{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T13:08:23Z","timestamp":1778159303479,"version":"3.51.4"},"reference-count":73,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T00:00:00Z","timestamp":1668384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PKU-OPPO Innovation Fund","award":["BO202103"],"award-info":[{"award-number":["BO202103"]}]},{"name":"PKU-OPPO Innovation Fund","award":["HP2021-11-50102"],"award-info":[{"award-number":["HP2021-11-50102"]}]},{"DOI":"10.13039\/501100009399","name":"Hygiene and Health Development Scientific Research Fostering Plan of Haidian District Beijing","doi-asserted-by":"publisher","award":["BO202103"],"award-info":[{"award-number":["BO202103"]}],"id":[{"id":"10.13039\/501100009399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009399","name":"Hygiene and Health Development Scientific Research Fostering Plan of Haidian District Beijing","doi-asserted-by":"publisher","award":["HP2021-11-50102"],"award-info":[{"award-number":["HP2021-11-50102"]}],"id":[{"id":"10.13039\/501100009399","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>It is essential to estimate the sleep quality and diagnose the clinical stages in time and at home, because they are closely related to and important causes of chronic diseases and daily life dysfunctions. However, the existing \u201cgold-standard\u201d sensing machine for diagnosis (Polysomnography (PSG) with Electroencephalogram (EEG) measurements) is almost infeasible to deploy at home in a \u201cubiquitous\u201d manner. In addition, it is costly to train clinicians for the diagnosis of sleep conditions. In this paper, we proposed a novel technical and systematic attempt to tackle the previous barriers: first, we proposed to monitor and sense the sleep conditions using the infrared (IR) camera videos synchronized with the EEG signal; second, we proposed a novel cross-modal retrieval system termed as Cross-modal Contrastive Hashing Retrieval (CCHR) to build the relationship between EEG and IR videos, retrieving the most relevant EEG signal given an infrared video. Specifically, the CCHR is novel in the following two perspectives. Firstly, to eliminate the large cross-modal semantic gap between EEG and IR data, we designed a novel joint cross-modal representation learning strategy using a memory-enhanced hard-negative mining design under the framework of contrastive learning. Secondly, as the sleep monitoring data are large-scale (8 h long for each subject), a novel contrastive hashing module is proposed to transform the joint cross-modal features to the discriminative binary hash codes, enabling the efficient storage and inference. Extensive experiments on our collected cross-modal sleep condition dataset validated that the proposed CCHR achieves superior performances compared with existing cross-modal hashing methods.<\/jats:p>","DOI":"10.3390\/s22228804","type":"journal-article","created":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T02:36:40Z","timestamp":1668479800000},"page":"8804","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Cross-Modal Contrastive Hashing Retrieval for Infrared Video and EEG"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4653-6022","authenticated-orcid":false,"given":"Jianan","family":"Han","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoxing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking University Third Hospital, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aidong","family":"Men","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingchao","family":"Chen","sequence":"additional","affiliation":[{"name":"National Institute of Health Data Science, Peking University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"597","DOI":"10.5664\/jcsm.2172","article-title":"Rules for scoring respiratory events in sleep: Update of the 2007 AASM manual for the scoring of sleep and associated events: Deliberations of the sleep apnea definitions task force of the American Academy of Sleep Medicine","volume":"8","author":"Berry","year":"2012","journal-title":"J. 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