Brain-Computer Interface Learning System for Quadriplegics

Abstract

The proposed Brain-Computer Interface system enables Quadriplegic patients, people with severe motor disabilities to send commands to electronic devices and communicate with ease. Interactive sessions are vital for effective knowledge transfer in any learning eco-system. The growth of Brain-Computer Interface (BCI) has led to rapid development in 'Assistive Systems' for the disabled called 'assistive domotics'. Brain-Computer-Interface is capable of reading the brainwaves of an individual and analyse it to obtain some meaningful data. This processed data can be used to assist people having speech disorders and sometimes people with limited locomotion to communicate. In this Project, Emotiv EPOC Headset is used to obtain the electroencephalogram (EEG). The obtained data is processed to communicate pre-defined commands and queries for interactive learning. EEG data can also be used to monitor student's emotional behaviour and provide emotional feedback to the students. Other Vital Information like the heartbeat, blood pressure, ECG and temperature are monitored and uploaded to the server. The Data is processed in Intel Edison, system on chip (SoC). Patient metrics are displayed via Intel IoT Analytics cloud service.