1. Analysis of behavioural curves to classify iris images under the influence of alcohol, drugs, and sleepiness conditions.
- Author
-
Causa, Leonardo, Tapia, Juan E., Valenzuela, Andres, Benalcazar, Daniel, Droguett, Enrique Lopez, and Busch, Christoph
- Subjects
- *
IRIS (Eye) , *BEHAVIORAL assessment , *DROWSINESS , *WAKEFULNESS , *DRUG utilization , *DATABASES - Abstract
This paper proposes a new method to estimate behavioural curves from Near-Infra-Red (NIR) iris images for classifying Fitness for Duty using a biometric capture device. Fitness for Duty (FFD) techniques detect whether a subject is Fit to safely perform a given task, which means no reduced alertness condition and security, or the subject is unfit, that could impact a reduced alertness condition by sleepiness or consumption of alcohol and drugs. The analysis showed essential differences in pupil and iris behaviour to classify the workers in "Fit" or "Unfit" conditions. The best results can distinguish subjects robustly under alcohol, drug consumption, and sleep conditions. The Multi-Layer-Perceptron and Gradient Boosted Machine reached the best results in all groups with an overall accuracy for Fit and Unfit classes of 74.0% and 75.5%, respectively. These results open a new application for iris capture devices. • This work is a step forward in Iris biometric applications. • This research proposes a new database and method to detect Fitness for Duty. • This paper proposes a new method to estimate behavioural curves from iris images • Fitness for Duty allows us to detect Fit/Unfit subjects and save lives • This method classifies alcohol, drug, and sleepiness using an iris image. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF