Abstract
© 2025 Elsevier Ltd.Electroencephalography (EEG) enables the investigation of olfactory perception through neuronal electrical activity. Decoding dynamic oscillatory changes in sensory-cognitive processing is critical to understanding odor-induced brain responses. First, the EEG signals of almond were obtained and transformed into the frequency domain. Welch's method was implemented to extract power spectral density (PSD). Subsequently, the power spectral analysis of brain responses across different regions and frequency bands was investigated. Moreover, the machine learning approach was employed to explore the primary discriminative features. As a result, pronounced oscillatory activity was obtained in delta and alpha bands inducing distinct spatial-frequency responses of increased δ-power in left temporal region and β-power in parieto-occipital region. Critically, the β-band frequencies of 18 Hz and 25.5 Hz, and channels of FP2, FZ, and C3 were confirmed as key features contributing to olfactory analysis. This study provides valuable insights for olfactory perception and applications for quality assessment and storage monitoring.
NETL
NSTL
Elsevier