Analysis of Pre-evacuation Time and EEG for Fire Alarm when Wearing ANC Earphones
Authors: Ji Won Gu, Ji-Hoon Hwang, Ryun-Seok Oh, Jun-Ho Choi
Abstract: With the development of mobile technology and the progress of an Untact society, the number of people who listen to lectures or music in various urban environments is increasing. In response to such an increase in demand, Active Noise Canceling(ANC) earphones that remove ambient background noise or static and also enable stable listening have been developed, and the earphones are enjoying great popularity. However, these ANC earphones can put the user in a dangerous situation at any time because they block even major alarm sounds such as a car horn or fire alarm. In this study, 10 men and women in their 20s, who frequently use ANC earphones, were asked to listen to music by wearing ANC earphones without prior notification of the fact that a fire alarm sound was transmitted. After that, the fire alarm bell or emergency broadcast sound was randomly generated for them to recognise the fire situation, and the time it took to start evacuation was measured. And in all these processes, EEG was simultaneously measured to analyse changes in emotions such as arousal responses felt by the experimental participants As a result of the experiment, it was found that the case of transmitting an emergency broadcast made the participants start evacuation approximately 23 seconds faster than the case of sounding the fire alarm bell. However, as a result of correlation analysis with EEG values indicating arousal responses such as tension, irritability, and nervousness, the significance probability(p-value) was 0.825, indicating that there is no statistically significant correlation. Therefore, it was found that the participants’ awareness of the fire alarm sound decreased when wearing ANC earphones regardless of the types of the fire alarm whether it was an alarm bell or an emergency broadcast.
Keywords: Active Noise Cancelling Earphone, ANC, Evacuation, Fire Alarm, Electroencephalogram, EEG
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