With the high incidence of neurological diseases such as stroke and mental illness, rehabilitation treatments for neurological disorders have received widespread attention. Electroencephalography (EEG) technology, despite its excellent temporal resolution, has historically been limited in application due to its insufficient spatial resolution, and is mainly confined to preoperative assessment, intraoperative monitoring, and epilepsy detection. However, traditional constraints of EEG technology are being overcome with the popularization of EEG technology with high-density over 64-lead, the application of innovative analysis techniques and the integration of multimodal techniques, which are significantly broadening its applications in clinical settings. These advancements have not only reinforced the irreplaceable role of EEG technology in neurorehabilitation assessment, but also expanded its therapeutic potential through its combined use with technologies such as transcranial magnetic stimulation, transcranial electrical stimulation and brain-computer interfaces. This article reviewed the applications, advancements, and future prospects of EEG technology in neurorehabilitation assessment and treatment. Advancements in technology and interdisciplinary collaboration are expected to drive new applications and innovations in EEG technology within the neurorehabilitation field, providing patients with more precise and personalized rehabilitation strategies.
Humans ; Electroencephalography/methods* ; Brain-Computer Interfaces ; Neurological Rehabilitation/methods* ; Transcranial Magnetic Stimulation ; Transcranial Direct Current Stimulation ; Nervous System Diseases/diagnosis* ; Epilepsy/diagnosis*

A novel robotic mirror therapy system was recently developed to provide proprioceptive stimulus to the hemiplegic arm during a mirror therapy. Validation of the robotic mirror therapy system was performed to confirm its synchronicity prior to the clinical study. The mean error angle range between the intact arm and the robot was 1.97 to 4.59 degrees. A 56-year-old male who had right middle cerebral artery infarction 11 months ago received the robotic mirror therapy for ten 30-minute sessions during 2 weeks. Clinical evaluation and functional magnetic resonance imaging (fMRI) studies were performed before and after the intervention. At the follow-up evaluation, the thumb finding test score improved from 2 to 1 for eye level and from 3 to 1 for overhead level. The Albert's test score on the left side improved from 6 to 11. Improvements were sustained at 2-month follow-up. The fMRI during the passive motion revealed a considerable increase in brain activity at the lower part of the right superior parietal lobule, suggesting the possibility of proprioception enhancement. The robotic mirror therapy system may serve as a useful treatment method for patients with supratentorial stroke to facilitate recovery of proprioceptive deficit and hemineglect.
Arm ; Brain ; Clinical Study ; Exoskeleton Device ; Follow-Up Studies ; Hemiplegia ; Humans ; Infarction, Middle Cerebral Artery ; Magnetic Resonance Imaging ; Male ; Methods ; Middle Aged ; Neurological Rehabilitation ; Parietal Lobe ; Pilot Projects* ; Proprioception* ; Stroke ; Thumb ; Upper Extremity*

For most of nonlinear systems, control strategy is complicated. The adaptive control methods based on the model identification can effectively improve the control precision and stability. According to the nonlinear and time-changeable characteristics of the wrist movement in the functional electrical stimulation, modeling and identification of wrist movement based on Hammerstein model were implemented. By using M sequence and invert-repeated M sequence as excitation signal, the wrist model is divided into the linear dynamic part and the nonlinear static part. The characteristics of nonlinear part being taken into consideration, an adaptive control method based on time-changeable characteristics of linear part is presented. This method simplifies the control strategy, and it is validated by the simulation experiment of FES.
Computer Simulation ; Electric Stimulation ; methods ; Female ; Humans ; Male ; Models, Neurological ; Movement ; Movement Disorders ; physiopathology ; rehabilitation ; Nonlinear Dynamics ; Recovery of Function ; Wrist Joint ; physiopathology