Combining Mixed Reality and Internet of Things: An Interaction Design Research on Developing Assistive Technologies for Elderly People

Abstract

Ambient Assistive Living (AAL) technologies have the capacity to provide a safe environment for elderly people and to monitor and analyse gathered data which have been proven to be valuable in detecting activities that underpin health decline. Although there is a growing interest for these technologies, older people face some difficulties interacting with the technology. In an AAL environment, the interaction problem due to changes in perceptual and motor skill capabilities that often accompany the aging process in elderly people is further complicated as the immense quantity of sensors, with varying user interface and user interaction, makes full interoperability difficult. As elderly people navigate through this environment, they should be able to discover, configure, and directly interact with a myriad smart objects and digital information delivered to them. To increase the uptake of these technologies, there is a need for an intuitive interaction technique that considers elderly people’s personal profile and presents contextual information when needed. In this paper, we present an interaction design research which aims to explore opportunities and challenges inherent to the development of an Assistive Technology (AT) for elderly people. The proposed AT, which is a combination of Mixed Reality (MR) and Internet of Things (IoT) technologies, aims to improve the Quality of Life (QoL) and to maintain the self-independence of people aged 65 or above. The intended users are elderly people, their family, their closest friends, and their healthcare network. The main contribution of this project is to provide a set of interaction design principles for combining MR and IoT as an AT. This is achieved by a carefully planned participatory design approach. The benefits and drawbacks of each phase are discussed transparently to inform current practices which are still mostly technology driven.