1256 A pilot study to identify the factors favouringhypovigilance by drowsiness measured by a non-invasive monitoring device under real conditions. (24th April 2018)

• Record Type: Journal Article
• Authors: El Fassi, M; Joris, J; François, C; Wertz, J; Godderis, L; Ghuysen, A
• Is Part Of: Occupational and environmental medicine. Volume 75(2018)Supplement 2
• Page Start: A23
• Page End: A23
• Publication Date: 2018-04-24
• Subjects: drowsiness -- road hazard -- predictive factors; Medicine, Industrial -- Periodicals; Environmental health -- Periodicals; 616.980305
• DOI: 10.1136/oemed-2018-ICOHabstracts.68
• Languages: English
• ISSNs: 1351-0711

Abstract

Abstract : Introduction: Every year, more than one million people die on the road worldwide, 20% of these deadly accidents being caused by hypovigilance due to drowsiness. Methods: Our study tested the feasibility of monitoring the level of sleepiness under real driving conditions, using the non-invasive Phasya monitoring device. Data were collected in 24 bus drivers' records, from November 3 to December 15, 2016. Continuous measurement of the level of drowsiness with Phasya device, allowed to scale this level from 0 (awake) to 10 (drowsy) by analysing ocular movements extracted from images of the eye. In addition, we determined individual and occupational risk factors potentially associated with drowsiness. Individual variables included, biometric, health-related data and the sleep profile. Occupational factors included the duration and distance travelled. Diurnal sleepiness was self-assessed with the Epworth Sleepiness Scale. Results: We recorded 31 journeys for a total of 6070 kilometres and 193 hours of driving. The drowsiness monitored was greater than or equal to 5 over 10 in 11.98% of the data collected, which is equivalent to more than 23 cumulative hours and more than 700 kilometres travelled being drowsy. Health behaviours such as regular physical activity and the absence of overweight showed non-significant protective patterns. However, diurnal sleepiness was highly associated with the level of drowsiness (r=0, 74) (p=0, 02). Likewise, the duration of journeys was also highly associated with increasing sleepiness (r=0, 25, p<0, 0005). Conclusion: This study demonstrates that the Phasya monitoring device is able to measure drowsiness under real driving conditions. Our results emphasise the need for prevention campaigns to include early detection of risk factors, as well as optimising the care of drivers suffering from drowsiness. We suggest that imposition of breaks based on drivers' drowsiness level and driving time. Giving a break after 2 hours of driving appears reasonable in terms of safety.