Investigation of Brain Computer Interface Based Exoskeleton in Rehabilitaion

Background of the study: The integration of Brain-Computer Interface (BCI) technology with exoskeletons has introduced novel solutions in the field of neurorehabilitation. BCI-based exoskeletons harness neural signals to control robotic limbs, offering enhanced motor restoration, improved patient engagement, and potential autonomy for individuals with disabilities.BCI-based exoskeletons offer a modern way by utilizing neural signals to control robotic devices, enhancing movement ability by promoting rehabilitation in patients with motor dysfunctions. This article will discuss recent advancements in BCI technology in context of exoskeletons, analyze the integration of BCI with exoskeletons. Methodology: A literature review was conducted using IEEE Xplore to identify original studies from 2018 to 2023 implementing BCI-exoskeleton systems for clinical populations. Inclusion criteria required studies to involve clinical populations and use BCI-exoskeletons for either upper or lower limb rehabilitation. Descriptive analysis and linear regression were applied to evaluate input signal types (EEG vs. EMG) and rehabilitation outcomes. Results: All selected studies involved stroke patients, predominantly using EEG signals. EEG-based systems showed a 67% greater chance of improvement compared to EMG, though the result was not statistically significant (p = 0.200.Key challenges identified include limited clinical trials, high cost, bulky design, system safety, and lack of pediatric applications Conclusion: BCI-integrated exoskeletons represent a promising advancement in rehabilitation, enabling personalized and neuroadaptive support for individuals with motor dysfunctions. However, clinical validation remains limited. outcomes in real-world settings.