{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:49:08Z","timestamp":1772556548394,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2014,12,24]],"date-time":"2014-12-24T00:00:00Z","timestamp":1419379200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2015,7]]},"DOI":"10.1007\/s00521-014-1802-y","type":"journal-article","created":{"date-parts":[[2014,12,23]],"date-time":"2014-12-23T05:47:44Z","timestamp":1419313664000},"page":"1193-1202","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["EEG data classification using wavelet features selected by Wilcoxon statistics"],"prefix":"10.1007","volume":"26","author":[{"given":"Thanh","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abbas","family":"Khosravi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Douglas","family":"Creighton","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saeid","family":"Nahavandi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,12,24]]},"reference":[{"issue":"3","key":"1802_CR1","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.1016\/j.eswa.2010.07.145","volume":"38","author":"M Sabeti","year":"2011","unstructured":"Sabeti M, Katebi SD, Boostani R, Price GW (2011) A new approach for EEG signal classification of schizophrenic and control participants. Expert Syst Appl 38(3):2063\u20132071","journal-title":"Expert Syst Appl"},{"issue":"3","key":"1802_CR2","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1109\/TBME.2010.2093133","volume":"58","author":"C Vidaurre","year":"2011","unstructured":"Vidaurre C, Kawanabe M, von Bunau P, Blankertz B, Muller KR (2011) Toward unsupervised adaptation of LDA for brain\u2013computer interfaces. IEEE Trans Biomed Eng 58(3):587\u2013597","journal-title":"IEEE Trans Biomed Eng"},{"issue":"8","key":"1802_CR3","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1007\/s00521-010-0481-6","volume":"20","author":"Y Li","year":"2011","unstructured":"Li Y, Koike Y (2011) A real-time BCI with a small number of channels based on CSP. Neural Comput Appl 20(8):1187\u20131192","journal-title":"Neural Comput Appl"},{"issue":"9","key":"1802_CR4","doi-asserted-by":"crossref","first-page":"e74433","DOI":"10.1371\/journal.pone.0074433","volume":"8","author":"R Zhang","year":"2013","unstructured":"Zhang R, Xu P, Guo L, Zhang Y, Li P, Yao D (2013) Z-score linear discriminant analysis for EEG based brain\u2013computer interfaces. PLoS ONE 8(9):e74433","journal-title":"PLoS ONE"},{"issue":"3","key":"1802_CR5","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.cmpb.2012.10.008","volume":"109","author":"B Hosseinifard","year":"2013","unstructured":"Hosseinifard B, Moradi MH, Rostami R (2013) Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal. Comput Methods Programs Biomed 109(3):339\u2013345","journal-title":"Comput Methods Programs Biomed"},{"issue":"3","key":"1802_CR6","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1109\/JBHI.2013.2289741","volume":"18","author":"P Prasad","year":"2014","unstructured":"Prasad P, Halahalli H, John J, Majumdar K (2014) Single-trial EEG classification using logistic regression based on ensemble synchronization. IEEE J Biomed Health Inform 18(3):2014","journal-title":"IEEE J Biomed Health Inform"},{"issue":"3","key":"1802_CR7","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1016\/j.cmpb.2013.12.020","volume":"113","author":"Y Li","year":"2014","unstructured":"Li Y, Wen PP (2014) Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain computer interface. Comput Methods Programs Biomed 113(3):767\u2013780","journal-title":"Comput Methods Programs Biomed"},{"issue":"11","key":"1802_CR8","doi-asserted-by":"crossref","first-page":"14314","DOI":"10.1016\/j.eswa.2011.04.222","volume":"38","author":"D Wang","year":"2011","unstructured":"Wang D, Miao D, Xie C (2011) Best basis-based wavelet packet entropy feature extraction and hierarchical EEG classification for epileptic detection. Expert Syst Appl 38(11):14314\u201314320","journal-title":"Expert Syst