{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T03:25:08Z","timestamp":1772249108519,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T00:00:00Z","timestamp":1559001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Commission and European Regional Development Fund","award":["0378_AD_EEGWA_2_P"],"award-info":[{"award-number":["0378_AD_EEGWA_2_P"]}]},{"name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades and FEDER","award":["DPI2017-84280-R"],"award-info":[{"award-number":["DPI2017-84280-R"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia\/Minist\u00e9rio da Ci\u00eancia, Tecnologia e Inova\u00e7\u00e3o and FEDER","award":["POCI-01-0145-FEDER-007274"],"award-info":[{"award-number":["POCI-01-0145-FEDER-007274"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia\/Minist\u00e9rio da Ci\u00eancia, Tecnologia e Inova\u00e7\u00e3o and FEDER","award":["UID\/MAT\/00144\/2013"],"award-info":[{"award-number":["UID\/MAT\/00144\/2013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Alzheimer\u2019s disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (ADMIL), 50 moderate AD patients (ADMOD), and 50 severe AD patients (ADSEV). Our results show statistically significant differences (p-values &lt; 0.05, FDR-corrected Kruskal\u2013Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. ADMIL and ADMOD vs. ADSEV comparisons (p-values &lt; 0.05, FDR-corrected Mann\u2013Whitney U-test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.<\/jats:p>","DOI":"10.3390\/e21060544","type":"journal-article","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T11:18:09Z","timestamp":1559042289000},"page":"544","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["EEG Characterization of the Alzheimer\u2019s Disease Continuum by Means of Multiscale Entropies"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7445-6498","authenticated-orcid":false,"given":"Aar\u00f3n","family":"Maturana-Candelas","sequence":"first","affiliation":[{"name":"Biomedical Engineering Group, E.T.S.I. de Telecomunicaci\u00f3n, Universidad de Valladolid, 47011 Valladolid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9488-0605","authenticated-orcid":false,"given":"Carlos","family":"G\u00f3mez","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, E.T.S.I. de Telecomunicaci\u00f3n, Universidad de Valladolid, 47011 Valladolid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8577-9559","authenticated-orcid":false,"given":"Jes\u00fas","family":"Poza","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, E.T.S.I. de Telecomunicaci\u00f3n, Universidad de Valladolid, 47011 Valladolid, Spain"},{"name":"Instituto de Investigaci\u00f3n en Matem\u00e1ticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain"},{"name":"Instituto de Neurociencias de Castilla y Le\u00f3n (INCYL), Universidad de Salamanca, 37007 Salamanca, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1903-4206","authenticated-orcid":false,"given":"Nadia","family":"Pinto","sequence":"additional","affiliation":[{"name":"Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal"},{"name":"Instituto de Investiga\u00e7\u00e3o e Inova\u00e7\u00e3o em Sa\u00fade (i3S), 4200-135 Porto, Portugal"},{"name":"Center of Mathematics of the University of Porto (CMUP), 4169-007 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9915-2570","authenticated-orcid":false,"given":"Roberto","family":"Hornero","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Group, E.T.S.I. de Telecomunicaci\u00f3n, Universidad de Valladolid, 47011 Valladolid, Spain"},{"name":"Instituto de Investigaci\u00f3n en Matem\u00e1ticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain"},{"name":"Instituto de Neurociencias de Castilla y Le\u00f3n (INCYL), Universidad de Salamanca, 37007 Salamanca, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alzheimer\u2019s Association (2018). 2018 Alzheimer\u2019s disease facts and figures. Alzheimers Dement., 14, 367\u2013429.","DOI":"10.1016\/j.jalz.2018.02.001"},{"key":"ref_2","unstructured":"(2019, April 04). Alzheimer\u2019s Disease International: World Alzheimer Report. Available online: https:\/\/www.alz.co.uk\/research\/world-report-2018."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.2174\/1567205015666180925110222","article-title":"Global View on Alzheimer\u2019s Disease and Diabetes Mellitus: Threats, Risks and Treatment Alzheimer\u2019s Disease and Diabetes Mellitus","volume":"15","author":"Klimova","year":"2018","journal-title":"Curr. Alzheimer Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1111\/j.1365-2796.2004.01388.x","article-title":"Mild cognitive impairment as a diagnostic entity","volume":"256","author":"Petersen","year":"2004","journal-title":"J. Intern. Med."},{"key":"ref_5","first-page":"30","article-title":"Dementia: A systematic approach to identifying reversible causes","volume":"41","author":"Reisberg","year":"1986","journal-title":"Geriatrics"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1007\/s004150050299","article-title":"Early diagnosis of dementia: Neuropsychology","volume":"246","author":"Pasquier","year":"1999","journal-title":"J. Neurol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","article-title":"NIA-AA Research Framework: Toward a biological definition of Alzheimer\u2019s disease","volume":"14","author":"Jack","year":"2018","journal-title":"Alzheimers Dement."