The primary goal of this project is to provide a platform that connects physiologists, disabled children, and their parents to facilitate and monitor cognitive behavioral training for the children. The training consists of various games such as memory games, puzzles, and quizzes, designed to stimulate cognitive activity and improve the children's cognitive abilities.The software aims to improve the cognitive abilities of children with EEG by providing them with a fun and engaging way to learn.
Since disabled children experience frequent seizures, they may find it difficult to use the mouse or keyboard. Therefore, the software has introduced the YOLO algorithm, which predicts the hand gestures of the children using the web camera to move the cursor. In addition to the YOLO algorithm, the software uses Long short-term memory (LSTM) to analyze the frequency of the activities of the children, which predicts the area in which the children lack knowledge. The LSTM is a type of recurrent neural network (RNN) that is capable of learning long-term dependencies.The software is a valuable tool for improving the cognitive abilities of children with EEG. Several studies have shown that brain training products can be effective in improving cognitive abilities in children and adolescents. Attention-memory training has been shown to yield behavioral and academic improvements in children diagnosed with attention-deficit hyperactivity disorder comorbid with a learning disorder. Neurofeedback training has also been shown to be effective in improving the attention of children with autism.