Are you afraid of heights and suitable for working at height?. (July 2019)

• Record Type: Journal Article
• Authors: Wang, Hong; Wang, Qiaoxiu; Hu, Fo
• Is Part Of: Biomedical signal processing and control. Volume 52(2019)
• Page Start: 23
• Page End: 31
• Publication Date: 2019-07
• Subjects: Fear of heights -- EEG -- VR -- Functional brain network; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.03.011
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The proposed paper combined VR technology and EEG together to assess the level of fear of heights. The frequency bands of interest and the regions of interest for fear of heights were found out. The proposed method has higher accuracy than traditional physiological measurements. Abstract: Fear of highs is one of the most common phobias all around world. It could affect people's life, work and health. Standing on high-altitude can lead to fear, anxiety or even panic to some people. In this paper, EEG method is creatively combined with VR technology to assess the severity of fear of heights. By doing time-frequency analysis, we found that alpha band (8–13 Hz) and high beta (20–30 Hz) are sensitive to fear of heights and frontal and parietotemporal areas are the regions of interests for fear of heights. Then using cross mutual information we built up a functional brain networks of every subject. And we extracted EEG features from the brain networks. Statistical analysis was performed to select the features based on significance of difference. Finally, we implemented classification. The performance of classifiers (the average accuracy could reach 94.44%) based on the proposed method was compared to the performance of classifiers based on the traditional physiological features. As a result, the proposed method was verified to be reliable and superior on estimating the severity of fear of heights. In addition, the system was tested on elderly people and came out with good performance. It turns out that the proposed system has good generalization capability and adaptability.