{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:22:22Z","timestamp":1760955742643,"version":"3.37.3"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,9,22]],"date-time":"2017-09-22T00:00:00Z","timestamp":1506038400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["51405381"],"award-info":[{"award-number":["51405381"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Scientific and Technological Project of Shaanxi Province","award":["2016GY-040"],"award-info":[{"award-number":["2016GY-040"]}]},{"name":"Leading Initiative for Excellent Young Researcher (LEADER) of Ministry of Education, Culture, Sports, Science and Technology-Japan","award":["16809746"],"award-info":[{"award-number":["16809746"]}]},{"name":"Grant in Aid for Scientific Research of JSPS","award":["17K14694"],"award-info":[{"award-number":["17K14694"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mobile Netw Appl"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s11036-017-0935-5","type":"journal-article","created":{"date-parts":[[2017,9,22]],"date-time":"2017-09-22T10:13:47Z","timestamp":1506075227000},"page":"336-343","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Anxiety Level Detection Using BCI of Miner\u2019s Smart Helmet"],"prefix":"10.1007","volume":"23","author":[{"given":"Mei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Songzhi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yuanjie","family":"Lv","sequence":"additional","affiliation":[]},{"given":"Huimin","family":"Lu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,22]]},"reference":[{"key":"935_CR1","unstructured":"Huimin L, Yujie L, Min C, Hyoungseop K, Seiichi S (2017) Brain intelligence: go beyond artificial intelligence. Mobile Networks and Application (arXiv:1706.01040):1\u201315"},{"key":"935_CR2","volume-title":"International affective picture system(IAPS): technical manual and affective ratings","author":"J Langp","year":"1997","unstructured":"Langp J, Bradleym M, Cuthbertb H (1997) International affective picture system(IAPS): technical manual and affective ratings. The Center for Research in Psychophysiology, University of Florida, Gainesville"},{"issue":"9","key":"935_CR3","doi-asserted-by":"crossref","first-page":"11449","DOI":"10.1007\/s11042-016-4203-7","volume":"76","author":"D Shin","year":"2017","unstructured":"Shin D, Shin D, Shin D (2017) Development of emotion recognition interface using complex EEG\/ECG bio-signal for interactive contents. Multimesia Tools and Applications 76(9):11449\u201311470","journal-title":"Multimesia Tools and Applications"},{"key":"935_CR4","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/j.compeleceng.2016.04.009","volume":"53","author":"MM Raja","year":"2016","unstructured":"Raja MM, Hyo JL (2016) A novel feature extraction method based on late positive potential for emotion recognition in human brain signal patterns. Comput Electr Eng 53:444\u2013457","journal-title":"Comput Electr Eng"},{"key":"935_CR5","unstructured":"Hong-mei Z (2011) Feature extraction and analysis of visual evoked EEG in emotion images. Master\u2019s Degree Thesis, Tianjin University, pp 22\u201334"},{"issue":"4","key":"935_CR6","first-page":"595","volume":"31","author":"N Dan","year":"2012","unstructured":"Dan N, Xiaowei W, Ruonan D et al (2012) Survey of emotion recognition based on EEG. Chin J Biomed Eng 31(4):595\u2013606","journal-title":"Chin J Biomed Eng"},{"key":"935_CR7","unstructured":"Khalili Z, Moradi MH (2015) Emotion recognition system using brain and peripheral signals: using correlation dimension to improve the results of EEG. International Joint Conference on Neural Networks. IEEE Press 1920-1924"},{"key":"935_CR8","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.procs.2016.04.073","volume":"84","author":"K Jyotish","year":"2016","unstructured":"Jyotish K, Jyoti K (2016) Affective modelling of users in HCI using EEG. Procedia Computer Science 84:107\u2013114","journal-title":"Procedia Computer Science"},{"issue":"8","key":"935_CR9","doi-asserted-by":"crossref","first-page":"604","DOI":"10.4236\/jbise.2014.78061","volume":"7","author":"V Stefano","year":"2014","unstructured":"Stefano V, Tanvir I, Peter J, Andrzej C (2014) Individual classification of emotions using EEG. J Biomed Sci Eng 7(8):604\u2013620","journal-title":"J Biomed Sci Eng"},{"key":"935_CR10","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1007\/978-3-642-12197-5_83","volume":"28","author":"G Zouridakis","year":"2009","unstructured":"Zouridakis G, Patidar U, Padhye NS et al (2009) Spectral power of brain activity associated with emotion -a pilot MEG study. IFMBE Proc 28:354\u2013357","journal-title":"IFMBE Proc"},{"key":"935_CR11","first-page":"262","volume":"2008","author":"M Murugappan","year":"2007","unstructured":"Murugappan M, Rizon M, Nagarajan R et al (2007) Time-frequency analysis of EEG signals for human emotion detection. 