{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T17:01:49Z","timestamp":1790787709061,"version":"4.1.0"},"reference-count":42,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of Enterpise and Made in Italy (MIMIT)","award":["B69J23001290005"],"award-info":[{"award-number":["B69J23001290005"]}]},{"name":"Italian Ministry of Enterpise and Made in Italy (MIMIT)","award":["B89J23002490005"],"award-info":[{"award-number":["B89J23002490005"]}]},{"name":"Italian Ministry of Enterpise and Made in Italy (MIMIT)","award":["DOT19X7NYL-2"],"award-info":[{"award-number":["DOT19X7NYL-2"]}]},{"name":"European Union\u2014FSE-REACT-EU","award":["B69J23001290005"],"award-info":[{"award-number":["B69J23001290005"]}]},{"name":"European Union\u2014FSE-REACT-EU","award":["B89J23002490005"],"award-info":[{"award-number":["B89J23002490005"]}]},{"name":"European Union\u2014FSE-REACT-EU","award":["DOT19X7NYL-2"],"award-info":[{"award-number":["DOT19X7NYL-2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer\u2019s disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity measure particularly sensitive to intra- and inter-subject variations in signal amplitude, as well as the selection of key parameters such as embedding dimension (m) and similarity criterion (r), which often result in inconsistent outcomes when applied to multivariate data, such as electroencephalography signals. To address these challenges and to generalize the possibility of adopting Multiscale Fuzzy Entropy as a diagnostic tool for Alzheimer\u2019s disease, this research explores amplitude transformation preprocessing on electroencephalography signals in Multiscale Fuzzy Entropy calculation across varying parameters. The statistical analysis of the obtained results demonstrates that amplitude transformation preprocessing significantly enhances Multiscale Fuzzy Entropy\u2019s ability to detect Alzheimer\u2019s disease, achieving higher and more consistent significant comparison percentages, with an average of 73.2% across all parameter combinations, compared with only one raw data combination exceeding 65%. Clustering analysis corroborates these findings, showing that amplitude transformation improves the differentiation between Alzheimer\u2019s disease patients and healthy subjects. These results highlight the potential of amplitude transformation to stabilize Multiscale Fuzzy Entropy performance, making it a more reliable tool for early Alzheimer\u2019s disease detection.<\/jats:p>","DOI":"10.3390\/s24237794","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T09:30:18Z","timestamp":1733391018000},"page":"7794","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer\u2019s Disease Detection via Amplitude Transformation"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5192-5922","authenticated-orcid":false,"given":"Pasquale","family":"Arpaia","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8825-3415","authenticated-orcid":false,"given":"Maria","family":"Cacciapuoti","sequence":"additional","affiliation":[{"name":"Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9031-7690","authenticated-orcid":false,"given":"Andrea","family":"Cataldo","sequence":"additional","affiliation":[{"name":"Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7189-1339","authenticated-orcid":false,"given":"Sabatina","family":"Criscuolo","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2792-2131","authenticated-orcid":false,"given":"Egidio","family":"De Benedetto","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8715-2303","authenticated-orcid":false,"given":"Antonio","family":"Masciullo","sequence":"additional","affiliation":[{"name":"Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5671-6433","authenticated-orcid":false,"given":"Marisa","family":"Pesola","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8462-5563","authenticated-orcid":false,"given":"Raissa","family":"Schiavoni","sequence":"additional","affiliation":[{"name":"Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5047","DOI":"10.1111\/ejn.15800","article-title":"Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations","volume":"56","author":"Lau","year":"2022","journal-title":"Eur. 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