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MRI India Journals Vol. 15 No. 1S (2026): Special Issue: Integration of AI Management Engineering and Technology

AI-Based Emotion Recognition and Supportive Response System for Non-Verbal Communication

Authors

  • Surekha Dhumal Computer Engineering Department / Genba Sopanrao Moze College of Engineering, Balewadi, Pune / SPPU / India
  • Dnyaneshwar Dhas Computer Engineering Department / Genba Sopanrao Moze College of Engineering, Balewadi, Pune / SPPU / India
  • Kavya Hingane Computer Engineering Department / Genba Sopanrao Moze College of Engineering, Balewadi, Pune / SPPU / India
  • Hrutik Jadhav4 Computer Engineering Department / Genba Sopanrao Moze College of Engineering, Balewadi, Pune / SPPU / India
  • Vaishnavi Tokale Computer Engineering Department / Genba Sopanrao Moze College of Engineering, Balewadi, Pune / SPPU / India

DOI:

https://doi.org/10.65521/ijeecs.v15i1S.3073

Keywords:

AI Therapist System Artificial Intelligence CNN Computer Vision Deep Learning Emotion Recognition Facial Expression Analysis Hand Gesture Recognition LSTM MediaPipe Multimodal Learning OpenCV Real-Time Processing Streamlit

Abstract

This research presents an AI-based multimodal therapist system for non-verbal communication using real-time facial emotion recognition and hand gesture detection. The system combines computer vision and deep learning techniques, where emotions are detected using a CNN model and gestures are recognized using MediaPipe and LSTM. Live video input is captured through a webcam and processed using OpenCV. The results are displayed via a Streamlit interface with voice feedback. Unlike existing systems, this approach integrates both emotion and gesture recognition, improving interaction accuracy and usability in real-time environments.

 

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Published

2026-05-22

How to Cite

Dhumal, S., Dhas, D., Hingane, K., Jadhav4, H., & Tokale, V. (2026). AI-Based Emotion Recognition and Supportive Response System for Non-Verbal Communication. International Journal of Electrical, Electronics and Computer Systems, 15(1S), 283–288. https://doi.org/10.65521/ijeecs.v15i1S.3073

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