Towards Visualization of Time–Series Ecological Momentary Assessment (EMA) Data on Standalone Voice–First Virtual Assistants

ASSETS 2022

Abstract

Population aging is a global issue in 21th century, and Ecologial Momentary Assesssments (EMA) is one well-known techniques widely used in geriatrics. However, accessing and interacting with digital health information is a well-known challenge for aging populations. While voice-based Intelligent Virtual Assistants (IVAs) are promising to improve the Quality of Life (QoL) of older adults, the effectiveness of visualizing time-series based EMA data on standalone IVAs has not been explored. To explore the potential opportunities for visualizing time-series based EMA data on standalone IVAs, we designed a prototype system, where older adults are able to query and examine the time–series EMA data on Amazon Echo Show — a widely used commercially available standalone screen–based IVA. We conducted a preliminary semi–structured interview with a geriatrician and an older adult, and identified three findings that should be carefully considered through thematic analysis. We believe our work will benefit future researchers and practitioners to innovate full-fledged data visualization systems aiming at improving QoL for older adults.

Publication
The 24th International ACM SIGACCESS Conference on Computers and Accessibility (Anthens, Greece) (ASSETS’22). Association for Computing Machinery, Anthens, Greece.
Chen Chen
Chen Chen
Ph.D. Student
Nadir Weibel
Nadir Weibel
Associate Professor of Computer Science and Engineering

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