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Identifying the Impact of Noise on Anomaly Detection through Functional Near-Infrared Spectroscopy (fNIRS) and Eye-tracking

Gabbard, Ryan Dwight
http://rave.ohiolink.edu/etdc/view?acc_num=wright1501711461736129

Abstract Details

2017, Master of Science in Biomedical Engineering (MSBME), Wright State University, Biomedical Engineering.
Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance (ISR) operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision making process. In this study the effects of different noise stimuli on analysts’ performance and workload in anomaly detection were investigated by simulating a noisy work environment. Functional near infrared spectroscopy (fNIRS) was utilized to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbD) concentration changes in the prefrontal cortex (PFC), as well as behavioral measures which include eye-tracking, reaction time, and accuracy rate. It was found that HbO for some of the channels analyzed were significantly different across noise types (p<0.05). The results indicated that HbO activation for short intermittent noise stimuli was greater in the PFC compared to long intermittent noises. Target transition rates were also significantly higher (p<0.05) for no noise conditions compared to noise filled environments. These approaches using fNIRS in conjunction with an understanding of the impact on human analysts in anomaly detection, could potentially lead to better performance by optimizing work environments.
Mary Fendley, Ph.D. (Advisor)
Nasser Kashou, Ph.D. (Committee Member)
Rik Warren, Ph.D. (Committee Member)
114 p.
Biomedical Engineering; Neurosciences
functional near-infrared spectroscopy; workload; prefrontal cortex; eye tracking; noise; anomaly detection

Recommended Citations

Citations

  • Gabbard, R. D. (2017). Identifying the Impact of Noise on Anomaly Detection through Functional Near-Infrared Spectroscopy (fNIRS) and Eye-tracking [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1501711461736129

    APA Style (7th edition)

  • Gabbard, Ryan. Identifying the Impact of Noise on Anomaly Detection through Functional Near-Infrared Spectroscopy (fNIRS) and Eye-tracking. 2017. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1501711461736129.

    MLA Style (8th edition)

  • Gabbard, Ryan. "Identifying the Impact of Noise on Anomaly Detection through Functional Near-Infrared Spectroscopy (fNIRS) and Eye-tracking." Master's thesis, Wright State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1501711461736129

    Chicago Manual of Style (17th edition)

wright1501711461736129
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© 2017, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.