Introducing GaitLib : a library for real-time gait analysis in smartphones

Wu, Michael M.; Schneider, Oliver; Karuei, Idin; Leong, Larissa; MacLean, Karon E.

doi:10.14288/1.0050993

2014

DOI: 10.14288/1.0050993

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Introducing GaitLib : a library for real-time gait analysis in smartphones

Michael M. Wu¹,

Oliver Schneider²,

Idin Karuei³

et al.

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Gait-Guided Adaptive Interfaces: Managing Cognitive Load In Older Users

Blumenthal

Tong

Chignell

2017

Proceedings of the Human Factors and Ergonomics Society Annual

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Mobile computing provides new ways to interact with technology; applications such as navigation, social facilitation, and augmented reality are used while walking. We introduce Gait-Guided Adaptive Interfaces (GGAIs) as a way to manage cognitive load in dual-task conditions (walking while using a device). Gait markers that can be suitably assessed using smartphone sensors (decreased gait speed, increased variability) have been shown to be indicative of cognitive load in older adults. Motor-cognitive interference is a more significant issue as we age, gait becomes less automatic, and the risk of falls under distraction increases. Apps with GGAIs measure changes in gait to infer load and then adapt the way that the App interacts with the user accordingly. We validate this approach using a simple Go/No-Go task, and then show how gait responds to changes in task complexity. We conclude with a discussion of how GGAIs may be used by developers to improve the usability of apps for older users.

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Gait-Guided Adaptive Interfaces: Managing Cognitive Load In Older Users

Blumenthal

Tong

Chignell

2017

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

show abstract

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Introducing GaitLib : a library for real-time gait analysis in smartphones

Cited by 1 publication

References 12 publications

Gait-Guided Adaptive Interfaces: Managing Cognitive Load In Older Users

Gait-Guided Adaptive Interfaces: Managing Cognitive Load In Older Users

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