Expression Detection Of Autistic Children Using CNN Algorithm

Facial emotion detection is a technique for identifying human emotions from facial expressions. Autism Spectrum Disorder is an advanced neurobehavioral disorder, autism is a vast field with many problems, including hyperactivity, sensory, speech, etc. Children with autism who have behavioral problems are the focus of this research. This research is on an automatic detection system that will detect the expressions of autistic children and generate a report explaining their behaviors during their therapy sessions. This automatic system is primarily focusing on three main behavioral issues: happy, neutral, and irritated. This research is done to provide facilities to the parents, therapists, and Autistic Rehabilitation Centers to keep records of their children’s and patients’ progress in the form of reports. This is carried out using machine learning and image processing methods. The autistic children's faces are used to extract the features using local binary patterns. The proposed system uses CNN, Haar Cascade object detection Algorithm, and TensorFlow. The classification of emotions and face detection is done using the CNN algorithm and Haar Cascade object detection algorithm. Helping Hands Rehabilitation Center, a Pakistan-based autism rehabilitation center has provided its utmost assistance to make this research possible.