Combined EEG and EMG fatigue measurement framework with application to hybrid brain-computer interface

In recent years, the EEG-based brain-computer interface (BCI) has become one of the most promising areas of research in computer science and robotics. Many internationally renewned research teams combining engineers and doctors, experts in neuroscience are trying to develop useful applications and devices offering disabled people to lead a normal life. Useful BCIs for disabled people suffering from Cerebral palsy, Parkinson’s disease, Brain injury, Spinal cord injuries, Multiple sclerosis, Stroke, Post-polio syndrome should allow them to use all their existing brain and muscle abilities as control possibilities. In this paper we present a framework based on the mutimodal fusion approach of the user’s electromyographic (EMG) and electroencephalographic (EEG) activities in a so called “Hybrid-BCI” (hBCI). Although EEG BCI alone yields good performance as already proved in many research papers, it is outperformed by the fusion of EEG and EMG. We investigate the influence of muscular fatigue on the EMG performance. Such a framework will allow a more reliable control and adaptation of the hBCI if the user get exhausted and loses concentration during the rehabilitation process. We focus our research in aims of improving the lives of many upper limb disabled individuals through a combination of current BCI technologies with existing assistive medical systems.

• Agata Manolova
• Georgi Tsenov
• Violeta Lazarova
• Nikolay Neshov

IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 2016.

https://ieeexplore.ieee.org/document/7901569