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Emotion recognition system for autism disordered people

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Abstract

People with autism spectrum disorders have difficulties with communicating and socially interacting through facial expressions, even with their parents. The proposed approach applies person identification and emotion recognition. The objective of this work is to monitor and identify the people with autism spectral disorder based on sensors and machine learning algorithm. Our proposed system uses neurological sensor to collect the EEG data of patients and Q sensor for measuring stress level. The proposal integrates the facial recognition for identifying emotion recognition. The experimental results obtained from the proposed work performance evaluation are discussed, considering each for Autism Patient and the emotion labels. Proposed work shown the experimental results that can detect emotion with good accuracy compared to other classifiers. The proposed work achieves a 6% better accuracy for Proposed Model than Support Vector machine and 8% more accuracy than back Propagation algorithm.

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Authors and Affiliations

  1. Sathyabama Institute of science and Technology, Semmancheri, Chennai, India

    A. Sivasangari, P. Ajitha, Immanuel Rajkumar & S. Poonguzhali

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  1. A. Sivasangari
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  2. P. Ajitha
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  3. Immanuel Rajkumar
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  4. S. Poonguzhali
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Correspondence to A. Sivasangari.

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Sivasangari, A., Ajitha, P., Rajkumar, I. et al. Emotion recognition system for autism disordered people. J Ambient Intell Human Comput (2019). https://doi.org/10.1007/s12652-019-01492-y

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  • DOI: https://doi.org/10.1007/s12652-019-01492-y

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