Person identification from EEG using various machine learning techniques with inter-hemispheric amplitude ratio

• Published in: PloS one Vol. 15; no. 9; p. e0238872
• Main Authors: Jayarathne, Isuru, Cohen, Michael, Amarakeerthi, Senaka
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 11.09.2020; Public Library of Science (PLoS)
• Subjects: Access control; Accuracy; Algorithms; Amplitudes; Asymmetry; Biology and Life Sciences; Biometrics; Classification; Complexity; Computer and Information Sciences; Discriminant analysis; EEG; Electrodes; Electroencephalography; Embedded systems; Event-related potentials; Experiments; Feature extraction; Identification (Physical); Identification systems; K nearest neighbour classification tree analysis; K-nearest neighbors algorithm; Learning algorithms; Machine learning; Medicine and Health Sciences; Methods; Physical Sciences; Research and Analysis Methods; Researchers; Signal processing; Stimulation; Support vector machines; Visual stimuli; Sri Lanka; Japan
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0238872

Association between electroencephalography (EEG) and individually personal information is being explored by the scientific community. Though person identification using EEG is an attraction among researchers, the complexity of sensing limits using such technologies in real-world applications. In thi...