Smartphone-derived Virtual Keyboard Dynamics Coupled with Accelerometer Data as a Window into Understanding Brain Health

要旨

We examine the feasibility of using accelerometer data exclusively collected during typing on a custom smartphone keyboard to study whether typing dynamics are associated with daily variations in mood and cognition. As part of an ongoing digital mental health study involving mood disorders, we collected data from a well-characterized clinical sample (N = 85) and classified accelerometer data per typing session into orientation (upright vs. not) and motion (active vs. not). The mood disorder group showed lower cognitive performance despite mild symptoms (depression/mania). There were also diurnal pattern differences with respect to cognitive performance: individuals with higher cognitive performance typed faster and were less sensitive to time of day. They also exhibited more well-defined diurnal patterns in smartphone keyboard usage: they engaged with the keyboard more during the day and tapered their usage more at night compared to those with lower cognitive performance, suggesting a healthier usage of their phone.

著者
Emma Ning
University of Illinois at Chicago, Chicago, Illinois, United States
Andrea T. Cladek
University of Illinois at Chicago, Chicago, Illinois, United States
Mindy K. Ross
University of Illinois at Chicago, Chicago, Illinois, United States
Sarah Kabir
University of Illinois at Chicago, Chicago, Illinois, United States
Amruta Barve
University of Illinois at Chicago, Chicago, Illinois, United States
Ellyn Kennelly
Wayne State University, Detroit, Michigan, United States
Faraz Hussain
University of Illinois at Chicago, Chicago, Illinois, United States
Jennifer Duffecy
University of Illinois at Chicago, Chicago, Illinois, United States
Scott Langenecker
University of Utah, Salt Lake City, Utah, United States
Theresa Nguyen
University of Illinois at Chicago, Chicago, Illinois, United States
Theja Tulabandhula
University of Illinois at Chicago, Chicago, Illinois, United States
John Zulueta
University of Illinois at Chicago, Chicago, Illinois, United States
Olusola A. Ajilore
University of Illinois, Chicago (UIC), Chicago, Illinois, United States
Alexander P. Demos
University of Illinois at Chicago, Chicago, Illinois, United States
Alex Leow
University of Illinois, Chicago (UIC), Chicago, Illinois, United States
論文URL

https://doi.org/10.1145/3544548.3580906

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Health Data and Tracking

Room Y07 + Y08
6 件の発表
2023-04-26 23:30:00
2023-04-27 00:55:00