Keyboard and mouse interaction based mood measurement using artificial neural networks

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.