{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T16:59:45Z","timestamp":1778345985921,"version":"3.51.4"},"reference-count":49,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T00:00:00Z","timestamp":1757462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013375","name":"the Ministry of Higher Education, Research and Development of Indonesia, through the RKI 2025 scheme of Universitas Sumatera Utara, Universitas Syiah Kuala, and Universitas Indonesia","doi-asserted-by":"publisher","award":["28\/UN5.4.10.K\/PT.01.03\/RKI\/2025"],"award-info":[{"award-number":["28\/UN5.4.10.K\/PT.01.03\/RKI\/2025"]}],"id":[{"id":"10.13039\/501100013375","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: An ASD diagnosis from EEG is challenging due to non-stationary, low-SNR signals and small cohorts. We propose a compact, interpretable pipeline that pairs a shift-invariant Stationary Wavelet Transform (SWT) with Fisher\u2019s Linear Discriminant (FLDA) as a supervised projection method, delivering band-level insight and subject-wise evaluation suitable for resource-constrained clinics. Methods: EEG from the KAU dataset (eight ASD, eight controls; 256 Hz) was decomposed with SWT (db4). We retained levels 3, 4, and 6 (\u03b3\/\u03b2\/\u03b8) as features. FLDA learned a low-dimensional discriminant subspace, followed by a linear decision rule. Evaluation was conducted using a subject-wise 70\/30 split (no subject overlap) with accuracy, precision, recall, F1, and confusion matrices. Results: The \u03b2 band (Level 4) achieved the best performance (accuracy\/precision\/recall\/F1 = 0.95), followed by \u03b3 (0.92) and \u03b8 (0.85). Despite partial overlap in FLDA scores, the projection maximized between-class separation relative to within-class variance, yielding robust linear decisions. Conclusions: Unlike earlier FLDA-only pipelines and wavelet\u2013entropy\u2013ANN approaches, our study (1) employs SWT (undecimated, shift-invariant) rather than DWT to stabilize sub-band features on short resting segments, (2) uses FLDA as a supervised projection to mitigate small-sample covariance pathologies before classification, (3) provides band-specific discriminative insight (\u03b2 &gt; \u03b3\/\u03b8) under a subject-wise protocol, and (4) targets low-compute deployment. These choices yield a reproducible baseline with competitive accuracy and clear clinical interpretability. Future work will benchmark kernel\/regularized discriminants and lightweight deep models as cohort size and compute permit.<\/jats:p>","DOI":"10.3390\/diagnostics15182291","type":"journal-article","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T08:43:54Z","timestamp":1757493834000},"page":"2291","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Recognition of EEG Features in Autism Disorder Using SWT and Fisher Linear Discriminant Analysis"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6760-4824","authenticated-orcid":false,"given":"Fahmi","family":"Fahmi","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Universitas Sumatera Utara, Medan 20155, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Melinda","family":"Melinda","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prima Dewi","family":"Purnamasari","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universitas Indonesia, Depok 16424, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizar","family":"Elizar","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aufa","family":"Rafiki","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1007\/s10803-022-05758-x","article-title":"Autism Spectrum Disorder in Down Syndrome: Experiences from Caregivers","volume":"54","author":"Spinazzi","year":"2024","journal-title":"J. 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