Biometric Recognition using EEG Signals from Brain

A new computational developed system for early detection of driver drowsiness using brain activity is measured by electroencephalographic (EEG) signals. Brain Computer Interface (BCI) are systems that can bypass the channels of transmission to provide direct communication between the human brain and physical devices. It can translates a different patterns of brain activity into commands. With these commands a robotic module can be controlled. The intention of the project work is to develop seat vibration that can assist the drowsiness people. Here, we analyze the brain wave signals. Generally human brain consists millions of neurons. The pattern of interaction between these neurons are represented as thoughts and emotional states in the human brain. According to human thoughts, this system will be changing which in turn to develop different electrical signals. A muscle contraction will also generate a unique electrical signals. All these electrical signals will be sensed by the brain wave sensor and it will convert the data into packets and transmit through radio frequency ID (RF ID) packets. Level analyzer unit (LAU) will receive the raw data from the RF ID packets and it will extract and process the signal using MATLAB platform. Then the control commands will be transmitted to the robotic module to generate seat vibration.