A cost-effective BCI assisted technology framework for neurorehabilitation

Brain Computer Interface (BCI) controlled assistive robotic systems have been developed with increasing success with the aim to rehabilitate brain injured patients to increase independence and quality of life. While such systems may use surgically implanted sensors, non-invasive alternatives can be better suited due to ease of use, reduced cost, improvements in accuracy and reliability with the advancement of the technology and practicality of use. The consumer grade BCI devices often capable of integrating multiple types of signals, including Electroencephalogram (EEG) and Electromyogram (EMG), as well as basic motion-based signals, such as gyroscopic data.

This paper reports the development of a framework for rolling out cost-effective BCI driven assistive technology systems and details the implementation and evaluation of a prototype robotic system to determine the efficacy of the proposed framework. The results indicate that the first stage of the framework was effective in accuracy, safety, usability, portability, adaptability and personalisation.