Year: 2014
Type: article
Study design: Clinical Trial
Abstract: BACKGROUND: This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. METHODS: EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. RESULTS: Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). CONCLUSION: Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies.
Authors: Asieh Ahani, Helane Wahbeh, Hooman Nezamfar, Meghan Miller, Deniz Erdogmus, Barry Oken
Institutions: Northeastern University, Oregon Health & Science University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,990
Awards: HCC-Small: RSVP IconCHAT - A Brain Computer Interface for Icon-based Communication, Advancing Physiological Signal Analysis for Mind-Body Research, CAREER: Signal Models, Channel Capacity, and Information Rate for Noninvasive Brain Interfaces, Mechanic pathways of mindfulness meditation in post-traumatic stress disorder., CPS: Medium: Collaborative Research: Holistic Design Methodology for Automated Implementation of Human-in-the-Loop Cyber-Physical Systems
OpenAlex ID: W2153257584