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

arXiv: https://arxiv.org/abs/2211.09210 · HTML: https://mlsanity.com/paper/2211.09210/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 13 references that are in the map.
- First posted on arXiv 16 Nov 2022.

## Builds on (most cited first, 8 of 8)

- [SensitiveLoss: Improving Accuracy and Fairness of Face Representations with Discrimination-Aware Deep Learning](https://mlsanity.com/paper/2004.11246/) (2020)
- [Biometrics: Trust, but Verify](https://mlsanity.com/paper/2105.06625/) (2021)
- [mEBAL: A Multimodal Database for Eye Blink Detection and Attention Level Estimation](https://mlsanity.com/paper/2006.05327/) (2020)
- [TypeNet: Deep Learning Keystroke Biometrics](https://mlsanity.com/paper/2101.05570/) (2021)
- [edBB: Biometrics and Behavior for Assessing Remote Education](https://mlsanity.com/paper/1912.04786/) (2019)
- [ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning](https://mlsanity.com/paper/2112.09165/) (2021)
- [Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBB](https://mlsanity.com/paper/2006.00825/) (2020)
- [RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild](https://mlsanity.com/paper/2011.01890/) (2020)

## Built on by (most cited first, 18 of 18)

- [M2LADS: A System for Generating MultiModal Learning Analytics Dashboards in Open Education](https://mlsanity.com/paper/2305.12561/) (2023)
- [VAAD: Visual Attention Analysis Dashboard applied to e-Learning](https://mlsanity.com/paper/2405.20091/) (2024)
- [A multimodal dataset for understanding the impact of mobile phones on remote online virtual education](https://mlsanity.com/paper/2412.14195/) (2024)
- [PBa-LLM: Privacy- and Bias-aware NLP using Named-Entity Recognition (NER)](https://mlsanity.com/paper/2507.02966/) (2025)
- [Biometrics and Behavior Analysis for Detecting Distractions in e-Learning](https://mlsanity.com/paper/2405.15434/) (2024)
- [mEBAL2 Database and Benchmark: Image-based Multispectral Eyeblink Detection](https://mlsanity.com/paper/2309.07880/) (2023)
- [DeepFace-Attention: Multimodal Face Biometrics for Attention Estimation with Application to e-Learning](https://mlsanity.com/paper/2408.05523/) (2024)
- [SMARTe-VR: Student Monitoring and Adaptive Response Technology for e-Learning in Virtual Reality](https://mlsanity.com/paper/2501.10977/) (2025)
- [AI-based Multimodal Biometrics for Detecting Smartphone Distractions: Application to Online Learning](https://mlsanity.com/paper/2506.17364/) (2025)
- [MOSAIC-F: A Framework for Enhancing Students' Oral Presentation Skills through Personalized Feedback](https://mlsanity.com/paper/2506.08634/) (2025)
- [EduEVAL-DB: A Role-Based Dataset for Pedagogical Risk Evaluation in Educational Explanations](https://mlsanity.com/paper/2602.15531/) (2026)
- [M2LADS Demo: A System for Generating Multimodal Learning Analytics Dashboards](https://mlsanity.com/paper/2502.15363/) (2025)
- [Enhancing Online Learning by Integrating Biosensors and Multimodal Learning Analytics for Detecting and Predicting Student Behavior: A Review](https://mlsanity.com/paper/2509.07742/) (2025)
- [AIriskEval-edu: New Dataset for Risk Assessment in AI-mediated K-12 Educational Explanations](https://mlsanity.com/paper/2607.01934/) (2026)
- [TRACE: A Generalizable Drift Detector for Streaming Data-Driven Optimization](https://mlsanity.com/paper/2512.07082/) (2025)
- [A Multimodal Dataset of Student Oral Presentations with Sensors and Evaluation Data](https://mlsanity.com/paper/2601.07576/) (2026)
- [Real-Time Multimodal Data Collection Using Smartwatches and Its Visualization in Education](https://mlsanity.com/paper/2512.02651/) (2025)
- [AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations](https://mlsanity.com/paper/2607.25634/) (2026)

## Abstract (arXiv)

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.