{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:04:13Z","timestamp":1788998653138,"version":"build-2803163510"},"reference-count":82,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,11,8]],"date-time":"2017-11-08T00:00:00Z","timestamp":1510099200000},"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":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2018,1]]},"DOI":"10.1007\/s11517-017-1734-7","type":"journal-article","created":{"date-parts":[[2017,11,8]],"date-time":"2017-11-08T04:16:33Z","timestamp":1510114593000},"page":"137-157","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Discrimination of stroke-related mild cognitive impairment and vascular dementia using EEG signal analysis"],"prefix":"10.1007","volume":"56","author":[{"given":"Noor Kamal","family":"Al-Qazzaz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sawal Hamid Bin Mohd","family":"Ali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siti Anom","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohd Shabiul","family":"Islam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier","family":"Escudero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,11,8]]},"reference":[{"key":"1734_CR1","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.2147\/NDT.S68443","volume":"10","author":"NK Al-Qazzaz","year":"2014","unstructured":"Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S (2014) Cognitive assessments for the early diagnosis of dementia after stroke. Neuropsychiatr Dis Treat 10:1743","journal-title":"Neuropsychiatr Dis Treat"},{"key":"1734_CR2","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1136\/jnnp.2006.095414","volume":"78","author":"B Cullen","year":"2007","unstructured":"Cullen B, O\u2019Neill B, Evans JJ, Coen RF, Lawlor BA (2007) A review of screening tests for cognitive impairment. J Neurol Neurosurg Psychiatry 78:790\u2013799","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"1734_CR3","doi-asserted-by":"crossref","first-page":"229","DOI":"10.2147\/ciia.2006.1.3.229","volume":"1","author":"C McVeigh","year":"2006","unstructured":"McVeigh C, Passmore P (2006) Vascular dementia: prevention and treatment. Clin Interv Aging 1:229","journal-title":"Clin Interv Aging"},{"key":"1734_CR4","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.jns.2012.03.027","volume":"322","author":"AD Korczyn","year":"2012","unstructured":"Korczyn AD, Vakhapova V, Grinberg LT (Nov 15 2012) Vascular dementia. J Neurol Sci 322:2\u201310","journal-title":"J Neurol Sci"},{"key":"1734_CR5","doi-asserted-by":"crossref","unstructured":"NK Al-Qazzaz, SHB Ali, SA Ahmad, K Chellappan, MS Islam, J Escudero (2014) Role of EEG as biomarker in the early detection and classification of dementia, Sci World J vol 2014","DOI":"10.1155\/2014\/906038"},{"key":"1734_CR6","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1126\/science.1736359","volume":"255","author":"A Baddeley","year":"1992","unstructured":"Baddeley A (1992) Working memory. Science 255:556\u2013559","journal-title":"Science"},{"key":"1734_CR7","unstructured":"Chellappan K, Mohsin NK, Ali SBM, Islam M (2012) Post-stroke brain memory assessment framework, in Biomedical engineering and sciences (IECBES), 2012 I.E. EMBS conference on. pp. 189\u2013194"},{"key":"1734_CR8","doi-asserted-by":"crossref","unstructured":"Guerrero-Mosquera C, Trigueros AM, Navia-Vazquez A (2012) EEG signal processing for epilepsy","DOI":"10.5772\/31609"},{"key":"1734_CR9","unstructured":"N\u00fa\u00f1ez IMB (2010) EEG artifact detection"},{"key":"1734_CR10","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.jneumeth.2014.01.024","volume":"225","author":"R Sameni","year":"2014","unstructured":"Sameni R, Gouy-Pailler C (2014) An iterative subspace denoising algorithm for removing electroencephalogram ocular artifacts. J Neurosci Methods 225:97\u2013105","journal-title":"J