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However, it has been reported that the accident rate of UCAVs is much higher than that of manned combat aerial vehicles. One of the main reasons for the high accident rate of UCAVs is the hypovigilance problem which refers to the decrease in vigilance levels of UCAV operators while maneuvering. In this paper, we propose hypovigilance detection models for UCAV operators based on EEG signal to minimize the number of occurrences of hypovigilance. To enable detection, we have applied hidden Markov models (HMMs), two of which are used to indicate the operators\u2019 dual states, normal vigilance and hypovigilance, and, for each operator, the HMMs are trained as a detection model. To evaluate the efficacy and effectiveness of the proposed models, we conducted two experiments on the real-world data obtained by using EEG-signal acquisition devices, and they yielded satisfactory results. By utilizing the proposed detection models, the problem of hypovigilance of UCAV operators and the problem of high accident rate of UCAVs can be addressed.<\/jats:p>","DOI":"10.1155\/2014\/567645","type":"journal-article","created":{"date-parts":[[2014,5,20]],"date-time":"2014-05-20T17:13:19Z","timestamp":1400605999000},"page":"1-13","source":"Crossref","is-referenced-by-count":9,"title":["Hypovigilance Detection for UCAV Operators Based on a Hidden Markov Model"],"prefix":"10.1155","volume":"2014","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7239-5118","authenticated-orcid":true,"given":"Yerim","family":"Choi","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Namyeon","family":"Kwon","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of 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