Abstract
Purpose :
To study blink rate in adults in awakening and sleepiness conditions. Fatigue is difficult to define. The evaluation of blink rate can lead to a precise indicator of fatigue. Blink frequency as indicator of sleepiness and alterations in performance can lead to a simple measurement useful in everyday living.
Methods :
The study included 8 voluntary adults (range 31 to 80 years-old) with written consent signed and was conducted in compliance with the "Declaration of Helsinki". Subjects were required to read text during 15minutes in specific lighting conditions. The primary phase of 5mn was evaluated in photopic conditions. After 5minute the last 10minutes were evaluated in scotopic conditions for 6 subjects lying down to get them drowsy. Subjects were not required to perform any operation other than natural reading. The subject’s face was filmed by a video camera and monitored by an expert observer, resulting in 16 recordings. Blink rate was evaluated for the first consecutive 5-minute periods in photopic conditions and the last consecutive 5-minute periods in scotopic conditions. The two subjects at the end of the task were alert and the 6 subjects showed some marked signs of sleepiness.
Results :
Blink rate was evaluated for the first consecutive 5minutes and the last consecutive 5minutes, and then compared. Average blink varied from 3 per minute to 13 per minute. Average blink rate in the 2 subjects was unchanged (respectively 3 and 4 blink per minute). Of the 6 subjects, increase of blink rate has varied from 13% to 71% (41% mean increasing blink frequency).
Conclusions :
There was considerable variability in blinking for the different subjects. However there was a tendency for an increase in blink frequency with sleepiness of subjects. Blink rate increase thus appears to be a robust measure of fatigue effects. The evaluation of blink frequency is linked to a driver’s ability to react to environmental stimuli. Larger studies are needed to get more data on blink rate in different situations. Development of drowsiness-detection algorithms could be useful associated with specific devices adapted to everyday life.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.