Gabor Wavelet based Denoising of EEG Signals for Human Mindfulness Assessment under the exposure to Vedic Chanting
Veera Raghava Swamy Nalluri, V. J. K. Kishor Sonti
Research Square July 15, 2025 preprint DOI: 10.21203/rs.3.rs-7107299/v1 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | EEG signal analysis study |
|---|---|
| Population | People of various age groups whose EEG signals were collected |
| Interventions | OM chanting popular music |
| Topics | Meditation |
| Key points | Proposes a Gabor Transform-based time-frequency method with improved wavelet de-noising, including a mother wavelet selection approach, to analyze EEG during Vedic chanting (Rudra Suktham, OM chanting, Gayatri mantra) and popular music, with the aim of examining effects on brain neural activity and estimating a relaxing factor. The abstract reports no numerical outcomes. |
Abstract
Abstract This research presents improved time-frequency analysis of Sanathan Vedic Chanting (SVC) augmentation of human cerebral activity. Listening to music can help manage negative emotions, and since ancient times, there has been a significant improvement in brain neuronal activity. This article examines the effects of Vedic chanting on brain neural activity and relaxing factor estimation, in addition to popular music. During Vedic chanting, the spectrum is estimated at different points in time using Gabor Transforms (GT), and wavelet de-nosing is effectively employed to eliminate undesired high frequencies. By utilising an efficient mother wavelet selection approach during the de-noising phase, the noise removal procedure in the proposed work is significantly enhanced. Among the usual OM chanting and Gayatri mantra, Rudra Suktham from Yajurveda is investigated using the proposed GT analysis, and EEG signals are collected from various age groups. The signals are processed using proposed algorithm in MATLAB programming.