Attention Level

Attention level estimation aims to objectively measure a person's cognitive engagement with a task, a crucial factor in fields like education and human-robot interaction. Current research focuses on developing robust multimodal systems that integrate various data sources, such as facial expressions, eye movements, head pose, and EEG signals, often employing convolutional neural networks (CNNs) and transformer-based architectures for analysis and classification. These advancements hold significant promise for improving e-learning platforms, enhancing human-robot collaboration safety, and providing valuable insights into cognitive processes in various contexts.