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EEG-Based Emotion Recognition Using Quantum Machine Learning

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Abstract

Recognizing emotions is crucial for the development of artificial intelligence in various fields. This study explores the application of quantum support vector machines (SVMs) on emotion recognition from electroencephalogram (EEG) signals and compares its performance to traditional SVMs. SVMs are a popular machine-learning algorithm for this task due to their ability to handle high-dimensional data and non-linear relationships between input features. This study uses a quantum SVM to generate distinct solutions based on quantum principles. We applied this method to the DEAP benchmark dataset for binary class classification and gained new insights into the quantum nature of emotions. The algorithm has trained on D-Wave quantum annealer using various samples, achieving accuracies of 65.6% and 75.0% for valence and arousal dimensions, respectively, with 22 × 40 × 32 (subjects × trials × channels) data points, demonstrating the potential of quantum machine learning for EEG-based emotion recognition. However, there are methodological challenges due to the quantum arbitrariness of current annealers and the sensitivity of quantum-based machines to initial values. To address this, we conducted multiple investigations under similar circumstances and successfully recognized emotions using our proposed method.

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Authors and Affiliations

  1. Department of Computer Engineering, NIT Kurukshetra, Kurukshetra, Haryana, India

    Divya Garg & Awadhesh Kumar Singh

  2. Department of Information Technology, NIT Raipur, Raipur, Chhattisgarh, India

    Gyanendra Kumar Verma

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The authors confirm their contribution to the paper as follows: study conception and design: GKV, AKS; data collection: DG; analysis and interpretation of results: DG, GKV; draft manuscript preparation: DG, GKV, AKS. All the authors reviewed the results and approved the final version of the manuscript.

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Correspondence to Divya Garg.

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This article is part of the topical collection “Research Trends in Computational Intelligence” guest edited by Anshul Verma, Pradeepika Verma, Vivek Kumar Singh and S. Karthikeyan.

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Garg, D., Verma, G.K. & Singh, A.K. EEG-Based Emotion Recognition Using Quantum Machine Learning. SN COMPUT. SCI. 4, 480 (2023). https://doi.org/10.1007/s42979-023-01943-6

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