@inproceedings{a74dca9026324dbb99c6196ae0338f91,
title = "Using mouse and keyboard dynamics to detect cognitive stress during mental arithmetic",
abstract = "To build a personalized e-learning system that can deliver adaptive learning content based on student{\textquoteright}s cognitive effort and efficiency, it is important to develop a construct that can help measuring perceived mental state, such as stress and cognitive load. The construct must be able to be quantified, computerized and automated. Our research investigates how mouse and keyboard dynamics analyses could be used to detect cognitive stress, which is induced by high mental arithmetic demand with time pressure, without using intrusive and expensive equipment. The research findings suggest that when task demand increased, task error, task duration, passive attempt, stress perception and mouse idle duration may increase, while mouse speed, left mouse click and keystroke speed decreased. The significant effects of task demand and time pressure on mouse and keystroke behaviours suggest that stress evaluation from these input devices is potentially useful for designing an adaptive e-learning system.",
keywords = "Adaptive e-learning, Keyboard dynamics, Mental arithmetic, Mouse dynamics, Stress detection",
author = "Lim, {Yee Mei} and Aladdin Ayesh and Martin Stacey",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.",
year = "2015",
month = feb,
day = "14",
doi = "10.1007/978-3-319-14654-6_21",
language = "English",
isbn = "978-3-319-14653-9",
series = "Studies in Computational Intelligence",
publisher = "Springer ",
pages = "335--350",
booktitle = "Intelligent Systems in Science and Information 2014, SAI 2014",
}