Abstract
ABSTRACT Relaxation, which means the absence of tension and stress, is important for health, as extended periods of tension may lead to illness. This study detects induced relaxation through Electroencephalography (EEG) for real-time monitoring of brain activity. The Multivariate Empirical Mode Decomposition with Dynamic Phase-Synchronized Hilbert-Huang Transform (MEMD-DPS-HHT) algorithm was utilized to extract dynamic brain wave patterns from EEG data of participants exposed to blended essential oil. Preprocessing included artifact removal using Independent Component Analysis (ICA), bandpass filtering within the 4-12 Hz range, and normalization. The EEG data underwent decomposition into five Intrinsic Mode Functions (IMFs) through the application of MEMD. The average frequency of IMF1 (8.56 Hz) and IMF2 (4.91 Hz) are within the designated frequency range. Dynamic phase synchronization and instantaneous frequency analysis employed adaptive time-frequency-energy representation. Analysis of phase synchronization across channels indicated a maximum coherence of 0.87. The dynamic Hilbert spectra and relaxation indices, pre- and post-stimulation, showed an average maximum of 0.16, aligning with paired t- test results (p ≥ 0.05), suggesting no significant difference in the Theta and Alpha bands (TA band) frequencies and stimulation. A two-way repeated measures ANOVA indicated p = 1, implying no significant effect of stimulation on the TA band. The results demonstrate the ability of MEMD-DPS-HHT to analyze cross-channel, multi-dimensional, dynamic EEG data associated with relaxation. The average relaxation index from this dataset was rather low, suggesting that the impact of this particular blended essential oil stimulation may differ among individuals. INDEX TERMS Relaxation, Blended Essential Oil, Electroencephalography, EEG, Multivariate Empirical Mode Decomposition, MEMD, Dynamic Phase-Synchronized, DPS, Hilbert-Huang Transform, HHT, Phase Coherence, Relaxation Index
Authors
Umsura, B., Srimaharaj, W., Sittiprapaporn, P., Bencheva, Suksathan, N. &., & R.C.A.R.
https://doi.org/10.1109/ACCESS.2025.3561142