Neurosci Methods"},{"key":"1734_CR11","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.dsp.2008.07.004","volume":"19","author":"ED \u00dcbeyli","year":"2009","unstructured":"\u00dcbeyli ED (2009) Combined neural network model employing wavelet coefficients for EEG signals classification. Digit Signal Process 19:297\u2013308","journal-title":"Digit Signal Process"},{"key":"1734_CR12","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.3390\/s17061326","volume":"17","author":"NK Al-Qazzaz","year":"2017","unstructured":"Al-Qazzaz NK, Hamid Bin Mohd Ali S, Ahmad SA, Islam MS, Escudero J (2017) Automatic artifact removal in EEG of normal and demented individuals using ICA\u2013WT during working memory tasks. Sensors 17:1326","journal-title":"Sensors"},{"key":"1734_CR13","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1109\/JSEN.2011.2115236","volume":"12","author":"N Mammone","year":"2012","unstructured":"Mammone N, La Foresta F, Morabito FC (2012) Automatic artifact rejection from multichannel scalp EEG by wavelet ICA. Sensors J IEEE 12:533\u2013542","journal-title":"Sensors J IEEE"},{"key":"1734_CR14","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1111\/j.1469-8986.2010.01061.x","volume":"48","author":"A Mognon","year":"2011","unstructured":"Mognon A, Jovicich J, Bruzzone L, Buiatti M (2011) ADJUST: an automatic EEG artifact detector based on the joint use of spatial and temporal features. Psychophysiology 48:229\u2013240","journal-title":"Psychophysiology"},{"key":"1734_CR15","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","volume":"134","author":"A Delorme","year":"2004","unstructured":"Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134:9\u201321","journal-title":"J Neurosci Methods"},{"key":"1734_CR16","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/0013-4694(85)91048-X","volume":"61","author":"LA Coben","year":"1985","unstructured":"Coben LA, Danziger W, Storandt M (1985) A longitudinal EEG study of mild senile dementia of Alzheimer type: changes at 1 year and at 2.5 years. Electroencephalogr Clin Neurophysiol 61:101\u2013112","journal-title":"Electroencephalogr Clin Neurophysiol"},{"key":"1734_CR17","doi-asserted-by":"crossref","unstructured":"Moretti D, Zanetti O, Binetti G, Frisoni G (2012) Quantitative EEG markers in mild cognitive impairment: degenerative versus vascular brain impairment. Int J Alzheimer\u2019s Dis vol 2012","DOI":"10.1155\/2012\/917537"},{"key":"1734_CR18","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.clinph.2008.11.012","volume":"120","author":"D Moretti","year":"2009","unstructured":"Moretti D, Fracassi C, Pievani M, Geroldi C, Binetti G, Zanetti O et al (2009) Increase of theta\/gamma ratio is associated with memory impairment. Clin Neurophysiol 120:295\u2013303","journal-title":"Clin Neurophysiol"},{"key":"1734_CR19","first-page":"1","volume":"4","author":"D Moretti","year":"2013","unstructured":"Moretti D, Paternic\u00f2 D, Binetti G, Zanetti O, Frisoni G (2013) Relationship between EEG alpha3\/alpha2 ration and the nucleus accumbens in subjects with mild cognitive impairment. J Neurol Neurophysiol 4:1\u20136","journal-title":"J Neurol Neurophysiol"},{"key":"1734_CR20","doi-asserted-by":"crossref","first-page":"1866","DOI":"10.1016\/j.clinph.2007.05.009","volume":"118","author":"D Moretti","year":"2007","unstructured":"Moretti D, Miniussi C, Frisoni G, Zanetti O, Binetti G, Geroldi C et al (2007) Vascular damage and EEG markers in subjects with mild cognitive impairment. Clin Neurophysiol 118:1866\u20131876","journal-title":"Clin Neurophysiol"},{"key":"1734_CR21","doi-asserted-by":"crossref","first-page":"60","DOI":"10.3389\/fnagi.2013.00060","volume":"5","author":"MT Schmidt","year":"2013","unstructured":"Schmidt MT, Kanda PA, Basile LF, da Silva Lopes HF, Baratho R, Demario J et al (2013) Index of alpha\/theta ratio of