Paper Info
Title
Exploring The Use Of Fingerprint Sensor Gestures For Unlock Journaling: A Comparison With Slide-To-X
Abstract
Experience Sampling Methods (ESM) allow the timely collection of subjective self-reports that would otherwise be impossible to measure accurately in ecologically valid scenarios. Recent work suggests that unlock journaling allowed the collection of more data points per day, was faster and perceived as being less intrusive by participants than notification-based ESM. This work extends the unlock journaling field by introducing a novel lockscreen data collection mechanism harnessing an increasingly popular authentication mechanism: the fingerprint sensor. Results collected during a twelve-day user study with fingerprint sensor users show that fingerprint sensor gesture reporting compares favorably to Slide-to-X approaches. The proposed gestural interface was subjectively perceived as being the fastest, least intrusive, and overall most preferred interface, in addition to offering the highest response compliance. By offering a reporting mechanism better aligned with modern smartphone unlocking habits, this work encourages the deployment of unlock journaling in the wild.
Year
DOI
Venue
2019
10.1145/3338286.3340135
PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION WITH MOBILE DEVICES AND SERVICES (MOBILEHCI'19)
Keywords
Field
DocType
Experience sampling methods, unlock journaling, data collection, gestural input
Computer vision,Gesture,Fingerprint recognition,Computer science,Journaling file system,Artificial intelligence
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Pascal Fortin185.63
yuxiang huang203.04
Jeremy R. Cooperstock3449102.09