Quality of Experience Evaluation of Smart-Wearables: A Mathematical Modelling Approach

Abstract

A rapid growth in the smart-wearable industry is making it increasingly important to cater to the Quality of Experience (QoE) requirements of the end-users. In this work, we try to model the relationship between human experience and quality perception in relation to the smart-wearable segment. For this, the concepts of Quality of Data (QoD) and Quality of Information (QoI) are used. Step-counts and heart-rate measurement readings by the wearables are the parameters considered for evaluating the QoD, whereas perceived ease of use, perceived usefulness, and richness in information are the ones taken for evaluating the QoI. A subjective experiment comprising of 40 participants and 5 wearable devices is performed in a free-living condition in order to create the QoE model. We hypothesize QoE to be a function of QoD, and QoI and use a balanced weight technique to formulate the final model. R^2and adjusted-R^2values of 0.65 and 0.63 indicate a reasonable predictive power of the proposed scheme. Based upon the results appropriate recommendations are provided to the different smart-wearable vendors for improving their products, thereby ensuring a greater user-adoption.