the electroencephalogram: a new marker for Alzheimer\u2019s disease. Front Aging Neurosci 5:60","journal-title":"Front Aging Neurosci"},{"key":"1734_CR22","doi-asserted-by":"crossref","first-page":"3008","DOI":"10.1162\/jocn_a_00029","volume":"23","author":"M Lundqvist","year":"2011","unstructured":"Lundqvist M, Herman P, Lansner A (2011) Theta and gamma power increases and alpha\/beta power decreases with memory load in an attractor network model. J Cogn Neurosci 23:3008\u20133020","journal-title":"J Cogn Neurosci"},{"key":"1734_CR23","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.medengphy.2005.07.004","volume":"28","author":"D Ab\u00e1solo","year":"2006","unstructured":"Ab\u00e1solo D, Hornero R, G\u00f3mez C, Garc\u00eda M, L\u00f3pez M (2006) Analysis of EEG background activity in Alzheimer\u2019s disease patients with Lempel\u2013Ziv complexity and central tendency measure. Med Eng Phys 28:315\u2013322","journal-title":"Med Eng Phys"},{"key":"1734_CR24","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1088\/0967-3334\/27\/11\/004","volume":"27","author":"J Escudero","year":"2006","unstructured":"Escudero J, Ab\u00e1solo D, Hornero R, Espino P, L\u00f3pez M (2006) Analysis of electroencephalograms in Alzheimer\u2019s disease patients with multiscale entropy. Physiol Meas 27:1091","journal-title":"Physiol Meas"},{"key":"1734_CR25","unstructured":"Kantz H, Kurths J, Mayer-Kress G (2012) Nonlinear analysis of physiological data: Springer Science and Business Media"},{"key":"1734_CR26","doi-asserted-by":"crossref","DOI":"10.1002\/9781118622162","volume-title":"Adaptive processing of brain signals","author":"S Sanei","year":"2013","unstructured":"Sanei S (2013) Adaptive processing of brain signals. Wiley, New York"},{"key":"1734_CR27","doi-asserted-by":"crossref","unstructured":"Holzinger A, H\u00f6rtenhuber M, Mayer C, Bachler M, Wassertheurer S, Pinho AJ et al (2014) On entropy-based data mining. In: Interactive knowledge discovery and data mining in biomedical informatics. Springer, pp 209\u2013226","DOI":"10.1007\/978-3-662-43968-5_12"},{"key":"1734_CR28","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.3390\/e14071186","volume":"14","author":"FC Morabito","year":"2012","unstructured":"Morabito FC, Labate D, La Foresta F, Bramanti A, Morabito G, Palamara I (2012) Multivariate multi-scale permutation entropy for complexity analysis of Alzheimer\u2019s disease EEG. Entropy 14:1186\u20131202","journal-title":"Entropy"},{"key":"1734_CR29","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1109\/TBME.2006.878067","volume":"53","author":"G Henderson","year":"2006","unstructured":"Henderson G, Ifeachor E, Hudson N, Goh C, Outram N, Wimalaratna S et al (2006) Development and assessment of methods for detecting dementia using the human electroencephalogram. IEEE Trans Biomed Eng 53:1557\u20131568","journal-title":"IEEE Trans Biomed Eng"},{"key":"1734_CR30","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.pnpbp.2013.07.022","volume":"47","author":"AC Yang","year":"2013","unstructured":"Yang AC, Wang S-J, Lai K-L, Tsai C-F, Yang C-H, Hwang J-P et al (2013) Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer\u2019s disease. Prog Neuro-Psychopharmacol Biol Psychiatry 47:52\u201361","journal-title":"Prog Neuro-Psychopharmacol Biol Psychiatry"},{"key":"1734_CR31","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, Ismail Gursoy M (2010) EEG signal classification using PCA, ICA, LDA and support vector machines. Expert Syst Appl 37:8659\u20138666","journal-title":"Expert Syst Appl"},{"key":"1734_CR32","unstructured":"KavitaMahajan M, Rajput MSM (2012) A comparative study of ANN and SVM for EEG classification. Int J Eng vol 1"},{"key":"1734_CR33","unstructured":"Vialatte F, Cichocki A, Dreyfus G, Musha T, Rutkowski TM, Gervais R (2005) Blind source separation and sparse bump modelling