Detection of a Smartphone User's Distraction Based on Typing and Touch Gestures
PervasiveHealth'19 Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare(2019)
Abstract
Distraction influences how we experience user interfaces and perform tasks as it increases our workload. It can be caused by internal or external factors. However, it is difficult to measure it in everyday life situations. Smartphones might solve this problem. To examine correlations between smartphone features and distraction, we conducted a user study with 20 participants. They had to (1) type text to describe a picture and (2) swipe and tap to select images from a gallery, either with or without distraction. Ground truth data (NASA-TLX, task completion time, eye pupil diameter) confirmed a successful distraction. Distraction went along with significant changes in touch and typing behavior. That is, participants tended to type slower (higher inter-key interval), made more typing errors (higher keystroke per character), and swiped slower (lower swiping speed). We conclude that a detection of distraction is possible, but only relative to a basic or previous user behavior that needs to be known.
MoreTranslated text
Key words
Mobile Sensing,Distraction,Workload,Touch Gestures,Typing,Smartphones
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined