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Journal of Interaction Science

, 3:6

First Online: 11 November 2015Received: 28 May 2015Accepted: 13 October 2015


The role of affect and emotion in interactive system design is an active and recent research area. The aim is to make systems more responsive to user’s needs and expectations. The first step towards affective interaction is to recognize user’s emotional state. Literature contains many works on emotion recognition. In those works, facial muscle movement, gestures, postures and physiological signals were used for recognition. The methods are computation intensive and require extra hardware e.g., sensors and wires. In this work, we propose a simpler model to predict the affective state of a touch screen user. The prediction is done based on the user’s touch input, namely the finger strokes. We defined seven features based on the strokes. A linear combination of these features is proposed as the predictor, which can predict a user’s affective state into one of the three states: positive happy, excited and elated, negative sad, anger, fear, disgust and neutral calm, relaxed and contented. The model alleviates the need for extra setup as well as extensive computation, making it suitable for implementation on mobile devices with limited resources. The model is developed and validated with empirical data involving 57 participants performing 7 touch input tasks. The validation study demonstrates a high prediction accuracy of 90.47 %. The proposed model and its empirical development and validation are described in this paper.

KeywordsEmotional state Touch screen Strike and tap Features Linear regression Empirical study  Download fulltext PDF

Autor: Sachin Shah - J. Narasimha Teja - Samit Bhattacharya


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