Author: Asieh Ahani 1 Email: ahani@ece.neu.edu Helane Wahbeh 2 Email: wahbehh@ohsu.edu Hooman Nezamfar 1 Email: nezamfar@ece.neu.edu Meghan Miller 2 Email: millerme@ohsu.edu Deniz Erdogmus1 Email: erdogmus@ece.neu.edu Barry Oken 2,3∗ ∗ Corresponding author Email: oken@ohsu.edu
Affiliation: 1Cognitive Systems Laboratory, Northeastern University, Boston, MA, USA 2Department of Neurology, Oregon Health and Science University, Portland, OR, USA 3Departments of Behavioral Neuroscience and Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA
Conference/Journal: Journal of NeuroEngineering and Rehabilitation
Date published: 2014 May 14
Other:
Volume ID: 11 , Pages: 87 , Special Notes: doi:10.1186/1743-0003-11-87 , Word Count: 186
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.
article
http://www.jneuroengrehab.com/content/pdf/1743-0003-11-87.pdf