Telemedical System for Monitoring the Psycho-Neurological State of Patients in the Process of Rehabilitation

Telemedical system for monitoring the psycho-neurological state for rehabilitation is evolving for assessment and supervision of various neurological syndromes. Persons with disabilities are not a homogenous group, they are facing multiple problems in their daily life. Common problem of people with disabilities and old aged people is that they have lacked access to basic services. Nowadays researchers are focused on human computer interaction-based rehabilitation technologies that bring social-emotional intelligence closer. The paper is designed to achieve cognitive rehabilitation using machine learning approaches for disabled and elderly people. Electroencephalograms are used to monitor brain activity of the human brain and Kinect sensors are used to track users' movements. Chebyshev filter used to remove noise, for feature extraction Autoencoder technique is used, and classification is done by Transfer learning based Convolutional neural network with 95% and above accuracy. The proposed system will be applied in real time to achieve a better quality of life for disabled and elderly people.