DocumentCode :
2976614
Title :
Keyboard and mouse interaction based mood measurement using artificial neural networks
Author :
Khan, M.S. ; Khan, Iqbal A. ; Shafi, M.
Author_Institution :
Dept. of Comput. Software Eng., Univ. of Eng. & Technol., Peshawar, Pakistan
fYear :
2012
fDate :
22-23 Oct. 2012
Firstpage :
130
Lastpage :
134
Abstract :
The study is based on an experiment to measure the affective states of computer users via their use of mouse and keyboard. The experiment was replicated from a previous study by Khan et al., [5] resulting in significant correlations between the computer users pattern of interactions and their valence, arousal ratings. This study utilized the same data set from [5] and re-confirmed its validity by training Artificial Neural Networks (ANN). The data was divided into two portions for each individual. A portion to train ANN on his/her patterns of interaction and other portion to test the ANN. The study resulted in an average recognition rate of 64.72 % for valence and 61.02 % for arousal ratings. The highest recognition rates for individual participants´ valence and arousal were 100% and 87% respectively. These figures suggest that ANN is a bright prospect for the measurement of affective states of individual computer users via their interaction with keyboard and mouse.
Keywords :
human computer interaction; human factors; keyboards; learning (artificial intelligence); mouse controllers (computers); neural nets; psychology; ANN testing; ANN training; arousal ratings; artificial neural networks; computer user affective state measurement; interaction pattern; keyboard interaction-based mood measurement; mouse interaction-based mood measurement; valence; Artificial neural networks; Computers; Emotion recognition; Humans; Mice; Mood; Pattern recognition; Keybaord; Mood; Mouse; Neural Network; affects; recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Artificial Intelligence (ICRAI), 2012 International Conference on
Conference_Location :
Rawalpindi
Print_ISBN :
978-1-4673-4884-3
Type :
conf
DOI :
10.1109/ICRAI.2012.6413378
Filename :
6413378
Link To Document :
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