{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:01:41Z","timestamp":1792785701272,"version":"4.5.0"},"reference-count":31,"publisher":"IOP Publishing","issue":"5","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"tdm","delay-in-days":7,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"National Natural Science Foundation of China","award":["82271234"],"award-info":[{"award-number":["82271234"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Jiangxi Province thousands of Plans","award":["jxsq2019201023"],"award-info":[{"award-number":["jxsq2019201023"]}]},{"name":"Natural Science Foundation of Jiangxi Province","award":["20242BAB26133"],"award-info":[{"award-number":["20242BAB26133"]}]},{"name":"Jiangxi Province Key Laboratory of Anesthesiology","award":["2024SSY06161"],"award-info":[{"award-number":["2024SSY06161"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["J. Neural Eng."],"published-print":{"date-parts":[[2026,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Postoperative delirium (POD) is a common perioperative complication involving central nervous system dysfunction, particularly among critically ill and elderly patients, yet its rapid and objective detection remains challenging in clinical settings. To develop and evaluate a lightweight, interpretable electroencephalography (EEG)-based deep learning framework for POD detection that remains accurate under sparse-electrode acquisition and practical for bedside or portable deployment.\n                    <jats:italic>Approach.<\/jats:italic>\n                    We propose Helix Fusion HarmonyNet (HFHN), a transform-domain architecture that explicitly separates EEG representations into amplitude and phase pathways. HFHN integrates multi-head self-attention, convolutional local feature extraction, learnable sinusoidal positional encoding, and controlled cross-pathway fusion to jointly model spectral intensity, temporal synchrony, local patterns, and long-range dependencies. The framework was evaluated against representative CNN-, Transformer-, and EEG-specific deep learning models across signal domains, fusion strategies, electrode configurations, ablation settings, and deployment-oriented efficiency tests.\n                    <jats:italic>Main Results.<\/jats:italic>\n                    In Fourier-domain POD detection, HFHN achieved 100% accuracy, precision, specificity,\n                    <jats:italic>F<\/jats:italic>\n                    1-score, and sensitivity. Ablation analysis confirmed the importance of amplitude\u2013phase interaction, as removing cross-pathway fusion reduced accuracy from 100% to 95.38%. Under sparse-channel conditions, HFHN maintained 99.42% accuracy and a 99.33%\n                    <jats:italic>F<\/jats:italic>\n                    1-score with 8 electrodes, and 94.08% accuracy and a 93.26%\n                    <jats:italic>F<\/jats:italic>\n                    1-score with only 4 high-attention electrodes. Reducing the number of electrodes from 60 to 4 decreased FLOPs from 16.95 G to 0.99 G, while inference latency remained below 3.09 ms.\n                    <jats:italic>Significance.<\/jats:italic>\n                    HFHN provides an accurate, interpretable, and computationally efficient solution for EEG-based POD detection. Its robustness under sparse-channel acquisition and low-latency performance support potential integration into portable or bedside EEG systems for rapid postoperative monitoring in wards and intensive care units.\n                  <\/jats:p>","DOI":"10.1088\/1741-2552\/aea18f","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T22:51:00Z","timestamp":1788389460000},"page":"056044","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Harmonizing complexity and efficiency: Helix Fusion HarmonyNet\u2019s breakthrough in EEG-based postoperative delirium recognition"],"prefix":"10.1088","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2798-228X","authenticated-orcid":true,"given":"Conghui","family":"Wei","sequence":"first","affiliation":[{"name":"The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou Rehabilitation Hospital, Gusu School, Nanjing Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuqin","family":"Rao","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4493-6379","authenticated-orcid":true,"given":"Bo","family":"Hu","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences"},{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Zeng","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengcheng","family":"Yi","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huasu","family":"Shao","sequence":"additional","affiliation":[{"name":"The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou Rehabilitation Hospital, Gusu School, Nanjing Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianqian","family":"Tan","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Xie","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyuan","family":"Fang","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Gong","sequence":"additional","affiliation":[{"name":"The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou Rehabilitation Hospital, Gusu School, Nanjing Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6718-6490","authenticated-orcid":true,"given":"Fuzhou","family":"Hua","sequence":"additional","affiliation":[{"name":"The Second Affiliated Hospital, Jiangxi medical College, Nanchang University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"key":"jneaea18fbib1","first-page":"448","type":"journal-article","article-title":"Postoperative delirium","volume":"77","author":"Whitlock","year":"2011","journal-title":"Minerva Anestesiol."},{"key":"jneaea18fbib2","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1017\/s1041610202008499","type":"journal-article","article-title":"Confusion\/delirium following cataract surgery: an incidence study of 1-year duration","volume":"14","author":"Milstein","year":"2002","journal-title":"Int. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-03-29","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-08-31","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-08","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}