{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:27:12Z","timestamp":1747189632164,"version":"3.40.5"},"reference-count":17,"publisher":"World Scientific Pub Co Pte Ltd","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2021,9,15]]},"abstract":"<jats:p> Background: Muslim prayer (Namaz) is the most important obligatory religious duty in Islam that is regularly performed five times per day at specific prescribed times by Muslims. Due to the fact that change of body position affects brain activity, Namaz can be considered as a suitable model to assess the effect of quick changes of the body position on brain activity measured by electroencephalography (EEG). Methods: Forty Muslim participants performed a four-cycle Namaz while their brain activity was being recorded using a 14-channel EEG recorder. The brain connectivity (as defined by a mutual correlation between EEG channels in this study) in different frequency bands (delta, theta, alpha, beta, and gamma) was measured in various positions of Namaz including standing, bowing, prostration, and sitting. Results: The results indicated that the delta band demonstrates the most changes in cross-correlation between the recorded channels, and finally, the accuracy of 73.8% was obtained in the data classification. <\/jats:p>","DOI":"10.1142\/s0218001421540288","type":"journal-article","created":{"date-parts":[[2021,8,24]],"date-time":"2021-08-24T11:16:33Z","timestamp":1629803793000},"page":"2154028","source":"Crossref","is-referenced-by-count":2,"title":["Classification of Body Position During Muslim Prayer Using the Convolutional Neural Network"],"prefix":"10.1142","volume":"35","author":[{"given":"Vahid","family":"Sobhani","sequence":"first","affiliation":[{"name":"Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Science, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koorosh","family":"Izadi","sequence":"additional","affiliation":[{"name":"Neuroscience Research Center, Baqiyatallah University of Medical Science, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ehsan Manshadi","family":"Mokari","sequence":"additional","affiliation":[{"name":"Neuroscience Research Center, Baqiyatallah University of Medical Science, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2638-3463","authenticated-orcid":false,"given":"Boshra","family":"Hatef","sequence":"additional","affiliation":[{"name":"Neuroscience Research Center, Baqiyatallah University of Medical Science, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,8,23]]},"reference":[{"key":"S0218001421540288BIB001","doi-asserted-by":"publisher","DOI":"10.15252\/msb.20156651"},{"key":"S0218001421540288BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2010.12.034"},{"key":"S0218001421540288BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512699"},{"key":"S0218001421540288BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccc.2015.12.005"},{"key":"S0218001421540288BIB005","doi-asserted-by":"publisher","DOI":"10.1089\/acm.2013.0426"},{"volume-title":"Deep Learning","year":"2016","author":"Goodfellow I.","key":"S0218001421540288BIB006"},{"volume-title":"Aaron Courville Deep Learning","year":"2016","author":"Goodfellow I.","key":"S0218001421540288BIB007"},{"key":"S0218001421540288BIB008","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2013.6611018"},{"key":"S0218001421540288BIB009","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"S0218001421540288BIB010","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2018.10.008"},{"key":"S0218001421540288BIB011","doi-asserted-by":"publisher","DOI":"10.1007\/s11538-015-0094-4"},{"key":"S0218001421540288BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.09.041"},{"issue":"1","key":"S0218001421540288BIB013","first-page":"93","volume":"76","author":"Chamsi-Pasha M.","year":"2021","journal-title":"The Medical journal of Malaysia"},{"key":"S0218001421540288BIB014","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuropsychologia.2016.06.015"},{"key":"S0218001421540288BIB015","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2014.06.014"},{"key":"S0218001421540288BIB016","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-015-9447-8"},{"key":"S0218001421540288BIB017","doi-asserted-by":"publisher","DOI":"10.1109\/29.21701"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001421540288","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T10:17:58Z","timestamp":1632133078000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001421540288"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,23]]},"references-count":17,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2021,9,15]]}},"alternative-id":["10.1142\/S0218001421540288"],"URL":"https:\/\/doi.org\/10.1142\/s0218001421540288","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"type":"print","value":"0218-0014"},{"type":"electronic","value":"1793-6381"}],"subject":[],"published":{"date-parts":[[2021,8,23]]}}}