Digital Repository

Thought identification through visual stimuli presentation from a commercially available EEG device

Show simple item record

dc.contributor.author Gunawardhana, M. P. A. V.
dc.contributor.author Jayatissa, C. A. N. W. K.
dc.contributor.author Seneviratne, J. A.
dc.date.accessioned 2022-10-31T06:16:02Z
dc.date.available 2022-10-31T06:16:02Z
dc.date.issued 2021
dc.identifier.citation Gunawardhana M. P. A. V.; Jayatissa C. A. N. W. K.; Seneviratne J. A. (2021), Thought identification through visual stimuli presentation from a commercially available EEG device, International Research Conference on Smart Computing and Systems Engineering (SCSE 2021), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. 53-58. en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/25354
dc.description.abstract Thought identification has been the ultimate goal of brain-computer interface systems. However, due to the complex nature of brain signals, classification is difficult. But recent developments in deep learning have made the classification of multivariate time series data relatively easy. Studies have been carried out in the recent past to classify thoughts based on signals from medical-grade EEG devices. This study explores the possibility of thought identification using a commercially available EEG device using deep learning techniques. The crucial part of any EEG experiment is contamination-free data collection. Keeping the subject’s mind concentrated only in the decided state is important, yet challenging. To address this issue, we have developed a graphical user interface (GUI) based program that allows stimulus controlling and data recording. With the use of the low-cost commercially available EEG device, accuracies up to 89% were achieved for the classification of high contrast signals. However, tests on complex thought identification did not produce statistically significant results over the chance accuracy. en_US
dc.publisher Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka en_US
dc.subject brain-computer-interface, classification, EEG, signal processing en_US
dc.title Thought identification through visual stimuli presentation from a commercially available EEG device en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Digital Repository


Browse

My Account