Tempo-Spectral EEG Biomarkers for Odour Identification

Different odours evoke different activity in the brain. Among the non-invasive methods, electroencephalogram (EEG) is the most widely used mode to measure brain activity. While there has been significant work around EEG signal analysis, studies in the area of EEG with odour as stimuli is nascent. In this paper, we experiment and study different EEG biomarkers with an aim to understand which biomarker shows promise for odour identification. We show, on a widely used and publicly available data-set, through a series of experiments that it is possible to get a Subject Dependent (SD) odour classification accuracy of over 90%, using a set of tempo-spectral EEG biomarkers. We further experiment with Subject Independent (SI) odour classification, which has not been addressed and show that the performance drops to under 50% for SI odour classification.Clinical Relevance - The study shows that the same odour evoke different brain responses from the subject.