This site supports my Doctor of Professional Practice research at Universiti Teknologi Malaysia. The work explores how teachers in e-classrooms can better understand student engagement using contactless physiological signals extracted from standard cameras on existing devices.
In distance learning and e-classroom settings, teachers often have limited visibility of how engaged students are during live sessions. This research examines how engagement can be inferred using signals that are already present in typical learning setups.
Using a standard camera on an existing device, subtle physiological changes can be observed from facial videos. The goal is to explore contactless methods that support teacher decision making without adding extra hardware.
This website presents selected background and development notes related to the ongoing Doctor of Professional Practice research.
Only high-level information is shared here. Detailed methods, results, and technical components will not be fully published until the research is formally released through journal publication or patent protection.
The site functions as a controlled research showcase and may evolve as the study progresses.
Our initial research focuses on contactless physiological and behavioral signal analysis using AI. We explore how subtle, natural signals can support insights into human states.
Learn about our pilot programsMonitoring learning fatigue, attention, and engagement to improve student wellbeing without wearable devices.
Understanding human-states in non-clinical environments to inform operational decisions and policy planning.
We engage partners as co-researchers. Our collaborative model ensures solutions are ethically governed and context-specific.