroke rehabilitation is anticipated.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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