{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T17:40:18Z","timestamp":1792086018592,"version":"4.4.0"},"reference-count":56,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:00:00Z","timestamp":1776816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Objective: Single-channel EEG artifact suppression often relies on signal decomposition; however, it is not always clear how much clean EEG is recoverable from a given decomposition when component weighting is ideal. We present an oracle-based benchmark that characterises this best-case recoverability across common 1-D decomposition families under controlled EOG, EMG, and mixed contamination. This work does not propose a new denoising algorithm; rather, it isolates representation capacity from component-selection heuristics by computing an upper bound on reconstruction quality. Approach: Using EEGdenoiseNet, we constructed a synthetic benchmark of 4500 single-channel 2 s segments (125 Hz; T = 250) by mixing clean EEG with ocular (EOG) and\/or cranial EMG exemplars at noise-to-signal ratios (NSRs) spanning \u221210 to +10 dB (floor \u221210 dB denotes an absent modality). We evaluated variational mode decomposition (VMD), singular spectrum analysis (SSA), discrete wavelet transform (DWT), and CEEMDAN by decomposing each mixture and reconstructing the clean EEG using a bounded nonnegative linear combination of components obtained via constrained least squares (the oracle). Main results: Under this oracle benchmark, SSA achieved the lowest reconstruction error in most tested conditions, while DWT tended to rank best in milder ocular regimes; VMD performance improved, with an increased mode count at higher computational cost. CEEMDAN exhibited higher latency dominated by ensemble settings. Significance: These results should be interpreted as decomposition-level upper bounds under controlled mixtures, not field-ready denoising performance. The benchmark provides a tool with which to compare representational recoverability across decompositions and to inform the subsequent design of practical component-selection strategies.<\/jats:p>","DOI":"10.3390\/s26092581","type":"journal-article","created":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T12:54:08Z","timestamp":1776862448000},"page":"2581","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Oracle Upper Bounds on Clean-EEG Recoverability from Single-Channel Decompositions Under EOG\/EMG Contamination"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0171-3940","authenticated-orcid":false,"given":"Usman Qamar","family":"Shaikh","sequence":"first","affiliation":[{"name":"Institute of Biomedical Technologies, Auckland University of Technology, Auckland 1010, New Zealand"},{"name":"Department of Electrical and Electronic Engineering, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7908-3053","authenticated-orcid":false,"given":"Anubha Manju","family":"Kalra","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Technologies, Auckland University of Technology, Auckland 1010, New Zealand"},{"name":"Department of Electrical and Electronic Engineering, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0612-1036","authenticated-orcid":false,"given":"Andrew","family":"Lowe","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Technologies, Auckland University of Technology, Auckland 1010, New Zealand"},{"name":"Department of Mechanical Engineering, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8752-7224","authenticated-orcid":false,"given":"Imran Khan","family":"Niazi","sequence":"additional","affiliation":[{"name":"Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland 1060, New Zealand"},{"name":"Department of Health Science and Technology, Aalborg University, 9200 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7134","DOI":"10.1038\/s41598-019-43594-9","article-title":"Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury","volume":"9","author":"Ofner","year":"2019","journal-title":"Sci. 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