Appl"},{"issue":"8","key":"1802_CR9","doi-asserted-by":"crossref","first-page":"10425","DOI":"10.1016\/j.eswa.2011.02.118","volume":"38","author":"L Guo","year":"2011","unstructured":"Guo L, Rivero D, Dorado J, Munteanu CR, Pazos A (2011) Automatic feature extraction using genetic programming: an application to epileptic EEG classification. Expert Syst Appl 38(8):10425\u201310436","journal-title":"Expert Syst Appl"},{"issue":"4","key":"1802_CR10","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.bspc.2011.07.007","volume":"7","author":"UR Acharya","year":"2012","unstructured":"Acharya UR, Molinari F, Sree SV, Chattopadhyay S, Ng KH, Suri JS (2012) Automated diagnosis of epileptic EEG using entropies. Biomed Signal Process Control 7(4):401\u2013408","journal-title":"Biomed Signal Process Control"},{"issue":"2","key":"1802_CR11","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1109\/TNSRE.2003.814441","volume":"11","author":"D Garrett","year":"2003","unstructured":"Garrett D, Peterson DA, Anderson CW, Thaut MH (2003) Comparison of linear, nonlinear, and feature selection methods for EEG signal classification. IEEE Trans Neural Syst Rehabil Eng 11(2):141\u2013144","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"5","key":"1802_CR12","doi-asserted-by":"crossref","first-page":"2537","DOI":"10.1016\/j.asoc.2012.11.032","volume":"13","author":"M Vatankhah","year":"2013","unstructured":"Vatankhah M, Asadpour V, Fazel-Rezai R (2013) Perceptual pain classification using ANFIS adapted RBF kernel support vector machine for therapeutic usage. Appl Soft Comput 13(5):2537\u20132546","journal-title":"Appl Soft Comput"},{"key":"1802_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.bspc.2013.08.006","volume":"9","author":"V Joshi","year":"2014","unstructured":"Joshi V, Pachori RB, Vijesh A (2014) Classification of ictal and seizure-free EEG signals using fractional linear prediction. Biomed Signal Process Control 9:1\u20135","journal-title":"Biomed Signal Process Control"},{"issue":"2","key":"1802_CR14","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.cmpb.2004.10.009","volume":"78","author":"A Subasi","year":"2005","unstructured":"Subasi A, Er\u00e7elebi E (2005) Classification of EEG signals using neural network and logistic regression. Comput Methods Programs Biomed 78(2):87\u201399","journal-title":"Comput Methods Programs Biomed"},{"issue":"6","key":"1802_CR15","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1016\/j.measurement.2007.07.007","volume":"41","author":"W Ting","year":"2008","unstructured":"Ting W, Guo-zheng Y, Bang-hua Y, Hong S (2008) EEG feature extraction based on wavelet packet decomposition for brain computer interface. Measurement 41(6):618\u2013625","journal-title":"Measurement"},{"issue":"1","key":"1802_CR16","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.jneumeth.2010.05.020","volume":"191","author":"L Guo","year":"2010","unstructured":"Guo L, Rivero D, Dorado J, Rabunal JR, Pazos A (2010) Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks. J Neurosci Methods 191(1):101\u2013109","journal-title":"J Neurosci Methods"},{"issue":"1","key":"1802_CR17","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1016\/j.eswa.2010.07.118","volume":"38","author":"Y \u00d6zbay","year":"2011","unstructured":"\u00d6zbay Y, Ceylan R, Karlik B (2011) Integration of type-2 fuzzy clustering and wavelet transform in a neural network based ECG classifier. Expert Syst Appl 38(1):1004\u20131010","journal-title":"Expert Syst Appl"},{"issue":"5","key":"1802_CR18","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1007\/s00521-012-1074-3","volume":"23","author":"A Ahangi","year":"2013","unstructured":"Ahangi A, Karamnejad M, Mohammadi N, Ebrahimpour R, Bagheri N (2013) Multiple classifier system for EEG signal classification with application to brain\u2013computer interfaces. Neural Comput Appl 23(5):1319\u20131327","journal-title":"Neural Comput Appl"},{"issue":"12","key":"1802_CR19","doi-asserted-by":"crossref","first-page":"8659","DOI":"10.1016\/j.eswa.2010.06.065","volume":"37","author":"A