We present edBB-Demo, a demonstrator of an AI-powered research platform for student monitoring in remote education.
The experimental framework is carried out using a public multimodal database for eye blink detection and attention level estimation called mEBAL, which comprises data from 38 students and multiples acquisition sensors, in particular, i) an electroencephalogram (EEG) band which provides the time signals coming from the student's cognitive information, and ii) RGB and NIR cameras to capture the students face gestures.
This work presents mEBAL, a multimodal database for eye blink detection and attention level estimation.
In this study we estimate the heart rate from face videos for student assessment.
We present a platform for student monitoring in remote education consisting of a collection of sensors and software that capture biometric and behavioral data.