of time frequency representation of eeg signals: New tools for early detection of alzheimer\u2019s disease, in Machine Learning for Signal Processing, 2005 I.E. Workshop on pp. 27\u201332"},{"key":"1734_CR34","doi-asserted-by":"crossref","first-page":"415","DOI":"10.4067\/S0716-97602007000500005","volume":"40","author":"M Besserve","year":"2007","unstructured":"Besserve M, Jerbi K, Laurent F, Baillet S, Martinerie J, Garnero L (2007) Classification methods for ongoing EEG and MEG signals. Biol Res 40:415\u2013437","journal-title":"Biol Res"},{"key":"1734_CR35","unstructured":"Khushaba RN, Kodagoda S, Liu D, Dissanayake G (2011) Electromyogram (EMG) based fingers movement recognition using neighborhood preserving analysis with QR-decomposition, in Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2011 Seventh International Conference on, pp. 1\u2013105"},{"key":"1734_CR36","doi-asserted-by":"crossref","first-page":"12431","DOI":"10.3390\/s130912431","volume":"13","author":"RH Chowdhury","year":"2013","unstructured":"Chowdhury RH, Reaz MB, Ali MABM, Bakar AA, Chellappan K, Chang T (2013) Surface electromyography signal processing and classification techniques. Sensors 13:12431\u201312466","journal-title":"Sensors"},{"key":"1734_CR37","doi-asserted-by":"crossref","unstructured":"Al-Timemy A, Bugmann G, Escudero J, Outram N (2013) Classification of finger movements for the dexterous hand prosthesis control with surface. Electromyography","DOI":"10.1109\/JBHI.2013.2249590"},{"key":"1734_CR38","unstructured":"Folstein MF, Folstein SE, McHugh PR 1998 Mini-mental state, A prac-32"},{"key":"1734_CR39","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1177\/070674370705200508","volume":"52","author":"T Smith","year":"2007","unstructured":"Smith T, Gildeh N, Holmes C (2007) The Montreal cognitive assessment: validity and utility in a memory clinic setting. Can J Psychiatr 52:329","journal-title":"Can J Psychiatr"},{"key":"1734_CR40","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.2147\/NDT.S67184","volume":"10","author":"NK Al-Qazzaz","year":"2014","unstructured":"Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S, Mohamad K (2014) Cognitive impairment and memory dysfunction after a stroke diagnosis: a post-stroke memory assessment. Neuropsychiatr Dis Treat 10:1677","journal-title":"Neuropsychiatr Dis Treat"},{"key":"1734_CR41","doi-asserted-by":"crossref","first-page":"29015","DOI":"10.3390\/s151129015","volume":"15","author":"N Al-Qazzaz","year":"2015","unstructured":"Al-Qazzaz N, Hamid Bin Mohd Ali S, Ahmad S, Islam M, Escudero J (2015) Selection of mother wavelet functions for multi-channel EEG signal analysis during a working memory task. Sensors 15:29015","journal-title":"Sensors"},{"key":"1734_CR42","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/72.761722","volume":"10","author":"A Hyvarinen","year":"1999","unstructured":"Hyvarinen A (1999) Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Netw 10:626\u2013634","journal-title":"IEEE Trans Neural Netw"},{"key":"1734_CR43","unstructured":"Al-Timemy AH, Bugmann G, Outram N, Escudero J 2011 Reduction in classification errors for myoelectric control of hand movements with independent component analysis, in The 5th International Conference on Information Technology, ICIT"},{"key":"1734_CR44","doi-asserted-by":"crossref","unstructured":"Stein CM (1981) Estimation of the mean of a multivariate normal distribution. Ann Stat:1135\u20131151","DOI":"10.1214\/aos\/1176345632"},{"key":"1734_CR45","unstructured":"Romo-Vazquez R, Ranta R, Louis-Dorr V, Maquin D (2007) EEG ocular artefacts and noise removal, in Engineering in medicine and biology society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp. 5445\u20135448"},{"key":"1734_CR46","unstructured":"Estrada E, Nazeran H, Sierra G, Ebrahimi F, Setarehdan SK (2011)Wavelet-based EEG