{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T08:20:37Z","timestamp":1787818837445,"version":"build-2784847793"},"reference-count":70,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health","doi-asserted-by":"publisher","award":["R01DK138248"],"award-info":[{"award-number":["R01DK138248"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"award":["R01DK138248"],"award-info":[{"award-number":["R01DK138248"]}],"id":[{"id":"https:\/\/ror.org\/00adh9b73","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Alzheimer\u2019s disease (AD), the leading cause of dementia, lacks an inexpensive and non-invasive method for early detection. Here, we investigate whether electrodermal activity (EDA), a measure of changes in electrical conductance at the skin\u2019s surface, can offer a convenient avenue for AD screening by capturing the autonomic dysfunction associated with the disease\u2019s pathology. As few studies have comprehensively examined EDA\u2019s utility as a standalone biomarker for AD, we conducted a pilot study with 10 cognitively healthy controls and 20 patients with AD, evaluating EDA recordings collected during an orthostatic test and a Montreal Cognitive Assessment (MoCA). The AD group included both carriers from Colombian kindreds affected by autosomal-dominant AD and patients with sporadic late-onset AD. We compared EDA features between groups using statistical analysis and tested whether machine learning models could separate the two groups using these features. During the MoCA, phasic EDA measures, specifically the number of skin conductance responses (NSSCR) and mean time-variant sympathetic tone (TVSymp), were significantly lower in the AD group than in controls (NSSCR: p=0.0083, Cohen\u2019s d=\u22121.07; mean TVSymp: p=0.0166, d=\u22120.96), suggesting a blunted sympathetic response to cognitive stress in AD. No significant between-group differences were observed during the orthostatic test (all p\u22650.60). A random forest classifier trained on MoCA-derived EDA features achieved a balanced accuracy of 78% (95% CI 60 to 93%; 75% sensitivity, 80% specificity, AUROC 0.75), with phasic features contributing most to performance. Performance did not differ significantly from that of the support vector machine or logistic regression models. These results provide preliminary, hypothesis-generating evidence for the utility of EDA in screening for AD. The small sample size, unequal group allocation, sex imbalance, and substantial mean age disparity between groups (\u224823.5 years) limit the strength of these conclusions and necessitate replication in larger, age- and sex-matched cohorts that include prodromal stages.<\/jats:p>","DOI":"10.3390\/s26175407","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T08:02:27Z","timestamp":1787817747000},"page":"5407","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Electrodermal Activity as a Potential Diagnostic Biomarker for Alzheimer\u2019s Disease: A Pilot Study"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2640-655X","authenticated-orcid":false,"given":"Sibi","family":"Pandian","sequence":"first","affiliation":[{"name":"Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3543-3677","authenticated-orcid":false,"given":"Luis R.","family":"Mercado-Diaz","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1180-0923","authenticated-orcid":false,"given":"Jonathan","family":"Ruiz-Trivino","sequence":"additional","affiliation":[{"name":"Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medell\u00edn 050010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2283-536X","authenticated-orcid":false,"given":"David","family":"Aguillon","sequence":"additional","affiliation":[{"name":"Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medell\u00edn 050010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4514-4772","authenticated-orcid":false,"given":"Hugo","family":"Posada-Quintero","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"ref_1","unstructured":"Prince, M., Albanese, E., Guerchet, M., and Prina, M. 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