Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer's Disease
dc.contributor.author | Al-Nuaimi, Ali H. Husseen | |
dc.contributor.author | Jammeh, Emmanuel | |
dc.contributor.author | Sun, Lingfen | |
dc.contributor.author | Ifeachor, Emmanuel | |
dc.date.accessioned | 2018-10-17T09:36:19Z | |
dc.date.available | 2018-10-17T09:36:19Z | |
dc.date.issued | 2018-03-13 | |
dc.identifier.issn | 1076-2787 | |
dc.identifier.issn | 1099-0526 | |
dc.identifier.other | ARTN 8915079 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/12567 | |
dc.description.abstract |
<jats:p>Alzheimer’s disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations. A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis. Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs. This is a cross-sectional study that aims to demonstrate the usefulness of EEG complexity measures in early AD diagnosis. We have focused on the three complexity methods which have shown the greatest promise in the detection of AD, Tsallis entropy (TsEn), Higuchi Fractal Dimension (HFD), and Lempel-Ziv complexity (LZC) methods. Unlike previous approaches, in this study, the complexity measures are derived from EEG frequency bands (instead of the entire EEG) as EEG activities have significant association with AD and this has led to enhanced performance. The results show that AD patients have significantly lower TsEn, HFD, and LZC values for specific EEG frequency bands and for specific EEG channels and that this information can be used to detect AD with a sensitivity and specificity of more than 90%.</jats:p> | |
dc.format.extent | 1-12 | |
dc.language | en | |
dc.language.iso | en | |
dc.publisher | Hindawi Publishing Corporation | |
dc.subject | Acquired Cognitive Impairment | |
dc.subject | Aging | |
dc.subject | Alzheimer's Disease | |
dc.subject | Brain Disorders | |
dc.subject | Prevention | |
dc.subject | Neurosciences | |
dc.subject | Dementia | |
dc.subject | Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) | |
dc.subject | Neurodegenerative | |
dc.subject | Clinical Research | |
dc.subject | 4.1 Discovery and preclinical testing of markers and technologies | |
dc.subject | Neurological | |
dc.title | Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer's Disease | |
dc.type | journal-article | |
dc.type | Journal Article | |
plymouth.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000428429700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.volume | 2018 | |
plymouth.publication-status | Published | |
plymouth.journal | Complexity | |
dc.identifier.doi | 10.1155/2018/8915079 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA12 Engineering | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
plymouth.organisational-group | /Plymouth/Users by role/Researchers in ResearchFish submission | |
dcterms.dateAccepted | 2018-02-04 | |
dc.identifier.eissn | 1099-0526 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.funder | EPSRC | |
rioxxterms.identifier.project | Novel Point-of-Care Diagnostic Techniques for Dementia | |
rioxxterms.versionofrecord | 10.1155/2018/8915079 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2018-03-13 | |
rioxxterms.type | Journal Article/Review | |
plymouth.funder | Novel Point-of-Care Diagnostic Techniques for Dementia::EPSRC |