denoising for automatic sleep stage classification, in Electrical communications and computers (CONIELECOMP), 2011 21st international conference on, pp. 295\u2013298"},{"key":"1734_CR47","unstructured":"Al-Qazzaz NK, Ali S, Ahmad SA, Islam MS, Ariff MI (2014) Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task, in Biomedical engineering and sciences (IECBES), 2014 I.E. conference on, pp. 214\u2013219"},{"key":"1734_CR48","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1159\/000106615","volume":"8","author":"I Rosen","year":"1997","unstructured":"Rosen I (1997) Electroencephalography as a diagnostic tool in dementia. Dement Geriatr Cogn Disord 8:110\u2013116","journal-title":"Dement Geriatr Cogn Disord"},{"key":"1734_CR49","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1016\/j.clinph.2004.01.001","volume":"115","author":"J Jeong","year":"2004","unstructured":"Jeong J (2004) EEG dynamics in patients with Alzheimer\u2019s disease. Clin Neurophysiol 115:1490\u20131505","journal-title":"Clin Neurophysiol"},{"key":"1734_CR50","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1007\/s12555-009-0521-0","volume":"7","author":"K-E Ko","year":"2009","unstructured":"Ko K-E, Yang H-C, Sim K-B (2009) Emotion recognition using EEG signals with relative power values and Bayesian network. Int J Control Autom Syst 7:865\u2013870","journal-title":"Int J Control Autom Syst"},{"key":"1734_CR51","doi-asserted-by":"crossref","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","volume":"88","author":"C Bandt","year":"2002","unstructured":"Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88:174102","journal-title":"Phys Rev Lett"},{"key":"1734_CR52","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.3390\/e14081553","volume":"14","author":"M Zanin","year":"2012","unstructured":"Zanin M, Zunino L, Rosso OA, Papo D (2012) Permutation entropy and its main biomedical and econophysics applications: a review. Entropy 14:1553\u20131577","journal-title":"Entropy"},{"key":"1734_CR53","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.bspc.2015.08.004","volume":"23","author":"H Azami","year":"2016","unstructured":"Azami H, Escudero J (2016) Improved multiscale permutation entropy for biomedical signal analysis: interpretation and application to electroencephalogram recordings. Biomed Signal Process Control 23:28\u201341","journal-title":"Biomed Signal Process Control"},{"key":"1734_CR54","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/0167-2789(88)90081-4","volume":"31","author":"T Higuchi","year":"1988","unstructured":"Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Physica D Nonlinear Phenomena 31:277\u2013283","journal-title":"Physica D Nonlinear Phenomena"},{"key":"1734_CR55","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/TSP.1993.193131","volume":"41","author":"P Maragos","year":"1993","unstructured":"Maragos P, Sun F-K (1993) Measuring the fractal dimension of signals: morphological covers and iterative optimization. IEEE Trans Signal Process 41:108\u2013121","journal-title":"IEEE Trans Signal Process"},{"key":"1734_CR56","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0010-4825(88)90041-8","volume":"18","author":"MJ Katz","year":"1988","unstructured":"Katz MJ (1988) Fractals and the analysis of waveforms. Comput Biol Med 18:145\u2013156","journal-title":"Comput Biol Med"},{"key":"1734_CR57","unstructured":"Petrosian A (1995) Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns, in Computer-based medical systems, 1995., Proceedings of the Eighth IEEE Symposium on, pp. 212\u2013217"},{"key":"1734_CR58","unstructured":"Mandelbrot B (1977) Fractals: form, chance and dimension. San Francisco, ed: WH Freeman and Co"},{"key":"1734_CR59","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/s004220050394","volume":"77","author":"A Accardo","year":"1997","unstructured":"Accardo