Abstract
Children with autism spectrum disorder (ASD) exhibit deficiencies in the socio-communicative domain and commonly struggle with emotion perception and expression. Robots are becoming increasingly prevalent in our lives, notably in the medical field. Some therapists at therapeutic centers are beginning to experiment with techniques such as computer games, Online exchanges that are available and robot-assisted therapy. Robot-assisted therapy has been widely proven to provide a reliable and effective intervention for enhancing communication and social skills in children having ASD. The humanoid robot may grab the attention of young children and later draw the interest of researchers. This study is accomplished through the use of a revolutionary technique based on deep learning algorithms that comprises essential data and understanding about patients, diagnostic procedures, and medicines. A robot therapist can transmit the results responsibly using this paradigm. Here parameter tunned CNN based model are used and the model is achieved with an accuracy rate of 96% in ASD detection.
Publisher
Inventive Research Organization