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

摘要

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