Welcome to the upgraded BRAC University Institutional Repository. We are currently organizing collections after a recent system upgrade. Homepage category counters may temporarily show lower numbers while syncing, but over 27,000 repository items remain safe and accessible. Please use the search bar to find theses, scholarly outputs, and institutional documents.

Applying tDCS over the dominant Hemisphere to observe event-related Desynchronization

Citation

Abstract

Although keeping us alive is arguably the most important function of the human brain, the human brain is responsible for a host of functions|including processing of environmental stimuli. Electroencephalography (EEG) is a psychophysiological technique used to measure electro-cortical activity in the brain. It is a noninvasive technique that provides a direct measure of the brain's electrical activity through placement of electrodes on the scalp which is quite precise and instantaneous. A set of probes or electrodes are placed on the scalp which receive EEG signals or brain waves. Using EEG signals we may analyze the mechanisms behind language, cognition, sensory functions, and brain oscillations. After gathering the eeg signals, it can be used as a neurofeedback - a process by which eeg signals are again applied to the brain with the same electrodes. By applying neurofeedback of some speci c pattern or feature we can enhance those features and reduce the other features. Transcarnial Direct Current Stimulation (tDCs) is also another non-invasive method of neuromodulation which is used to constatly apply a small amount of electric current on the head with the use of electrodes. With adequate amount of training with neurofeedback, tdcs individuals may learn to control their own brain waves and thus changing their state of self at will. We have initiated a system where we use EEG-based neurofeedback and tDCs on the left hemisphere of the brain and observe Event-related desynchronization occuring on the right hemisphere. After applying ve-fold cross validation method of classi cation we acquired an accuracy of 86.67% for anodal stimulation and 88.33% for cathodal stimulation.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 33-37).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Publisher Link

Type

Thesis