Smeaton, Alan F.ORCID: 0000-0003-1028-8389, Krishnamurthy, Naveen Garaga and Suryanarayana, Amruth Hebbasuru
(2021)
Keystroke dynamics as part of lifelogging.
In: 27th International Conference on Multimedia Modeling, MMM 2021, 22-24 June 2021, Prage, Czech Republic (Online).
ISBN 978-3-030-67835-7
In this paper we present the case for including keystroke dynamics in lifelogging. We describe how we have used a simple keystroke logging application called Loggerman, to create a dataset of longitudinal keystroke timing data spanning a period of up to seven months for four participants. We perform a detailed analysis of this data by examining the timing information associated with bigrams or pairs of adjacently-typed alphabetic characters. We show how the amount of day-on-day variation of the keystroke timing among the top-200 bigrams for participants varies with the amount of typing each would do on a daily basis. We explore how daily variations could correlate with sleep score from the previous night but find no significant relationship between the two. Finally we describe the public release of a portion of this data and we include a series of pointers for future work including correlating keystroke dynamics with mood and fatigue during the day.
Metadata
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Additional Information:
The final authenticated publication is available online at https://link.springer.com/chapter/10.1007/978-3-030-67835-7_16
27th International Conference on Multimedia Modeling (MMM 2021), Proceedings. Lecture Notes in Computer Science (LNCS)
12573.
Springer. ISBN 978-3-030-67835-7