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"355","DOI":"10.3233\/JAD-2010-1374","article-title":"Early stages of pathogenesis in memory impairment during normal senescence and Alzheimer\u2019s disease","volume":"20","author":"Daulatzai","year":"2010","journal-title":"J. Alzheimers Dis."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1002\/hbm.24393","article-title":"Changes in EEG multiscale entropy and power-law frequency scaling during the human sleep cycle","volume":"40","author":"Miskovic","year":"2018","journal-title":"Hum. Brain Mapp."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.1088\/0305-4470\/12\/11\/017","article-title":"A spectral entropy method for distinguishing regular and irregular motion of Hamiltonian systems","volume":"12","author":"Powell","year":"1979","journal-title":"J. Phys. A: Math. Gen."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1073\/pnas.88.6.2297","article-title":"Approximate entropy as a measure of system complexity","volume":"88","author":"Pincus","year":"1991","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiol. Heart. Circ. Physiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/0020-0255(86)90006-X","article-title":"Fuzzy Entropy and Conditioning","volume":"40","author":"Kosko","year":"1986","journal-title":"Inf. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","article-title":"Permutation entropy: A natural complexity measure for time series","volume":"88","author":"Bandt","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"G\u00f3mez, C., Poza, J., Gomez-Pilar, J., Bachiller, A., Juan-Cruz, C., Tola-Arribas, M.A., Carreres, A., Cano, M., and Hornero, R. (2016, January 17\u201320). Analysis of Spontaneous EEG Activity in Alzheimer\u2019s Disease Using Cross-Sample Entropy and Graph Theory. Proceedings of the The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lake Buena Vista (Orlando), FL, USA.","DOI":"10.1109\/EMBC.2016.7591319"},{"key":"ref_16","first-page":"591","article-title":"Approximate entropy of EEG background activity in Alzheimer\u2019s disease patients","volume":"15","author":"Hornero","year":"2009","journal-title":"Intell. Autom. Soft. Co."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1088\/0967-3334\/27\/3\/003","article-title":"Entropy analysis of the EEG background activity in Alzheimer\u2019s disease patients","volume":"27","author":"Hornero","year":"2006","journal-title":"Physiol. Meas."},{"key":"ref_18","first-page":"317","article-title":"Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer\u2019s disease","volume":"367","author":"Hornero","year":"2008","journal-title":"Phil. Trans. Math. Phys. Eng. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1016\/j.clinph.2004.01.001","article-title":"EEG dynamics in patients with Alzheimer\u2019s disease","volume":"115","author":"Jeong","year":"2004","journal-title":"Clin. Neurophysiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"021906","DOI":"10.1103\/PhysRevE.71.021906","article-title":"Multiscale entropy analysis of biological signals","volume":"71","author":"Costa","year":"2005","journal-title":"Phys. Rev. E"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"068102","DOI":"10.1103\/PhysRevLett.89.068102","article-title":"Multiscale Entropy Analysis of Complex Physiologic Time Series","volume":"89","author":"Costa","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1312","DOI":"10.1016\/S0140-6736(96)90948-4","article-title":"Non-linear dynamics for clinicians: Chaos theory, fractals, and complexity at the bedside","volume":"347","author":"Goldberger","year":"1996","journal-title":"Lancet"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"685","DOI":"10.3389\/fnins.2018.00685","article-title":"Topological Pattern Recognition of Severe Alzheimer\u2019s Disease Via Regularized Supervised Learning of EEG Complexity","volume":"12","author":"Fan","year":"2018","journal-title":"Front. Neurosci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1088\/0967-3334\/27\/11\/004","article-title":"Analysis of electroencephalograms in Alzheimer\u2019s disease patients with multiscale entropy","volume":"27","author":"Escudero","year":"2006","journal-title":"Physiol. Meas."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1034\/j.1600-0404.2003.02067.x","article-title":"EEG synchronization in mild cognitive impairment and Alzheimer\u2019s disease","volume":"108","author":"Stam","year":"2003","journal-title":"Acta Neurol. Scand."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1016\/j.clinph.2004.09.022","article-title":"Disturbed fluctuations of resting state EEG synchronization in Alzheimer\u2019s disease","volume":"116","author":"Stam","year":"2005","journal-title":"Clin. Neurophysiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10439-007-9402-y","article-title":"Regional Analysis of Spontaneous MEG Rhythms in Patients with Alzheimer\u2019s Disease Using Spectral Entropies","volume":"36","author":"Poza","year":"2007","journal-title":"Ann. Biomed. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1109\/TBME.2016.2533665","article-title":"Refined Multiscale Hilbert-Huang Spectral Entropy and its Application to Central and Peripheral Cardiovascular Data","volume":"63","author":"Wu","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","article-title":"\u201cMini-mental state\u201d. A practical method for grading the cognitive state of patients for the clinician","volume":"12","author":"Folstein","year":"1975","journal-title":"J. Psychiatr. