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IKKN Predictor: An EEG Signal Based Emotion Recognition for HCI

  • Sujata Bhimrao WankhadeEmail author
  • Dharmapal Dronacharya Doye
Article
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Abstract

Emotion recognition is the process of identifying the human emotion through their facial expression. However, it is a challenging task to determine the emotions of mentally challenged people. Therefore the emotion classification and prediction is the main aim of the research developed in the past years with different techniques. The number of state-of-the-art literature is reviewed using these techniques for the prediction of emotions. This paper carried out three stages of the analysis such as pre-processing, feature extraction and selection then emotion recognition using IKNN. The performance of this algorithm is evaluated using five parameters in SEED platform of Matlab simulation tool. This method of classification gives better performance regarding accuracy, precision, recall and mean square error. Therefore based on the analysis, this paper summarises the deep study of different classification strategies with its performance.

Keywords

Emotion recognition Pre-processing Improved k-nearest neighbour Classification Support vector machine Accuracy 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Sujata Bhimrao Wankhade
    • 1
    Email author
  • Dharmapal Dronacharya Doye
    • 2
  1. 1.Computer Science and Engineering DepartmentShri Guru Gobind Singhji Institute of Engineering and TechnologyVishnupuri, NandedIndia
  2. 2.Department of Electronics and Telecommunication EngineeringShri Guru Gobind Singhji Institute of Engineering and TechnologyVishnupuri, NandedIndia

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