Anxiety detection from Electrodermal Activity Sensor with movement & interaction during Virtual Reality Simulation

Abstract

Nowadays, Virtual Reality (VR) is bringing great benefits to Anxiety Disorder treatments, as well as to other brain cognitive dysfunctions. The advantage of VR is that it can provoke stimuli to the same degree as real-life situations. However, measurement methods of physiological changes caused by the aforementioned stimuli, which apply to VR Anxiety Disorder treatments, have not been examined extensively. As a result, clinicians who use biosignal sensors tend to ask their patients to remain motionless during simulations in order to achieve accurate measurements from the sensors. It is clear that this practice limits the level and range of benefits yielded when using VR simulation. As a consequence, the patients’ experience is restricted and so is the potential of the sensors’ application in the treatment methods. Furthermore, the data gathered from the sensors is handled using conventional analysis affecting the conclusions drawn about the patients’ state. This study aims to emphasise the importance of interacting with the stimuli during the VR treatment through the proposal of an Electrodermal Activity (EDA) Sensor System architecture that can be combined with VR simulations while still allowing the patient to move and interact within the Virtual Environment, without compromising the sensor’s measurements. Continuous Deconvolution Analysis is used to draw conclusions from the gathered biosensor data.