|Title:||A corticomuscular coherence (CMC)-electromyography (EMG)-based brain computer interface (BCI) for wrist-hand rehabilitation after stroke|
|Advisors:||Zheng, Yongping (BME)|
Hu, Xiaoling (BME)
|Subject:||Cerebrovascular disease -- Patients -- Rehabilitation|
Hand -- Wounds and injuries -- Patients -- Rehabilitation
Wrist -- Wounds and injuries -- Patients -- Rehabilitation
|Department:||Department of Biomedical Engineering|
|Pages:||xiv, 99 pages : color illustrations|
|Abstract:||Restoration of upper extremity function requires the repetitive, intensive physical practice of the paralyzed extremity with voluntary motor effort (VME) and minimized compensatory motions in close-to-normal muscular coordination after stroke. Currently, robot-assisted rehabilitation therapy has been widely used as a solution for repeated and intensive upper limb training. Electromyography (EMG) and brain computer interface (BCI) were introduced as the control methods for robotic devices to detect voluntary motor effort and avoid compensatory motions. However, most chronic stroke survivors sustain poorer distal joint function recovery than that of proximal joint, with the proximal compensations for the distal upper limb motions. Furthermore, 'learned non-use' occurs with the restriction on the possible recovery at the distal joints due to this muscle discoordination. Thus, the mechanism of the compensatory contraction of proximal muscles for distal joint motions should be further investigated. In this project, we first investigated the compensatory activities of the proximal upper limb among chronic stroke during the distal joints movements via corticomuscular coherence (CMC) and explored the corticomuscular coordination pattern. Based on the results, we then introduced CMC as the representation of the corticomuscular VME to a BCI system for wrist-hand function rehabilitation after stroke, with the purpose to reduce the proximal muscle compensatory contractions during the distal joint movements.|
The objectives of this project were as follows:
(1) To explore the corticomuscular coupling patterns in the paralyzed upper extremity and the mechanism of compensatory activation from the proximal muscles through CMC and EMG measurements when persons with chronic stroke execute motor tasks at the distal joints.
(2) To develop a novel CMC-EMG-based BCI for wrist-hand function rehabilitation after stroke and evaluate its feasibility and rehabilitation training effectiveness through a pilot clinical trial.
This project was divided into two parts to achieve these objectives:
In the first part, 14 chronic stroke survivors were recruited as the experimental group to investigate the mechanism of compensatory activation of proximal muscle, with 10 age-matched unimpaired participants as control group. EMG signals across the upper limb, including extensor digitorum (ED), flexor digitorum (FD), triceps brachii (TRI), and biceps brachii (BIC), and electroencephalogram (EEG) from the sensorimotor area were recorded. The proximal muscle compensatory contraction for distal joint movements was evaluated by CMC, EMG activation level and co-contraction index (CI). The stroke subjects showed significant differences in peak TRI and BIC CMC (P<0.01). No significant inter-or intra-group difference was observed in peak CMC during finger flexion. Higher EMG activation levels in TRI and BIC muscles, and higher CI in the muscle pairs involving the proximal muscles (TRI and BIC) were observed during both finger extension/flexion tasks in stroke group than those in control group (P<0.05). These results indicated that the proximal muscular compensation originated from the cortical level.
In the second part, a novel CMC-EMG-based robotic BCI was developed for wrist-hand rehabilitation. This system integrated the CMC and EMG activation levels to evaluate the central-and-peripheral VME, during the assistance of this system in wrist-hand motion practice. Once the desired VME levels were detected, a neuromuscular-electrical-stimulation-assisted robot of the wrist-hand joint would be triggered to assist the target motions, i.e., wrist-hand extension or flexion. A single-group pilot clinical trial with 20 sessions was conducted to evaluate its feasibility and rehabilitation training effectiveness for chronic stroke. During the multiple training sessions, there was a significant increase in the success rate of the system triggering by all stroke participants (P<0.05), which suggested the feasibility of using the system to assist the desired wrist-hand movements. There was a significant improvement (P<0.05) post-training in the wrist-hand fine motion control measured by clinical scores and CMC, EMG activation levels and CIs in the related muscles of the upper limb. It demonstrated that this CMCEMG BCI was effective for fine motor function recovery with reduced compensatory motions from the proximal joints in the upper limb.
In conclusion, the corticomuscular coordination of proximal muscle's compensatory activations for the distal joint motions in the upper extremity was cortically derived in chronic strokes. A novel CMC-EMG-driven BCI system was developed for post-stroke wrist-hand rehabilitation. This CMC-EMG-based robotic BCI can feasibly assist in wrist-hand rehabilitation and could improve the wrist-hand function with reduced proximal compensation.
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