4th Kuala Lumpur International Conference on Biomedical Engineering 2008:262\u2013265","journal-title":"4th Kuala Lumpur International Conference on Biomedical Engineering"},{"issue":"8","key":"935_CR12","first-page":"680","volume":"28","author":"Z Zhifei","year":"2015","unstructured":"Zhifei Z, Duoqian M, Hongyun Z (2015) Multi label emotion classification based on decision rough set. Pattern Recognit Artif Intell 28(8):680\u2013685","journal-title":"Pattern Recognit Artif Intell"},{"issue":"2","key":"935_CR13","first-page":"182","volume":"32","author":"HQ Peng","year":"2013","unstructured":"Peng HQ (2013) The wavelet packet transformation and nonlinear analysis of EEG signals are used to determine the state of mental fatigue. Vibration and Shock 32(2):182\u2013188","journal-title":"Vibration and Shock"},{"key":"935_CR14","first-page":"224","volume":"11","author":"Z Vadim","year":"2016","unstructured":"Vadim Z, Han Y, Masaya M, Raquel P, Kymberly DY, Matthew TE, Jerzy B (2016) Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression. Neuro Image Clinical 11:224\u2013238","journal-title":"Neuro Image Clinical"},{"key":"935_CR15","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.bspc.2017.03.016","volume":"36","author":"ZB Siao","year":"2017","unstructured":"Siao ZB, Khairunizam W, Murugappan M, Norlinah MI, Yuvaraj R, Khairiyah M (2017) Implementation of wavelet packet transform and non linear analysis for emotion classification in stroke patient using brain signals. Biomed Signal Process Control 36:102\u2013112","journal-title":"Biomed Signal Process Control"},{"issue":"2016","key":"935_CR16","first-page":"734","volume":"94","author":"W Mei","year":"2016","unstructured":"Mei W, Wen-Yuan C, Xiangdan L (2016) Hand gesture recognition using valley circle feature and Hu\u2019s moments technique for robot movement control. Measurement 94(2016):734\u2013744","journal-title":"Measurement"},{"issue":"3","key":"935_CR17","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.neucli.2017.01.009","volume":"47","author":"VB Andrey","year":"2017","unstructured":"Andrey VB, Gennady GK, Alexander NS (2017) Depression and implicit emotion processing: an EEG study. Neurophysiologie Clinique\/Clinical Neurophysiology 47(3):225\u2013230","journal-title":"Neurophysiologie Clinique\/Clinical Neurophysiology"},{"issue":"2017","key":"935_CR18","first-page":"502","volume":"58","author":"W Mei","year":"2016","unstructured":"Mei W, Lin G, Wen-Yuan C (2016) Blink detection using Adaboost and contour circle for fatigue recognition. Comput Electr Eng 58(2017):502\u2013512","journal-title":"Comput Electr Eng"},{"issue":"1","key":"935_CR19","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.compeleceng.2013.10.016","volume":"40","author":"S Seiichi","year":"2014","unstructured":"Seiichi S, Huimin L (2014) Underwater image dehazing using joint trilateral filter. Comput Electr Eng 40(1):41\u201350","journal-title":"Comput Electr Eng"},{"issue":"5","key":"935_CR20","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1016\/j.camwa.2012.03.017","volume":"64","author":"L Huimin","year":"2012","unstructured":"Huimin L, Lifeng Z, Seiichi S (2012) Maximum local energy: an effective approach for image fusion in beyond wavelet transform domain. Computers & Mathematics with Applications 64(5):996\u20131003","journal-title":"Computers & Mathematics with Applications"}],"container-title":["Mobile Networks and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11036-017-0935-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-017-0935-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11036-017-0935-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,4,24]],"date-time":"2018-04-24T05:04:25Z","timestamp":1524546265000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11036-017-0935-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,22]]},"references-count":20,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["935"],"URL":"https:\/\/doi.org\/10.1007\/s11036-017-0935-5","relation":{},"ISSN":["1383-469X","1572-8153"],"issn-type":[{"type":"print","value":"1383-469X"},{"type":"electronic","value":"1572-8153"}],"subject":[],"published":{"date-parts":[[2017,9,22]]}}}