{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T01:30:56Z","timestamp":1773365456773,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,3,17]],"date-time":"2017-03-17T00:00:00Z","timestamp":1489708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The analysis of electroencephalograms (EEGs) of patients with Alzheimer\u2019s disease (AD) could contribute to the diagnosis of this dementia. In this study, a new non-linear signal processing metric, distance-based Lempel\u2013Ziv complexity (dLZC), is introduced to characterise changes between pairs of electrodes in EEGs in AD. When complexity in each signal arises from different sub-sequences, dLZC would be greater than when similar sub-sequences are present in each signal. EEGs from 11 AD patients and 11 age-matched control subjects were analysed. The dLZC values for AD patients were lower than for control subjects for most electrode pairs, with statistically significant differences (p &lt; 0.01, Student\u2019s t-test) in 17 electrode pairs in the distant left, local posterior left, and interhemispheric regions. Maximum diagnostic accuracies with leave-one-out cross-validation were 77.27% for subject-based classification and 78.25% for epoch-based classification. These findings suggest not only that EEGs from AD patients are less complex than those from controls, but also that the richness of the information contained in pairs of EEGs from patients is also lower than in age-matched controls. The analysis of EEGs in AD with dLZC may increase the insight into brain dysfunction, providing complementary information to that obtained with other complexity and synchrony methods.<\/jats:p>","DOI":"10.3390\/e19030129","type":"journal-article","created":{"date-parts":[[2017,3,17]],"date-time":"2017-03-17T11:22:56Z","timestamp":1489749776000},"page":"129","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Distance-Based Lempel\u2013Ziv Complexity for the Analysis of Electroencephalograms in Patients with Alzheimer\u2019s Disease"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4547-793X","authenticated-orcid":false,"given":"Samantha","family":"Simons","sequence":"first","affiliation":[{"name":"Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4268-2885","authenticated-orcid":false,"given":"Daniel","family":"Ab\u00e1solo","sequence":"additional","affiliation":[{"name":"Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,17]]},"reference":[{"key":"ref_1","unstructured":"Braunwald, E., Fauci, A.S., Kasper, D.L., Hauser, S.L., Longo, D.L., and Jameson, J.L. 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