Projects Advanced Reality Lab (ARL)

Members of Advanced Reallity Lab team are among the best researchers and experts in their field. Our Research projects are ground-breaking and at the front of academic research in the fields of virtual and augmented reality.

Physiological Interfaces in Virtual Reality



Estimating Fear Tendency from Physiological Responses using virtual stimuli - For psychotherapy and similar applications it is critical to be able to measure the responses to the Virtual Reality, and physiology may be even more useful than subjective reporting. This is even more critical for closed-loop applications advocated in affective computing. We have induced four types of fearful stimuli in VR, and systematically measured reported phobia using questionnaires and physiology. Our expectation was that high phobia would result in a high degree of fear in the VR, and also high physiological arousal. Our findings are that this is not always the case.



Towards Reliable Monitoring and Machine Induced Regulation of Stress in Every Day Life using Highly Immersive Virtual Reality (2017-2019)., In collaboration with Dr. Yulia Golland, School of Psychology.


A timely intervention to manage daily stress can significantly improve our physiological and psychological health and well-being. A key ingredient in most intervention methods is measurement of daily stress, but this has proved challenging. The "golden standard" is often considered to be cortisol levels, but these are not easy to determine, and have a very low temporal resolution. Subjective reports have found to correlate poorly (0.26-0.36) with cortisol levels. Therefore, there is a growing interest in developing accurate measurements of stress based on neurophysiology. A sensor-based continuous measurement of stress in daily life would be a necessary building block for a wide range of applications and scenarios (often referred to as "affective computing"), including many interventions for wellness.


Our first and main goal is to make substantial progress towards accurate and reliable continuous measurement of stress using neurophysiological signals in everyday life, based on a data-driven machine learning approach. We use immersive virtual reality to simulate everyday life situations, retaining both ecological validity and experimental control. Our next goal is to harness this measurement for regulating stress. Given that we live in a digital world (soon to become even more pervasive with IoT devices) we will ask – can machines take a proactive role in helping to regulate people's stress levels?