Identifying Relationships between Physiological Measures and Evaluation Metrics for 3D Interaction Techniques

Abstract

Abstract. This project aims to present a methodology to study the relationships between physiological measures and evaluation metrics for 3D interaction techniques using methods for multivariate data analysis. Physiological responses, such as heart rate and skin conductance, offer objective data about the user stress during interaction. This could be useful, for instance, to evaluate qualitative aspects of interaction techniques without relying on solely subjective data. Moreover, these data could contribute to improve task performance analysis by measuring different responses to 3D interaction techniques. With this in mind, we propose a methodology that defines a testing protocol, a normalization procedure and statistical techniques, considering the use of physiological measures during the evaluation process. A case study comparison between two 3D interaction techniques (ray-casting and HOMER) shows promising results, pointing to heart rate variability, as measured by the NN50 parameter, as a potential index of task performance. Further studies are needed in order to establish guidelines for evaluation processes based on welldefined associations between human behaviors and human actions realized in 3D user interfaces.

Cybersickness in current-generation virtual reality head-mounted displays: systematic review and outlook

“…For example, CS has been reported to increase cortisol levels in saliva (Kennedy et al 2010) or to cause tachycardia (Hu and Stern 1999;Imai et al 2006). Furthermore, it seems that CS often correlates with facial pallor, sweating, and respiration rate variations (Johnson 2005) as well as with heart rate variability (Rieder et al 2011). Unfortunately, individual differences in autonomic regulation and variations caused by the experience but not by a negative reaction to it (sickness) make it challenging to predict CS based on variables such as the heart rate or respiration rate (Kiryu and Iijima 2014).…”

From Physiological Measures to an Automatic Recognition System of Stress

“…Physiological measurements, unlike subjective measurements, can provide real-time and objective data [3]. Thereby, many studies have explored the link between physiological responses and stress.…”

Identifying Cybersickness through Heart Rate Variability alterations

“…This stresses the importance shown by previous research on attempting to move to more objective measurement methods, such as postural sway (Chardonnet, Mirzaei, and Merienne 2017) or biosignals. Previous studies have reported for cybersickness to increase the levels of cortisol in saliva (Kennedy, Drexler, and Kennedy 2010), cause tachygastria, correlate with sweating and respiratory rate variations (Johnson 2005) heart rate variability (Gavgani, Hodgson, and Nalivaiko 2017;Malińska et al 2015;Nakagawa 2015;Rieder, Kristensen, and Pinho 2011) and galvanic skin response (GSR) (Gavgani et al 2017). Other studies state that the onset of cybersickness is induced by specific factors (or triggers), but the increase in cybersickness depends on individual differences in autonomic regulation, which makes it difficult to detect it (Kiryu and Iijima 2014).…”