THE ANALYSIS OF MOTOR IMAGERY AND SSVEPS FOR THE BCI APPLICATION

Many studies have shown that the electrical and magnetic fields generated during brain activities can produce certain signals. Some of these signals can be captured using electroencephalography, a detection tool involving mobile brainwave sensors whose use has matured and become affordable. The braincomputer interface (BCI) provides an alternative form of communication between the human and a system (computer or actuator) without any physical contact between them. There are many ways to evoke brain signals for translation into computer tasks, but the most popular are motor imagery and steady-state visual evoked potentials
(SSVEPs). In this research, an offline analysis of motor imagery and SSVEPs
based on BCI experiments that use electroencephalography (EEG) is reported. The results show that SSVEPs are more accurate and convenient
than motor imagery, with errors of 15 percent and 35 percent, respectively.