Subasi","year":"2010","unstructured":"Subasi A, Gursoy MI (2010) EEG signal classification using PCA, ICA, LDA and support vector machines. Expert Syst Appl 37(12):8659\u20138666","journal-title":"Expert Syst Appl"},{"issue":"17","key":"1802_CR20","doi-asserted-by":"crossref","first-page":"3051","DOI":"10.1016\/j.neucom.2011.04.029","volume":"74","author":"T Gandhi","year":"2011","unstructured":"Gandhi T, Panigrahi BK, Anand S (2011) A comparative study of wavelet families for EEG signal classification. Neurocomputing 74(17):3051\u20133057","journal-title":"Neurocomputing"},{"issue":"3","key":"1802_CR21","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.cmpb.2010.11.014","volume":"104","author":"Siuly","year":"2011","unstructured":"Siuly, Li Y, Wen PP (2011) Clustering technique-based least square support vector machine for EEG signal classification. Comput Methods Programs Biomed 104(3):358\u2013372","journal-title":"Comput Methods Programs Biomed"},{"issue":"1","key":"1802_CR22","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s00521-010-0472-7","volume":"20","author":"S Sun","year":"2011","unstructured":"Sun S, Lu Y, Chen Y (2011) The stochastic approximation method for adaptive Bayesian classifiers: towards online brain\u2013computer interfaces. Neural Comput Appl 20(1):31\u201340","journal-title":"Neural Comput Appl"},{"issue":"8","key":"1802_CR23","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.compbiomed.2011.05.014","volume":"41","author":"WY Hsu","year":"2011","unstructured":"Hsu WY (2011) EEG-based motor imagery classification using enhanced active segment selection and adaptive classifier. Comput Biol Med 41(8):633\u2013639","journal-title":"Comput Biol Med"},{"issue":"7\u20138","key":"1802_CR24","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1007\/s00521-012-1244-3","volume":"23","author":"S Hu","year":"2013","unstructured":"Hu S, Tian Q, Cao Y, Zhang J, Kong W (2013) Motor imagery classification based on joint regression model and spectral power. Neural Comput Appl 23(7\u20138):1931\u20131936","journal-title":"Neural Comput Appl"},{"issue":"1","key":"1802_CR25","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s00521-011-0744-x","volume":"22","author":"E Cinar","year":"2013","unstructured":"Cinar E, Sahin F (2013) New classification techniques for electroencephalogram (EEG) signals and a real-time EEG control of a robot. Neural Comput Appl 22(1):29\u201339","journal-title":"Neural Comput Appl"},{"issue":"2","key":"1802_CR26","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s10916-008-9231-z","volume":"34","author":"DP Subha","year":"2010","unstructured":"Subha DP, Joseph PK, Acharya R, Lim CM (2010) EEG signal analysis: a survey. J Med Syst 34(2):195\u2013212","journal-title":"J Med Syst"},{"issue":"2","key":"1802_CR27","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/TNSRE.2006.875637","volume":"14","author":"DJ McFarland","year":"2006","unstructured":"McFarland DJ, Anderson CW, Muller K, Schlogl A, Krusienski DJ (2006) BCI meeting 2005-workshop on BCI signal processing: feature extraction and translation. IEEE Trans Neural Syst Rehabil Eng 14(2):135","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"issue":"6","key":"1802_CR28","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1109\/TBME.2005.848377","volume":"52","author":"D Li","year":"2005","unstructured":"Li D, Pedrycz W, Pizzi NJ (2005) Fuzzy wavelet packet based feature extraction method and its application to biomedical signal classification. IEEE Trans Biomed Eng 52(6):1132\u20131139","journal-title":"IEEE Trans Biomed Eng"},{"issue":"1","key":"1802_CR29","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1515\/jisys-2013-0061","volume":"23","author":"Y Tan","year":"2014","unstructured":"Tan Y, Li G, Duan H, Li C (2014) Enhancement of medical image details via wavelet homomorphic filtering transform. J Intell Syst 23(1):83\u201394","journal-title":"J Intell Syst"},{"key":"1802_CR30","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.compbiomed.2013.10.029","volume":"44","author":"N