**1. Introduction**

A common finding in cognitive neuroscience [1] states that a person's perception of their behavior does not always relate to their neural activity. Experiments have shown that people do not always know what is going on inside their minds. For instance, in an eye-tracking study that involved reading [2], real-time quantitative measures of eye movements revealed longer fixation times for reading text with transposed letters as compared to reading normal

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

text even though readers claimed to spend just a few seconds on text with transposed letters. Also, electroencephalography (EEG) of language processing [3] has concluded that phrases judged as easy to comprehend and highly acceptable sometimes entail a larger processing effort on the part of the readers.

samples of the voice are calculated from extracted speech parameters. The features serve as inputs to a classifier, which can be a computer program, a device, or both. The classifier assigns at least one emotional state from a finite number of possible emotional states to the speech signal. Such techniques enable scientists to further debate the real nature of emotions, whether they are evolutionary, physiological, or cognitive to explain affective states. Results from applying this methodology on real-time data collected from a single subject demonstrated a recognition level of 71.4% which is comparable to the best results achieved. The detection mechanism outlined in this chapter has most of the characteristics required to

A Control System for Detecting Emotions on Visual Interphase Stimulus

http://dx.doi.org/10.5772/intechopen.75873

27

An experiment was conducted [14, 15] in which a single participant interacted with three different visual interphases—games, webpage, and a textbook. The user's physiological readings were taken alongside the eye movement measured with an eye tracker. The rationale for choosing these interphases is derived from the fact that all stimuli contain dynamic contents and involve cognitive workload on the user that induces slight stress. For creating a system control capable of identifying users' emotion on an interphase, MATLAB was used for its signal processing and system identifiable toolbox capable of developing dynamic systems. The

Adera is a story-driven adventure game that involves a single player; it allows to solve puzzles, collect artifacts, and explore the environments to reveal the mysteries of a newfound civilization. The episodic story involved begins when the player receives a message from a missing person known as the grandfather (Hawk). The game involves some cognitive processing on the part of the user. The user interacts with the first episode, while his eye

The Yahoo homepage is a very popular site where most regular users frequent for currents news and entertainment widgets. The user was simply asked to locate news or entertainment contents that were of interest and interact with while the physiological measures

The textbook (The Designer) incentive involves locating an interesting phrase from a stimulus page that captures the reader's attention at a single glance. All the tasks are contrived, simply to induce slight stress so we can observe the amplitudes or increase in physiological response

perform emotion detection on real-time visual stimulus.

following sections discuss these visuals and tasks involved.

**3. Methods**

**3.1. Adera**

movement was taken.

**3.2. Yahoo webpage**

were taken.

**3.3. Textbook**

in reaction to the visual interphase.

Control systems are sometimes used to understand the mechanism behind human computer interaction to provide industry-standard algorithms and applications that systematically analyze, design, and tune linear control systems. In this aspect, a system can be specified as a statespace model, transfer function, frequency-response model, or zero polegain. Some applications and functions, such as step response plot and Bode plot, let us visualize system behavior in time domain and frequency domain, which was observed in the result section of the chapter to analyze the behavior of our final system response. The compensator parameters are tuned using automatic, Bode loop shaping method in MATLAB; this was used to validate the design by verifying the rise time, settling time, phase, and gain margins. To understand the systems dynamics between eye movement and the visual stimuli, we adopt the second differential equation Eq. (1), which represents the prediction focus, 4 min from the detected fixations, and visual contents that induce stress. Therefore, the main objectives of this chapter include:

