Designing Digital Technologies and Safeguards for Improving Activities and Well-Being for Aging in Place

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Abstract

Older adults (65+) are becoming primary users of technologies, including IoTs, wearables and emerging smart systems, especially for aging in place and in daily living activities related to better health and wellness. Research demonstrates some critical features in home health care and wearable technology adoption by older adults such as wearability, device appearance, display and interaction, the modeling and technical aspects of data measurement and presentation, with more sophisticated, personalized interaction systems and data analysis expected over time. The design and development of home health care technologies are often led by the requirements of their social and caregiving environments rather than the needs and preferences of older adult users. The mismatch between functionalities, intrinsic motivations and expected benefits has a detrimental impact on user acceptance. User acceptance is critical for technology to be integrated within daily living especially in areas such as IoTs and wearables. Cybersecurity is an essential part of a safe, effective and reliable healthcare delivery system. Security and privacy challenges can be overcome by implementing best practices to safeguard systems and devices. There are significant privacy risks associated with wearables and home IoTs. The literature review has identified emerging issues that underscore the need to develop a set of guidelines for conducting HCI and human factors research based on an understanding of older adults’ perceptions and preferences about data privacy and security. Additionally, directions for current and future research are discussed in the paper, including late breaking research on virtual care and support vulnerable seniors during the COVID 19 pandemic.

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APA

Fournier, H., Kondratova, I., & Molyneaux, H. (2020). Designing Digital Technologies and Safeguards for Improving Activities and Well-Being for Aging in Place. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12426 LNCS, pp. 524–537). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60149-2_40

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