A Hierarchical Model for Analyzing User Experiences in Affect Aware Systems

Affect aware systems hold immense potential towards the creation of smart and assistive living spaces to establish paradigms of human-computer interactions through enhancing user experiences. The relevance of affect-aware systems not only lies in analyzing the affective components of user interactions, but it also involves analysis of the components affecting these user interactions in terms of context parameters and components of user behavior. Therefore, this work proposes a hierarchical structure for analyzing user behavior and performance while performing complex activities in the context of a smart home. This analysis would help to increase the assistive and adaptive nature of future intelligent systems for creation of smart and ambient living spaces in the context of a smart home; specifically, to improve the quality of life experienced by the increasing population of elderly people. To analyze the efficacy of this proposed model, several complex activities from the UK DALE dataset [1] were analyzed and a considerable efficiency of 75% was observed for the specific case study presented in this paper.

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