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

机译:智能耐用性经验评估质量:数学建模方法

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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. R2 and adjusted-R2 values 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.
机译:智能可穿戴行业的快速增长使迎合最终用户的经验质量(QoE)要求越来越重要。在这项工作中,我们试图模拟人类经验与与智能佩戴段相关的质量感知之间的关系。为此,使用数据质量(Qod)和信息质量(Qoi)的概念。可穿戴物的阶梯计数和心率测量读数是评估Qod的参数,而感知使用,感知有用性和丰富的资料是用于评估Qoi的易用性。在自由生活条件下进行包含40名参与者和5个可穿戴装置的主观实验,以创建QoE模型。我们假设QoE成为Qod的功能,Qoi和使用平衡的重​​量技术来制定最终模型。 R. 2 和调整-R 2 0.65和0.63的值表示所提出的计划的合理预测力。根据结果​​,向不同的智能可穿戴供应商提供适当的建议,以改善其产品,从而确保更大的用户采用。

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