Torbati","year":"2014","unstructured":"Torbati N, Ayatollahi A, Kermani A (2014) An efficient neural network based method for medical image segmentation. Comput Biol Med 44:76\u201387","journal-title":"Comput Biol Med"},{"key":"1802_CR31","author":"T Nguyen","year":"2014","unstructured":"Nguyen T, Khosravi A, Creighton D, Nahavandi S (2014) Classification of healthcare data using genetic fuzzy logic system and wavelets. Expert Syst Appl. doi: 10.1016\/j.eswa.2014.10.027","journal-title":"Expert Syst Appl"},{"issue":"6","key":"1802_CR32","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1109\/TBME.2004.827081","volume":"51","author":"BD Mensh","year":"2004","unstructured":"Mensh BD, Werfel J, Seung HS (2004) BCI competition 2003-data set Ia: combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals. IEEE Trans Biomed Eng 51(6):1052\u20131056","journal-title":"IEEE Trans Biomed Eng"},{"issue":"6","key":"1802_CR33","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1109\/TBME.2004.826702","volume":"51","author":"V Bostanov","year":"2004","unstructured":"Bostanov V (2004) BCI competition 2003-data sets Ib and IIb: feature extraction from event-related brain potentials with the continuous wavelet transform and the t-value scalogram. IEEE Trans Biomed Eng 51(6):1057\u20131061","journal-title":"IEEE Trans Biomed Eng"},{"key":"1802_CR34","volume-title":"Pattern recognition and machine learning","author":"CM Bishop","year":"2006","unstructured":"Bishop CM (2006) Pattern recognition and machine learning. Springer, New York"},{"issue":"1","key":"1802_CR35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/S0962492900002233","volume":"1","author":"RA DeVore","year":"1992","unstructured":"DeVore RA, Lucier BJ (1992) Wavelets. Acta Numer 1(1):1\u201356","journal-title":"Acta Numer"},{"issue":"8","key":"1802_CR36","doi-asserted-by":"crossref","first-page":"1661","DOI":"10.1162\/089976604774201631","volume":"16","author":"RQ Quiroga","year":"2004","unstructured":"Quiroga RQ, Nadasdy Z, Ben-Shaul Y (2004) Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Comput 16(8):1661\u20131687","journal-title":"Neural Comput"},{"key":"1802_CR37","doi-asserted-by":"crossref","unstructured":"Deng L, Pei J, Ma\u00a0J, Lee DL (2004) A rank sum test method for informative gene discovery. In: Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining, pp 410\u2013419","DOI":"10.1145\/1014052.1014099"},{"key":"1802_CR38","volume-title":"Nonparametrics: statistical methods based on ranks","author":"EL Lehmann","year":"2006","unstructured":"Lehmann EL, D\u2019Abrera HJ (2006) Nonparametrics: statistical methods based on ranks. Springer, New York"},{"key":"1802_CR39","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1038\/18581","volume":"398","author":"N Birbaumer","year":"1999","unstructured":"Birbaumer N, Flor H, Ghanayim N, Hinterberger T, Iverson I, Taub E, Kotchoubey B, K\u00fcbler A, Perelmouter J (1999) A brain-controlled spelling device for the completely paralyzed. Nature 398:297\u2013298","journal-title":"Nature"},{"issue":"260","key":"1802_CR40","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1080\/01621459.1952.10483441","volume":"47","author":"WH Kruskal","year":"1952","unstructured":"Kruskal WH, Wallis WA (1952) Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47(260):583\u2013621","journal-title":"J Am Stat Assoc"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1802-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-014-1802-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1802-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,30]],"date-time":"2023-07-30T21:55:35Z","timestamp":1690754135000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-014-1802-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,24]]},"references-count":40,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2015,7]]}},"alternative-id":["1802"],"URL":"https:\/\/doi.org\/10.1007\/s00521-014-1802-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,24]]}}}