{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,15]],"date-time":"2025-06-15T23:40:00Z","timestamp":1750030800858,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":12,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811039652"},{"type":"electronic","value":"9789811039669"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-981-10-3966-9_19","type":"book-chapter","created":{"date-parts":[[2017,3,2]],"date-time":"2017-03-02T14:22:08Z","timestamp":1488464528000},"page":"176-184","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Features Fusion Method for Sleep Stage Classification Using EEG and EMG"],"prefix":"10.1007","author":[{"given":"Tiantian","family":"Lv","sequence":"first","affiliation":[]},{"given":"Xinzui","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Qian","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,3,3]]},"reference":[{"key":"19_CR1","first-page":"121","volume-title":"Sleep Deprivation","author":"FP Neonates","year":"2004","unstructured":"Neonates, F.P., Kushida, C.A.: Sleep Deprivation, pp. 121\u2013150. Marcel Dekker, New York (2004)"},{"issue":"6","key":"19_CR2","first-page":"693","volume":"34","author":"Z Liu","year":"2015","unstructured":"Liu, Z., Zhang, H., Zhao, H.: Study on sleep staging algorithm based on EEG signals. Chin. J. Biomed. Eng. 34(6), 693\u2013700 (2015)","journal-title":"Chin. J. Biomed. Eng."},{"issue":"16","key":"19_CR3","first-page":"18","volume":"34","author":"H Xie","year":"2015","unstructured":"Xie, H., Shi, X.: Research on sleep staging based on discrete wavelet transform for electroencephalogram. Softw. Algorithms 34(16), 18\u201320 (2015)","journal-title":"Softw. Algorithms"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Estrada, E., Nazeran, H., Nava, P., Behbehani, K., Burk, J., Lucas, E.: Itakura distance: a useful similarity measure between EEG and EOG signals in computer-aided classification of sleep stages. In: Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, pp. 1\u20134, September 2005","DOI":"10.1109\/IEMBS.2005.1616636"},{"key":"19_CR5","unstructured":"Li, J., Chen, H., Ye, S.: A self-adaptive threshold method for automatic sleep stage classification using EOG and EMG. MATEC Web Conf. 22 (2015). Article no. 05023"},{"issue":"23","key":"19_CR6","doi-asserted-by":"publisher","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","volume":"101","author":"AL Goldberger","year":"2000","unstructured":"Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., et al.: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215\u2013e220 (2000)","journal-title":"Circulation"},{"key":"19_CR7","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.jneumeth.2015.01.022","volume":"250","author":"T Lajnef","year":"2015","unstructured":"Lajnef, T., Chaibi, S., Ruby, P., Aguera, P.E., Eichenlaub, J.B.: Learning machines and sleeping brains: automatic sleep stage classification using decision-tree multi-class support vector machines. J. Neurosci. Methods 250, 94\u2013105 (2015)","journal-title":"J. Neurosci. Methods"},{"key":"19_CR8","first-page":"69","volume":"30","author":"R Constable","year":"1994","unstructured":"Constable, R., Thornhill, R.J., Carpenter, D.R.: Time frequency analysis of the surface EMG during maximum height jumps under altered conditions. Biomed. Sci. Instrum. 30, 69\u201374 (1994)","journal-title":"Biomed. Sci. Instrum."},{"issue":"6","key":"19_CR9","first-page":"575","volume":"8","author":"H Wang","year":"2009","unstructured":"Wang, H.: The latest interpretation of analytical standard guide on the American Academy of sleep medicine sleep staging. Diagn. Theor. Pract. 8(6), 575\u2013578 (2009)","journal-title":"Diagn. Theor. Pract."},{"issue":"5","key":"19_CR10","first-page":"501","volume":"30","author":"H Weixing","year":"2009","unstructured":"Weixing, H., Xiaoping, C., Junting, S.: Sleep EEG staging based on sample entropy. J. Jiangsu Univ. 30(5), 501\u2013504 (2009)","journal-title":"J. Jiangsu Univ."},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Baudat, G., Anouar, F.: Kernel-based methods and function approximation. In: IJCNN 2001 International Joint Conference on proceedings of the Neural Networks, pp. 1244\u20131249 (2001)","DOI":"10.1109\/IJCNN.2001.939539"},{"issue":"11","key":"19_CR12","first-page":"3135","volume":"35","author":"J Run","year":"2015","unstructured":"Run, J., Luo, D., Luo, H.: Indoor and outdoor scene recognition algorithm based on support vector machine multi-classifier. J. Comput. Appl. 35(11), 3135\u20133138 (2015)","journal-title":"J. Comput. Appl."}],"container-title":["Communications in Computer and Information Science","Geo-Spatial Knowledge and Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-10-3966-9_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,15]],"date-time":"2025-06-15T23:16:34Z","timestamp":1750029394000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-10-3966-9_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9789811039652","9789811039669"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-981-10-3966-9_19","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"3 March 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"GRMSE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"grmse2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.grmse2016.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}