edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms


  • Roberto Daza Universidad Autónoma de Madrid
  • Aythami Morales Universidad Autónoma de Madrid
  • Ruben Tolosana Universidad Autónoma de Madrid
  • Luis F. Gomez Universidad Autónoma de Madrid
  • Julian Fierrez Universidad Autónoma de Madrid
  • Javier Ortega-Garcia Universidad Autónoma de Madrid




E-learning Platforms, E-learning, Machine Learning, Biometrics, Behavioral Understanding, Human-Computer Interaction


We present edBB-Demo, a demonstrator of an AI-powered research platform for student monitoring in remote education. The edBB platform aims to study the challenges associated to user recognition and behavior understanding in digital platforms. This platform has been developed for data collection, acquiring signals from a variety of sensors including keyboard, mouse, webcam, microphone, smartwatch, and an Electroencephalography band. The information captured from the sensors during the student sessions is modelled in a multimodal learning framework. The demonstrator includes: i) Biometric user authentication in an unsupervised environment; ii) Human action recognition based on remote video analysis; iii) Heart rate estimation from webcam video; and iv) Attention level estimation from facial expression analysis.




How to Cite

Daza, R., Morales, A., Tolosana, R., Gomez, L. F., Fierrez, J., & Ortega-Garcia, J. (2023). edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16422-16424. https://doi.org/10.1609/aaai.v37i13.27066