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Optimized recurrent neural network based brain emotion recognition technique

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Abstract

In this paper, a brain emotion recognition model is developed for EEG signal-based emotion recognition using the dataset from Kaggle implementing a Gated Recurrent Unit (GRU) type Recurrent Neural Network (RNN) along with Principal Component Analysis (PCA) feature extraction technique. PCA is a statistical method that aims to decrease the number of features in a dataset while maintaining as much data as feasible. This shortens the training period and frequently leads to improved performance. In this paper, the emotions are classified by a classifier GRU-type RNN (GRNN). Deep learning network RNN has a unique structure that consists of input, hidden, and output layers. Most neural networks assess current input, not other information's impact. RNN has "memory," which evaluates inputs at any time. The proposed model is a GRNN method which is made up of three layers: a flattened layer, a dense layer with softmax activation, and a GRU layer with 128 units. A dense layer and GRU layers classify emotions from raw EEG signals' learning characteristics. The GRNN needs less training data and is easier to adapt. GRNNs contain less code when the network needs extra inputs. The experiments were conducted using the EEG Brain Wave Database by the proposed model and compared with the existing classifiers. The accuracy achieved is 96% using the GRNN model. Positive, neutral, and negative emotions are predicted, and the performance is measured using a confusion matrix. The entire model is built on Google Collaboratory Notebook. The accuracy of the proposed model is improved by 11.9% when compared to the existing Long Short-Term Memory (LSTM) model.

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Authors and Affiliations

  1. ECE Department, CVR College of Engineering, Hyderabad, India

    G. Ravi Kumar Reddy & Venkata Krishna Odugu

  2. PG Scholar, ECE Department, CVR College of Engineering, Hyderabad, India

    A. Durga Bhavani

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  1. G. Ravi Kumar Reddy
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  2. A. Durga Bhavani
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  3. Venkata Krishna Odugu
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Correspondence to G. Ravi Kumar Reddy.

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Reddy, G.R.K., Bhavani, A.D. & Odugu, V.K. Optimized recurrent neural network based brain emotion recognition technique. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18943-0

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