International Journal of Mathematical Sciences and Computing (IJMSC)
IJMSC Vol. 11, No. 2, 8 Jun. 2025
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BiLSTM-Powered Emotion Recognition from ECG and GSR Signals
PDF (713KB), PP.38-51
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Author(s)
Vanapalli Satya Sumanth
1,*
Vanapalli Sashi Vardhan
2
Peruri Bhuvan Satwik
3
Neelamsetty Glory
4
Vallala Lohitha Prakaashini
5
Saragadam Charishma
6
Adiraju Shasank
7
Index Terms
Electrocardiogram (ECG), Galvanic Skin Response (GSR), BiLSTM Networks, Emotion Classification, Affective Computing, Human-Computer Interaction (HCI), Physiological Signal Processing, Deep Learning
Abstract
Emotions significantly influence human behaviour, decision-making, and communication, making their accurate recognition essential for various applications. This study introduces a novel approach for emotion extraction from electrocardiogram (ECG) and galvanic skin response (GSR) signals using Bidirectional Long Short-Term Memory (BiLSTM) networks. Unlike conventional emotion recognition methods that rely on facial expressions or self-reports, our model utilizes physiological signals to capture emotional states with high precision. ECG provides insights into cardiac activity, while GSR reflects changes in skin conductance, both serving as reliable indicators of emotional responses. By leveraging advanced signal processing techniques and deep learning algorithms, the model effectively identifies intricate patterns within these biosignals, enabling accurate emotion classification. Experimental validation demonstrates the model’s effectiveness in distinguishing between different emotional states, surpassing traditional methods. This research contributes to affective computing and human-computer interaction (HCI) by enhancing the capability of intelligent systems to recognize and respond to human emotions, paving the way for applications in mental health monitoring, driver assistance systems, and adaptive user interfaces.
Cite This Paper
Vanapalli Satya Sumanth, Vanapalli Sashi Vardhan, Peruri Bhuvan Satwik, Neelamsetty Glory, Vallala Lohitha Prakaashini, Saragadam Charishma, Adiraju Shasank, "BiLSTM-Powered Emotion Recognition from ECG and GSR Signals", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.11, No.2, pp. 38-51, 2025. DOI: 10.5815/ijmsc.2025.02.04
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