Fire exit signs: The use of neurological activity analysis for quantitative evaluations on their perceptiveness in a virtual environment. (May 2016)

• Record Type: Journal Article
• Authors: Occhialini, Martina; Bernardini, Gabriele; Ferracuti, Francesco; Iarlori, Sabrina; D'Orazio, Marco; Longhi, Sauro
• Is Part Of: Fire safety journal. Volume 82(2016:May)
• Page Start: 63
• Page End: 75
• Publication Date: 2016-05
• Subjects: Evacuation signs identification -- Fire evacuation signs -- EEG techniques -- Wayfinding in evacuation condition -- Fire evacuation in buildings; Fire prevention -- Periodicals; Incendies -- Prévention -- Recherche -- Périodiques; Fire prevention -- Research; Periodicals; 628.92205
• DOI: 10.1016/j.firesaf.2016.03.003
• Languages: English
• ISSNs: 0379-7112

Abstract

Abstract: Emergency signs represent the easiest way to assist a person during an emergency building evacuation, such as in a fire. However, previous studies show that signs can also not be correctly perceived (because of: smoke/lighting conditions, sign positions in relation to individual's position, pictograms dimensions), consequently becoming useless. This study focuses on the effectiveness of exit signs, in terms of type and position. The related numerical quantification is founded on an objective experimental neurological method. A neurological stimulus (P300) is generated when the individual understands the meaning of the sign. It is so possible to objectively evaluate by using a neuro-headset the performance of each subject in terms of perceptual attention. The use of similar direct data overlooks errors connected to conscious or unconscious individual mediation in answers. Evacuation motion simulations are performed using a virtual reality environment because of limits in the neuro-headset use when walking. Two types of exit signs (reflective and photoluminescent) are tested considering different positions and environmental conditions (illuminated and not). The sign identification distance is retrieved and compared to results of real-world experiments. Finally, the sign effectiveness is also inquired in terms of statistical P300 presence on the analysed sample. Highlights: The EEG signal is analyzed for quantifying the evacuation sign identification task. An attention stimulus (P300) is noticed when the person unconsciously identifies the sign. The sign effectiveness can be expressed in terms of distances of unconscious and conscious identification. Effectiveness of reflective and PLM fire evacuation signs is inquired in different positions.