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"046001","DOI":"10.1088\/1741-2552\/aa6e05","article-title":"Exploring non-stationarity patterns in schizophrenia: Neural reorganization abnormalities in the alpha band","volume":"14","author":"Poza","year":"2017","journal-title":"J. Neural Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"76","DOI":"10.3389\/fninf.2018.00076","article-title":"Measuring Alterations of Spontaneous EEG Neural Coupling in Alzheimer\u2019s Disease and Mild Cognitive Impairment by Means of Cross-Entropy Metrics","volume":"12","author":"Poza","year":"2018","journal-title":"Front. Neuroinform."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1088\/0967-3334\/25\/4\/011","article-title":"Cortical entropy changes with general anaesthesia: Theory and experiment","volume":"25","author":"Sleigh","year":"2004","journal-title":"Physiol. Meas."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"R789","DOI":"10.1152\/ajpregu.00069.2002","article-title":"Sample entropy analysis of neonatal heart rate variability","volume":"283","author":"Lake","year":"2002","journal-title":"Am. J. Physiol. Regul. Integr. Comp. Physiol."},{"key":"ref_34","first-page":"323","article-title":"The development of a noisy brain","volume":"148","author":"McIntosh","year":"2010","journal-title":"Arch. Ital. Biol."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Weng, W.C., Jiang, G.J., Chang, C.F., Lu, W.Y., Lin, C.Y., Lee, W.T., and Shieh, J.S. (2015). Complexity of multi-channel electroencephalogram signal analysis in childhood absence epilepsy. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0134083"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2202","DOI":"10.1109\/TBME.2009.2021986","article-title":"Refined multiscale entropy: Application to 24-h Holter recordings of heart period variability in healthy and aortic stenosis subjects","volume":"56","author":"Valencia","year":"2009","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: A practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Series B Stat. Methodol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"058001","DOI":"10.1088\/1741-2560\/6\/5\/058001","article-title":"On the risk of extracting relevant information from random data","volume":"6","author":"Dominguez","year":"2009","journal-title":"J. Neural. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"049901","DOI":"10.1117\/1.2819119","article-title":"Pattern recognition and machine learning","volume":"16","author":"Bishop","year":"2007","journal-title":"J. Electron. Imaging"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1093\/jnci\/95.1.14","article-title":"Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification","volume":"95","author":"Simon","year":"2003","journal-title":"J. Natl. Cancer Inst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1049\/htl.2014.0106","article-title":"Classification of Alzheimer\u2019s disease from quadratic sample entropy of electroencephalogram","volume":"2","author":"Simons","year":"2015","journal-title":"Healthc. Technol. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1016\/S1388-2457(99)00013-9","article-title":"Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls","volume":"110","author":"Jelles","year":"1999","journal-title":"Clin. Neurophysiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/S1364-6613(98)01259-5","article-title":"Complexity and coherency: Integrating information in the brain","volume":"2","author":"Tononi","year":"1998","journal-title":"Trends Cogn. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1016\/j.clinph.2010.03.025","article-title":"Assessment of EEG dynamical complexity in Alzheimer\u2019s disease using multiscale entropy","volume":"121","author":"Mizuno","year":"2010","journal-title":"Clin. Neurophysiol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Azami, H., and Escudero, J. (2018). Coarse-graining approaches in univariate multiscale sample and dispersion entropy. Entropy, 20.","DOI":"10.3390\/e20020138"},{"key":"ref_46","unstructured":"Chai, X., Weng, X., Zhang, Z., Lu, Y., Liu, G., and Niu, H. (2018). Quantitative EEG in Mild Cognitive Impairment and Alzheimer\u2019s Disease by AR-Spectral and Multi-scale Entropy Analysis. World Congress on Medical Physics and Biomedical Engineering, Springer."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1109\/JSEN.2013.2271735","article-title":"Entropic measures of EEG complexity in Alzheimer\u2019s disease through a multivariate multiscale approach","volume":"13","author":"Labate","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1212\/WNL.46.3.692","article-title":"Compensatory reallocation of brain resources supporting verbal episodic memory in Alzheimer\u2019s disease","volume":"46","author":"Becker","year":"1996","journal-title":"Neurology"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"S527","DOI":"10.3233\/JAD-2010-100501","article-title":"Why women have more Alzheimer\u2019s disease than men: Gender and mitochondrial toxicity of amyloid-\u03b2 peptide","volume":"20","author":"Vina","year":"2010","journal-title":"J. Alzheimers Dis."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/6\/544\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:54:14Z","timestamp":1760187254000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/6\/544"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,28]]},"references-count":49,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2019,6]]}},"alternative-id":["e21060544"],"URL":"https:\/\/doi.org\/10.3390\/e21060544","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,28]]}}}