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Keyboard and mouse interaction based mood measurement using artificial neural networks

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3 Author(s)
Mohammad Sohail Khan ; Dept. of Comput. Software Eng., Univ. of Eng. & Technol., Peshawar, Pakistan ; Iftikhar Ahmed Khan ; Muhammad Shafi

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.

Published in:

Robotics and Artificial Intelligence (ICRAI), 2012 International Conference on

Date of Conference:

22-23 Oct. 2012