A, Affinito M, Carrozzi M, Bouquet F (1997) Use of the fractal dimension for the analysis of electroencephalographic time series. Biol Cybern 77:339\u2013350","journal-title":"Biol Cybern"},{"key":"1734_CR60","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1109\/81.904882","volume":"48","author":"R Esteller","year":"2001","unstructured":"Esteller R, Vachtsevanos G, Echauz J, Litt B (2001) A comparison of waveform fractal dimension algorithms. IEEE Trans Circuits Syst I: Fundam Theory Appl 48:177\u2013183","journal-title":"IEEE Trans Circuits Syst I: Fundam Theory Appl"},{"key":"1734_CR61","doi-asserted-by":"crossref","first-page":"1869","DOI":"10.1103\/PhysRevA.42.1869","volume":"42","author":"A Block","year":"1990","unstructured":"Block A, Von Bloh W, Schellnhuber H (1990) Efficient box-counting determination of generalized fractal dimensions. Phys Rev A 42:1869","journal-title":"Phys Rev A"},{"key":"1734_CR62","doi-asserted-by":"crossref","first-page":"11","DOI":"10.7150\/ijms.1.11","volume":"1","author":"TL Doyle","year":"2004","unstructured":"Doyle TL, Dugan EL, Humphries B, Newton RU (2004) Discriminating between elderly and young using a fractal dimension analysis of centre of pressure. Int J Med Sci 1:11","journal-title":"Int J Med Sci"},{"key":"1734_CR63","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1016\/j.physa.2004.05.045","volume":"342","author":"W Klonowski","year":"2004","unstructured":"Klonowski W, Olejarczyk E, Stepien R (2004) \u2018Epileptic seizures\u2019 in economic organism. Physica A: Stat Mech Appl 342:701\u2013707","journal-title":"Physica A: Stat Mech Appl"},{"key":"1734_CR64","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.neurobiolaging.2009.04.003","volume":"32","author":"D Moretti","year":"2011","unstructured":"Moretti D, Frisoni G, Fracassi C, Pievani M, Geroldi C, Binetti G et al (2011) MCI patients\u2019 EEGs show group differences between those who progress and those who do not progress to AD. Neurobiol Aging 32:563\u2013571","journal-title":"Neurobiol Aging"},{"key":"1734_CR65","doi-asserted-by":"crossref","unstructured":"Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res:321\u2013357","DOI":"10.1613\/jair.953"},{"key":"1734_CR66","unstructured":"Kohavi R (1995) A study of cross-validation and bootstrap for accuracy estimation and model selection, in Ijcai, pp. 1137\u20131145"},{"key":"1734_CR67","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.jneumeth.2015.08.026","volume":"257","author":"Y Song","year":"2016","unstructured":"Song Y, Zhang J (2016) Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine. J Neurosci Methods 257:45\u201354","journal-title":"J Neurosci Methods"},{"key":"1734_CR68","unstructured":"Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques. Morgan Kaufmann"},{"key":"1734_CR69","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The WEKA data mining software: an update. ACM SIGKDD Explor Newslett 11:10\u201318","journal-title":"ACM SIGKDD Explor Newslett"},{"key":"1734_CR70","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.jneumeth.2006.10.023","volume":"161","author":"C Lehmann","year":"2007","unstructured":"Lehmann C, Koenig T, Jelic V, Prichep L, John RE, Wahlund L-O et al (2007) Application and comparison of classification algorithms for recognition of Alzheimer\u2019s disease in electrical brain activity (EEG). J Neurosci Methods 161:342\u2013350","journal-title":"J Neurosci Methods"},{"key":"1734_CR71","doi-asserted-by":"crossref","unstructured":"Vapnik V (2000) The nature of statistical learning theory. Springer","DOI":"10.1007\/978-1-4757-3264-1"},{"key":"1734_CR72","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/TITB.2006.879600","volume":"11","author":"I Guler","year":"2007","unstructured":"Guler I, Ubeyli ED (2007) Multiclass support vector machines for EEG-signals classification. IEEE