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Title: Guidelines for evaluating wearables’ quality of experience in a mulsemedia context
Authors: Hussain, N
Ghinea, G
Keywords: quality of experience (QoE);mulsemedia;heart rate;crossmodal;olfaction
Issue Date: 21-May-2022
Publisher: Springer Nature
Citation: Hussain, N.and Ghinea, G. (2022) 'Guidelines for evaluating wearables’ quality of experience in a mulsemedia context', Multimedia Tools and Applications, 0 (in press), pp. 1-32 (32). doi: 10.1007/s11042-022-12766-7.
Abstract: Copyright © The Author(s) 2022. Quality of Experience (QoE) is inextricably linked to the user experience of multimedia computing and, although QoE has been explored in relation to other types of multimedia devices, thus far its applicability to wearables has remained largely ignored. Given the proliferation of wearable devices and their growing use to augment and complement the multimedia user experience, the need for a set of QoE guidelines becomes imperative. This study meets that need and puts forward a set of guidelines tailored exclusively towards wearables’ QoE. Accordingly, an extensive experimental investigation has been undertaken to see how wearables impact users’ QoE in multiple sensorial media (mulsemedia) context. Based on the exploratory study, the findings have shown that the haptic vest (KOR-FX) enhanced user QoE to a certain extent. In terms of adoption, participants reported they would generally incorporate the heart rate (HR) monitor wristband (Mio Go) into their daily lives as opposed to the haptic vest. Other findings revealed that human factors play a part in user’s attitudes towards wearables and predominantly age was the major influencing factor. Moreover, the participants’ HR varied throughout the experiments, suggesting an enhanced level of engagement whilst viewing the multimedia video clips. Furthermore, the results suggest that there is a potential future for wearables, if the QoE is a positive one and if the design of such devices are appealing as well as unobtrusive.
ISSN: 1380-7501
Appears in Collections:Dept of Computer Science Research Papers

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