research-article

Understanding Older Users' Acceptance of Wearable Interfaces for Sensor-based Fall Risk Assessment

Authors:

Alan Yusheng Wu,

Cosmin MunteanuAuthors Info & Claims

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Paper No.: 119, Pages 1 - 13

https://doi.org/10.1145/3173574.3173693

Published: 19 April 2018 Publication History

Abstract

Algorithms processing data from wearable sensors promise to more accurately predict risks of falling -- a significant concern for older adults. Substantial engineering work is dedicated to increasing the prediction accuracy of these algorithms; yet fewer efforts are dedicated to better engaging users through interactive visualizations in decision-making using these data. We present an investigation of the acceptance of a sensor-based fall risk assessment wearable device. A participatory design was employed to develop a mobile interface providing visualizations of sensor data and algorithmic assessments of fall risks. We then investigated the acceptance of this interface and its potential to motivate behavioural changes through a field deployment, which suggested that the interface and its belt-mounted wearable sensors are perceived as usable. We also found that providing contextual information for fall risk estimation combined with relevant practical fall prevention instructions may facilitate the acceptance of such technologies, potentially leading to behaviour change.

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Casey BMarston GVyas D(2025)Self-Care Practices in the Context of Older Adults Living IndependentlyProceedings of the ACM on Human-Computer Interaction10.1145/37012059:1(1-26)Online publication date: 10-Jan-2025
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Karayaneva YSharifzadeh SSzczepura AJing YTan B(2024)AI-Enhanced Healthcare and Eldercare Delivery Using Non-Intrusive Sensors and Physical RobotsImpact of Digital Solutions for Improved Healthcare Delivery10.4018/979-8-3693-5237-3.ch001(1-34)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-5237-3.ch001
Zhang H(2024)Searching for the Non-Consequential: Dialectical Activities in HCI and the Limits of ComputersProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641945(1-13)Online publication date: 11-May-2024
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Index Terms

Understanding Older Users' Acceptance of Wearable Interfaces for Sensor-based Fall Risk Assessment
1. Applied computing
  1. Life and medical sciences
2. Human-centered computing
  1. Human computer interaction (HCI)

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CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

April 2018

8489 pages

ISBN:9781450356206

DOI:10.1145/3173574

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Published: 19 April 2018

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https://dl.acm.org/doi/10.1145/3701205
Karayaneva YSharifzadeh SSzczepura AJing YTan B(2024)AI-Enhanced Healthcare and Eldercare Delivery Using Non-Intrusive Sensors and Physical RobotsImpact of Digital Solutions for Improved Healthcare Delivery10.4018/979-8-3693-5237-3.ch001(1-34)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-5237-3.ch001
Zhang H(2024)Searching for the Non-Consequential: Dialectical Activities in HCI and the Limits of ComputersProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641945(1-13)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641945
Furtado GCaldo-Silva ADireito FEsteves PCosta-Brito SMoura CTeixeira AAbreu CRodrigues R(2024)The Use of New Devices Technologies to Analyse the Risk of Falls Associated with Gait Patterns in Older People: A Protocol for a Scoping ReviewProceedings of the 10th Congress of the Portuguese Society of Biomechanics10.1007/978-3-031-47790-4_47(481-489)Online publication date: 18-Feb-2024
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