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About 50% of stroke patients are unable to live independently because of residual disability. Brain-computer interface (BCI) is based on closed-loop theory, which facilitates neurological remodeling by establishing a bridge between central and peripheral connections. Studies have confirmed that BCI real-time neurofeedback training system based on motor imagery alone can effectively improve patients' motor function. So, is the benefit greater if motor imagery is combined with motor execution? Current conclusions are mixed. In addition, previous studies and our preliminary study found that prefrontal Fp1 and Fp2 areas play an important role in motor recovery after stroke, and they are involved in motor imagery, motor execution, attention and other behavioral processes. Therefore, we designed a BCI training system based on motor imagery and motor execution with prefrontal electroencephalogram (EEG) signals as the modulatory target. This was a randomized placebo-controlled double-blinded clinical trial. Patients in the test group performed BCI-controlled upper extremity motor imagery + upper extremity pedaling training. The control group had the same equipment and training scenario, and patients were also asked to imagine the upper extremity pedaling movement with effort, and patients also wore EEG caps, but the EEG signals were only recorded without controlling the pedaling equipment. After 3 weeks of treatment, we observed the changes of motor and cognitive functions as well as fNIRS-related brain network characteristics in both groups.
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40 participants in 2 patient groups
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Ziwen Yuan, MD
Data sourced from clinicaltrials.gov
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