EEG-Based Detection of Induced Relaxation
Bunyarat Umsura; Wanus Srimaharaj; Phakkharawat Sittiprapaporn; Nina Bencheva; Ratchuporn Suksathan; Roungsan Chaisricharoen · 2025 · IEEE Access
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Relaxation, which refers to the absence of tension and stress, is important for health because extended periods of tension may lead to illness. This study detected induced relaxation through electroencephalography (EEG) for the 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 the EEG data of participants exposed to the blended essential oils. Preprocessing included artifact removal using independent component analysis (IC
Abstract by Bunyarat Umsura; Wanus Srimaharaj; Phakkharawat Sittiprapaporn; Nina Bencheva; Ratchuporn Suksathan; Roungsan Chaisricharoen, IEEE Access (2025) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.1109/access.2025.3561142