Design of Wearable Insight for Autism

Computer Engineering

This project endeavors to address the critical need for improved emotional recognition methods tailored for individuals on the autism spectrum. The project context emerges from the pervasive challenges faced by individuals with autism in expressing and interpreting emotions, hindering their social interactions and communication skills. Traditional methods of emotion recognition often fall short in accommodating the unique needs of this population. The core problem addressed in this project revolves around the limited effectiveness of existing emotion recognition techniques for autistic individuals, particularly in real-time scenarios. To bridge this gap, we propose a novel approach utilizing Galvanic Skin Response (GSR) sensors, which measure physiological responses indicative of emotional states. By integrating GSR data with advanced machine learning algorithms, our solution aims to provide a more nuanced and accurate portrayal of the emotional experiences of individuals with autism. The project's methodology involves designing and implementing a GSR-based emotion recognition system, tailored to the specific characteristics and sensitivities of the autistic population. The results obtained from our research showcase the potential of GSR sensors in enhancing the precision of emotion recognition for individuals with autism. The system demonstrates promising accuracy in identifying a range of emotions, contributing to a better understanding of the emotional states experienced by autistic individuals. In conclusion, this project not only presents a technically robust solution to the problem of emotion recognition for individuals with autism but also underscores the significance of leveraging emerging technologies for the betterment of neurodiverse communities. The findings provide a foundation for future research and development in the field of assistive technologies, fostering inclusivity and improving the quality of life for individuals with autism.

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