Current Practices in Electroencephalogram- Based Brain-Computer Interfaces

Abstract

Electroencephalogram (EEG) is the electrical activity of the brain recorded by electrodes placed on the scalp. EEG signals are generally investigated for the diagnosis of mental conditions such as epilepsy, memory impairments, and sleep disorders. In recent years there has been another application using EEG: for brain-computer interface (BCI) designs (Vaughan & Wolpaw, 2006). EEG-based BCI designs are very useful for hands-off device control and communication as they use the electrical activity of the brain to interface with the external environment, therefore circumventing the use of peripheral muscles and limbs. Some current applications of BCIs in communication systems are for paralyzed individuals to communicate with their surroundings through character/menu selection and in device control such as wheelchair movement, prosthetics control, and flight and rehabilitative (assistive) technologies. For the general public, some of the possible applications are hands-off menu selection, flight/space control, and virtual reality (entertainment). BCI has also been applied in biometrics (Palaniappan & Mandic, 2007).

The Temporal Evolution of Coarse Location Coding of Objects: Evidence for Feedback

“…In the past, classification methods have been applied predominantly to fMRI and neurophysiological data in cognitive neuroscience and also in the brain-computer interface literature, where the goal is to classify scalp electrical patterns to signal a choice, without a behavioral response from the observer (e.g., Friedrich, Scherer, & Neuper, 2012;Green & Kalaska, 2011;Mak et al, 2011;Palaniappan, Syan, & Paramesran, 2009;Mensh, Werfel, & Seung, 2004). This technique has been rarely applied to electrophysiological measures such as EEG and MEG to study the temporal evolution of cognitive processes underlying perception.…”

Hidden Markov model and support vector machine based decoding of finger movements using electrocorticography

“…Brain-Computer-Interface (BCI) oriented research has a principle goal of aiding disabled people suffering from severe motor impairments (Hoffmann et al, 2007; Palaniappan et al, 2009). The majority of research on BCI has been based on EEG data and restricted to simple experimental tasks using a small set of commands.…”

A Brief Review of Brain Signal Monitoring Technologies for BCI Applications: Challenges and Prospects

“…Brain computer interface (BCI) which performs four distinct tasks: translating neurological input signals into electrical signals, extracting features from the signals, deriving meaningful information, and aggregating knowledge for useful purposes [7]. Even though early work on brain activity recording was performed in '40s before pacemaker or defibrillators were developed, recent advancements in low-power, wearable embedded systems technology and cyberphysical systems (CPS) have demonstrated the promise of real-time brain activity monitoring for patient centric diagnostics, therapy, and even preventative, proactive monitoring for well-beings [8][9][10][11].…”