Usability of Smartbands by the Elderly Population in the Context of Ambient Assisted Living Applications

Abstract

Nowadays, the Portuguese population is aging at a fast pace. The situation is more severe in the interior regions of the country, where the rural areas have few people and have been constantly losing population; these are mostly elderly who, in some cases, live socially isolated. They are also often deprived of some types of social, health and technological services. One of the current challenges with respect to the elderly is that of improving the quality of life for those who still have some autonomy and live in their own residences so that they may continue living autonomously, while receiving the assistance of some exterior monitoring and supporting services. The Internet of Things (IoT) paradigm demonstrates great potential for creating technological solutions in this area as it aims to seamlessly integrate information technology with the daily lives of people. In this context, it is necessary to develop services that monitor the activity and health of the elderly in real time and alert caregivers or other family members in the case of an unusual event or behaviour. It is crucial that the technological system is able to collect data in a nonintrusive manner and without requiring much interaction with the elderly. Smartband devices are very good candidates for this purpose and, therefore, this work proposes assessing the level of acceptance of the usage of a smartbands by senior users in their daily activities. By using the definition of an architecture and the development of a prototype, it was possible to test the level of acceptance of smartbands by a sample of the elderly population—with surprising results from both the elderly and the caregivers—which constitutes an important contribution to the research field of Ambient Assisted Living (AAL). The evaluation showed that most users did not feel that the smartband was intrusive to their daily tasks and even considered using it in the future, while caregivers considered that the platform was very intuitive.

The future of care and healthcare provision to communitydwelling disa-bled elderly people in an ageing society

“…Monitoring the growing number of elderly people living with physical and particularly mental disabilities is becoming an increasing organizational and financial burden for both healthcare institutions and independent caregivers. This burden can however be lessened to a significant extent through implementing remote monitoring solutions that combine the potential of IoMT sensors with nonmedical devices like smartphones and wearables [26], such as smartwatches and smartbands [45]. These are sometimes interconnected into an integrated body area network (bAn) [46] that can measure physical and physiological parameters [47], and which often involve software for human activity recognition (HAr) [27] and activities of daily life (ADL) and fall detection systems (FDS).…”

Definition of Guideline-Based Metrics to Evaluate AAL Ecosystem’s Usability

“…There are studies that focus over the usability assessment of existing solutions to identify critical bottlenecks and suggest optimizations accordingly. In this scope are included but not limited to the following application contexts: wearable camera system for dementia patients in 2014 by Matthews et al [162], diabetes-monitoring applications in 2015 by Isaković et al [163], IPTV application running in commercial environment that integrates multiple solutions to support home care by Ribeiro et al [164], emergency alert devices in 2020 by Lersilp et al [165], and smart bands in 2021 by Correia et al [166], among others.…”

IndoorCare: Low-Cost Elderly Activity Monitoring System through Image Processing

“…There are also recent studies that focus on the analyses and comparison, in various ways, of the created applications and architectures of recent AAL solutions, exposing the trends in the solutions' implementation that most works have followed [10]. On a more practical level, there are several interesting implementations that have used various methods to monitor and interact with older people; these solutions typically use IoT devices to perform this monitoring [11], whether using sensors attached to the person [12], monitoring furniture [13], using video systems that analyze in real time what is happening [14,15], using face recognition to detect people and who they are [16], or even through the analyses of the sound [17]. The use of computer vision together with artificial intelligence is an increasingly common practice, using the best that these technologies allow to better monitor the elderly in their homes [18].…”