Blinking supervision in a working environment

The health of the ocular surface requires blinks of the eye to be frequent in order to provide moisture and to renew the tear film. However, blinking frequency has been shown to decrease in certain conditions such as when subjects are conducting tasks with high cognitive and visual demands. These co...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of biomedical optics Jg. 21; H. 2; S. 25005
Hauptverfasser: Morcego, Bernardo, Argilés, Marc, Cabrerizo, Marc, Cardona, Genís, Pérez, Ramon, Pérez-Cabré, Elisabet, Gispets, Joan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.02.2016
Schlagworte:
Algorithms
Blinking - physiology
Dry Eye Syndromes
Humans
Image Processing, Computer-Assisted - methods
Iris - physiology
Workplace
ISSN:1560-2281
Online-Zugang:Weitere Angaben
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The health of the ocular surface requires blinks of the eye to be frequent in order to provide moisture and to renew the tear film. However, blinking frequency has been shown to decrease in certain conditions such as when subjects are conducting tasks with high cognitive and visual demands. These conditions are becoming more common as people work or spend their leisure time in front of video display terminals. Supervision of blinking frequency in such environments is possible, thanks to the availability of computer-integrated cameras. Therefore, the aim of the present study is to develop an algorithm for the detection of eye blinks and to test it, in a number of videos captured, while subjects are conducting a variety of tasks in front of the computer. The sensitivity of the algorithm for blink detection was found to be of 87.54% (range 30% to 100%), with a mean false-positive rate of 0.19% (range 0% to 1.7%), depending on the illumination conditions during which the image was captured and other computer–user spatial configurations. The current automatic process is based on a partly modified pre-existing eye detection and image processing algorithms and consists of four stages that are aimed at eye detection, eye tracking, iris detection and segmentation, and iris height/width ratio assessment.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1560-2281
DOI:10.1117/1.JBO.21.2.025005