Document Type

Book

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE, 3. MEDICAL AND HEALTH SCIENCES

Publication Details

https://link.springer.com/chapter/10.1007/978-3-031-35992-7_65

Jean, P., Murphy, E., Bates, E. (2023). Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1833. Springer, Cham.

https://doi.org/10.1007/978-3-031-35992-7_65

Abstract

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data.

DOI

https://doi.org/10.1007/978-3-031-35992-7_65

Funder

This research received no external funding

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 International License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.

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