Change in physiological signals during mindfulness meditation

Asieh Ahani, Helana Wahbeh, Meghan Miller, Hooman Nezamfar, Deniz Erdogmus, Barry Oken

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. 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 and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.

Original languageEnglish (US)
Title of host publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
Pages1378-1381
Number of pages4
DOIs
StatePublished - 2013
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
CountryUnited States
CitySan Diego, CA
Period11/6/1311/8/13

Fingerprint

Classifiers
Spectrum analysis
Frequency bands
Medicine
Support vector machines
Signal processing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

Cite this

Ahani, A., Wahbeh, H., Miller, M., Nezamfar, H., Erdogmus, D., & Oken, B. (2013). Change in physiological signals during mindfulness meditation. In International IEEE/EMBS Conference on Neural Engineering, NER (pp. 1378-1381). [6696199] https://doi.org/10.1109/NER.2013.6696199

Change in physiological signals during mindfulness meditation. / Ahani, Asieh; Wahbeh, Helana; Miller, Meghan; Nezamfar, Hooman; Erdogmus, Deniz; Oken, Barry.

International IEEE/EMBS Conference on Neural Engineering, NER. 2013. p. 1378-1381 6696199.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ahani, A, Wahbeh, H, Miller, M, Nezamfar, H, Erdogmus, D & Oken, B 2013, Change in physiological signals during mindfulness meditation. in International IEEE/EMBS Conference on Neural Engineering, NER., 6696199, pp. 1378-1381, 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013, San Diego, CA, United States, 11/6/13. https://doi.org/10.1109/NER.2013.6696199
Ahani A, Wahbeh H, Miller M, Nezamfar H, Erdogmus D, Oken B. Change in physiological signals during mindfulness meditation. In International IEEE/EMBS Conference on Neural Engineering, NER. 2013. p. 1378-1381. 6696199 https://doi.org/10.1109/NER.2013.6696199
Ahani, Asieh ; Wahbeh, Helana ; Miller, Meghan ; Nezamfar, Hooman ; Erdogmus, Deniz ; Oken, Barry. / Change in physiological signals during mindfulness meditation. International IEEE/EMBS Conference on Neural Engineering, NER. 2013. pp. 1378-1381
@inproceedings{375df5a2efb14c65b657788c49b6c219,
title = "Change in physiological signals during mindfulness meditation",
abstract = "Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. 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 and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.",
author = "Asieh Ahani and Helana Wahbeh and Meghan Miller and Hooman Nezamfar and Deniz Erdogmus and Barry Oken",
year = "2013",
doi = "10.1109/NER.2013.6696199",
language = "English (US)",
isbn = "9781467319690",
pages = "1378--1381",
booktitle = "International IEEE/EMBS Conference on Neural Engineering, NER",

}

TY - GEN

T1 - Change in physiological signals during mindfulness meditation

AU - Ahani, Asieh

AU - Wahbeh, Helana

AU - Miller, Meghan

AU - Nezamfar, Hooman

AU - Erdogmus, Deniz

AU - Oken, Barry

PY - 2013

Y1 - 2013

N2 - Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. 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 and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.

AB - Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. 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 and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.

UR - http://www.scopus.com/inward/record.url?scp=84897713829&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897713829&partnerID=8YFLogxK

U2 - 10.1109/NER.2013.6696199

DO - 10.1109/NER.2013.6696199

M3 - Conference contribution

AN - SCOPUS:84897713829

SN - 9781467319690

SP - 1378

EP - 1381

BT - International IEEE/EMBS Conference on Neural Engineering, NER

ER -