| Spinal cord injury (SCI) is a disease with high morbidity, high cost, high disability rate, and low age of onset [1], which can be caused by high-intensity injuries, such as traffic accidents, fall injuries, and violent injuries, as well as infections, tumors, and degenerative diseases of the spine, resulting in varying degrees of impairment of the information transmission pathways between the center and the body [2], and temporary or permanent changes in function below the level of injury, especially sensory and motor functions [3, 4]. Severe SCI can be a significant physical, psychological, and financial burden for patients and their families. During the recovery period of SCI, rehabilitation therapy plays an important role in it, such as the intervention of various treatment methods such as exercise therapy, physical factors, acupuncture, and orthoses, but these treatment effects have the disadvantages of limited effect, slow onset, and long curative effect, so the functional recovery of SCI patients has always been a difficult problem and challenge in the field of rehabilitation research [5].
In recent years, more and more emerging intelligent rehabilitation technologies have been applied in this field, and the rapid development and continuous innovation of the combination of neuroscience and engineering technology have provided more advanced and convenient means for the rehabilitation of SCI patients, such as non-invasive brain-computer interface (BCI), which has been gradually put into clinical use due to its high market acceptance, simple operation, safety and non-invasiveness, and low cost [6]. Although BCI technology is mostly combined with external devices (neuroprostheses and functional electrical stimulation) in the field of neuroscience [7], its current clinical application is still mainly combined with motor imagery (MI), and most patients can obtain higher accuracy in the BCI system, which is more beneficial for the functional recovery of patients with motor dysfunction [8].
In this study, BCI training was based on MI combined with visual and auditory stimulus input and feedback to treat a patient with hand dysfunction in cervical SCI, and the patient was driven by a rehabilitation robot to bend and extend the affected hand through MI during the treatment, in order to improve hand function. |