{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T18:07:33Z","timestamp":1772042853114,"version":"3.50.1"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T00:00:00Z","timestamp":1718064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Sci."],"abstract":"<jats:p>This work described a novel non-contact, wearable, real-time eye blink detection solution based on capacitive sensing technology. A custom-built prototype employing low-cost and low-power consumption capacitive sensors was integrated into standard glasses, with a copper tape electrode affixed to the frame. The blink of an eye induces a variation in capacitance between the electrode and the eyelid, thereby generating a distinctive capacitance-related signal. By analyzing this signal, eye blink activity can be accurately identified. The effectiveness and reliability of the proposed solution were evaluated through five distinct scenarios involving eight participants. Utilizing a user-dependent detection method with a customized predefined threshold value, an average precision of 92% and a recall of 94% were achieved. Furthermore, an efficient user-independent model based on the two-bit precision decision tree was further applied, yielding an average precision of 80% and an average recall of 81%. These results demonstrate the potential of the proposed technology for real-world applications requiring precise and unobtrusive eye blink detection.<\/jats:p>","DOI":"10.3389\/fcomp.2024.1394397","type":"journal-article","created":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T18:16:46Z","timestamp":1718129806000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Energy-efficient, low-latency, and non-contact eye blink detection with capacitive sensing"],"prefix":"10.3389","volume":"6","author":[{"given":"Mengxi","family":"Liu","sequence":"first","affiliation":[]},{"given":"Sizhen","family":"Bian","sequence":"additional","affiliation":[]},{"given":"Zimin","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Paul","family":"Lukowicz","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2024,6,11]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","DOI":"10.1109\/ALLERTON.2019.8919795","article-title":"\u201cBlink: A fully automated unsupervised algorithm for eye-blink detection in eeg signals,\u201d","volume-title":"2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","author":"Agarwal","year":"2019"},{"key":"B2","doi-asserted-by":"publisher","first-page":"93","DOI":"10.3390\/info9040093","article-title":"Robust eye blink detection based on eye landmarks and savitzky-golay filtering","volume":"9","author":"Al-gawwam","year":"2018","journal-title":"Information"},{"key":"B3","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1109\/IVS.2019.8813871","article-title":"\u201cCamera-based eye blink detection algorithm for assessing driver drowsiness,\u201d","volume-title":"2019 IEEE Intelligent Vehicles Symposium (IV)","author":"Baccour","year":"2019"},{"key":"B4","first-page":"247","article-title":"\u201cA systematic study of the influence of various user specific and environmental factors on wearable human body capacitance sensing,\u201d","volume-title":"EAI International Conference on Body Area Networks","author":"Bian","year":"2021"},{"key":"B5","first-page":"1","article-title":"\u201cPassive capacitive based approach for full body gym workout recognition and counting,\u201d","volume-title":"2019 IEEE International Conference on Pervasive Computing and Communications (PerCom)","author":"Bian","year":"2019"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3643555","article-title":"Body-area capacitive or electric field sensing for human activity recognition and human-computer interaction: a comprehensive survey","volume":"8","author":"Bian","year":"2024","journal-title":"arXiv"},{"key":"B7","first-page":"26","article-title":"\u201cCapfloor-a flexible capacitive indoor localization system,\u201d","volume-title":"International Competition on Evaluating AAL Systems through Competitive Benchmarking","author":"Braun","year":"2011"},{"key":"B8","doi-asserted-by":"crossref","first-page":"925","DOI":"10.23919\/EuMC48046.2021.9338116","article-title":"\u201cHead motion and eyes blinking detection: A mm-wave radar for assisting people with neurodegenerative disorders,\u201d","volume-title":"2020 50th European Microwave Conference (EuMC)","author":"Cardillo","year":"2021"},{"key":"B9","doi-asserted-by":"publisher","first-page":"116073","DOI":"10.1016\/j.eswa.2021.116073","article-title":"Efficient machine learning approach for volunteer eye-blink detection in real-time using webcam","volume":"188","author":"de Lima Medeiros","year":"2022","journal-title":"Expert Syst. 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