A Study on QoE Estimation from Heart Rate Variability Using Machine Learning

摘要

Quality of Experience (QoE) depends on user's psychological condition. Hence, in order to estimate QoE, it is necessary to investigate the relationship between QoE and biological information. This research investigates whether QoE, when users watched audiovisual contents, can be estimated from the heart rate variability. Feature quantities used for estimation of QoE are spectral flux, spectral centroid, the average distance of Lorenz plot representing the variability of R-R interval and the area of ellipse approximating the Lorenz plot representing the magnitude of RRI. Hidden Markov model and recurrent neural network are used for estimation of QoE from the parameters of heart rate variability. From the results estimated by these methods, feature quantities and methods required for QoE estimation are discussed.