title: Hypovigilance detection for UCAV operators based on a hidden Markov model.
abstract: With the advance of military technology, the number of unmanned combat aerial vehicles (UCAVs) has rapidly increased. 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' 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.
authors: Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea.
authors: Yerim
authors: 0000-0001-7239-5118
authors: Y
authors: Choi
authors: Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea.
authors: Namyeon
authors: N
authors: Kwon
authors: Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea.
authors: Sungjun
authors: 0000-0003-2677-9801
authors: S
authors: Lee
authors: Samsung Electronics, Suwon, Gyeonggi-do 443-742, Republic of Korea.
authors: Yongwook
authors: Y
authors: Shin
authors: Agency for Defense Development, Daejeon 305-152, Republic of Korea.
authors: Chuh Yeop
authors: CY
authors: Ryo
authors: Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea.
authors: Jonghun
authors: J
authors: Park
authors: Department of Industrial and Management Engineering, Hanyang University, Ansan, Gyeonggi-do 425-791, Republic of Korea.
authors: Dongmin
authors: 0000-0003-1785-4603
authors: D
authors: Shin
mesh_terms: D000063:Accidents, Traffic; D000328:Adult; D000401:Aircraft; D000465:Algorithms; D001288:Attention; D001334:Automobile Driving / Q000523:psychology*; D001921:Brain / Q000473:pathology*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008297:Male; D008390:Markov Chains; D008889:Military Personnel; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013647:Task Performance and Analysis; D014584:User-Computer Interface