Trans Inf Technol Biomed 11:117\u2013126","journal-title":"IEEE Trans Inf Technol Biomed"},{"key":"1734_CR73","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 11:141\u2013144","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"1734_CR74","unstructured":"Duda RO, Hart PE, Stork DG (2012) Pattern classification. Wiley"},{"key":"1734_CR75","doi-asserted-by":"crossref","unstructured":"Kantardzic M (2011) Data mining: concepts, models, methods, and algorithms. Wiley","DOI":"10.1002\/9781118029145"},{"key":"1734_CR76","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1016\/j.clinph.2003.12.029","volume":"115","author":"Y Pijnenburg","year":"2004","unstructured":"Pijnenburg Y, Vd Made Y, van Cappellen van Walsum AM, Knol DL, Scheltens P, Stam C (2004) EEG synchronization likelihood in mild cognitive impairment and Alzheimer\u2019s disease during a working memory task. Clin Neurophysiol 115:1332\u20131339","journal-title":"Clin Neurophysiol"},{"key":"1734_CR77","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/S0165-0173(98)00056-3","volume":"29","author":"W Klimesch","year":"1999","unstructured":"Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev 29:169\u2013195","journal-title":"Brain Res Rev"},{"key":"1734_CR78","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1109\/IECBES.2016.7843471","volume-title":"Biomedical engineering and sciences (IECBES), 2016 I.E. EMBS Conference on","author":"NK Al-Qazzaz","year":"2016","unstructured":"Al-Qazzaz NK, Ali S, Islam MS, Ahmad SA, Escudero J (2016) EEG markers for early detection and characterization of vascular dementia during working memory tasks. In: Biomedical engineering and sciences (IECBES), 2016 I.E. EMBS Conference on, pp 347\u2013351"},{"key":"1734_CR79","doi-asserted-by":"crossref","unstructured":"Al-Qazzaz NK, Ali S, Islam S, Ahmad S, Escudero J (2016) EEG wavelet spectral analysis during a working memory tasks in stroke-related mild cognitive impairment patients, in International Conference for Innovation in Biomedical Engineering and Life Sciences, pp. 82\u201385","DOI":"10.1007\/978-981-10-0266-3_17"},{"key":"1734_CR80","unstructured":"Al-Qazzaz NK, Ali S, Ahmad SA, Islam MS, Escudero J (2016) Entropy-based markers of EEG background activity of stroke-related mild cognitive impairment and vascular dementia patients, presented at the 2nd International Conference on Sensors Engineering and Electronics Instrumental Advances (SEIA 2016), Barcelona, Spain"},{"key":"1734_CR81","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1093\/cercor\/7.4.374","volume":"7","author":"A Gevins","year":"1997","unstructured":"Gevins A, Smith ME, McEvoy L, Yu D (1997) High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb Cortex 7:374\u2013385","journal-title":"Cereb Cortex"},{"key":"1734_CR82","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.medengphy.2008.06.010","volume":"31","author":"C G\u00f3mez","year":"2009","unstructured":"G\u00f3mez C, Mediavilla \u00c1, Hornero R, Ab\u00e1solo D, Fern\u00e1ndez A (2009) Use of the Higuchi\u2019s fractal dimension for the analysis of MEG recordings from Alzheimer\u2019s disease patients. Med Eng Phys 31:306\u2013313","journal-title":"Med Eng Phys"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-017-1734-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-017-1734-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-017-1734-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,5]],"date-time":"2019-10-05T19:54:15Z","timestamp":1570305255000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-017-1734-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,8]]},"references-count":82,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1]]}},"alternative-id":["1734"],"URL":"https:\/\/doi.org\/10.1007\/s11517-017-1734-7","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,8]]}}}