A Review on Algorithms for EEG-Based BCIs

Abstract

Many classes of electrophysiological activities of the brain are used in designing various types of brain-computer interfaces (BCIs). Those are discussed briefly in this section. Sensorimotor activity generally corresponds to the behavior of the brain rhythms (mu, beta, and gamma), movement-related potentials (MRPs), etc. Next, the classification of BCI based on various parameters has also been discussed. These parameters are the mode of signal acquisition, timing, and placement of sensors. Later in this section, algorithms that have been and with chances of being, used in BCI applications have been discussed in a detailed manner. The algorithms chosen for each stage of the signal processing have an equal role to play in resulting a better outcome. Therefore, the section emphasizes the algorithms for each such stage, separately. Choosing a perfect algorithm is very important to design an efficient classifier. This section provides important information about the algorithms concerned with BCI. Sensorimotor ActivitySensorimotor cortex is the source of mu rhythms (ranging from 8 to 12 Hz) and beta rhythms (ranging from 13 to 30 Hz). These are generated when a person is not involved in sensory or motor activities. They are most distinct in the frontal and parietal lobes of the brain and make changes in the mu and lower beta bands. Any voluntary movement in the subject increases the power in the brain rhythms or frequencies. This phenomenon is also known as event-related synchronization (ERS). The peak of an ERS occurs at a delay of 600 ms following the movement offset. Finally, gamma rhythm is a high-frequency rhythm in the electroencephalography (EEG). The amplitude of gamma rhythm increases upon the occurrence of a movement.Movement-related potentials (MRPs) usually have a maximum amplitude at the vertex with low-frequency potentials, which become more significant close to the movement. Sensorimotor activities other than the previously mentioned ones are not restricted to any particular band of frequencies or location in the brain. For example,