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1. Real-Time Wireless Brain–Computer Interface System for
Drowsiness Detection
A real-time wireless electroencephalogram (EEG)-based brain–computer interface (BCI)
system for drowsiness detection has been proposed. Drowsy driving has been implicated as a
causal factor in many accidents. Therefore, real-time drowsiness monitoring can prevent traffic
accidents effectively. However, current BCI systems are usually large and have to transmit an
EEG signal to a back-end personal computer to process the EEG signal. In this study, a novel
BCI system was developed to monitor the human cognitive state and provide biofeedback to the
driver when drowsy state occurs. The proposed system consists of a wireless physiological
signal-acquisition module and an embedded signal-processing module. Here, the physiological
signal-acquisition module and embedded signal-processing module were designed for long-term
EEG monitoring and real-time drowsiness detection, respectively. The advantages of low power
consumption and small volume of the proposed system are suitable for car applications.
Moreover, a real-time drowsiness detection algorithm was also developed and implemented in
this system. The experiment results demonstrated the feasibility of our proposed BCI system in a
practical application.
Existing System:
Most of the death occurs due to lack of concentration of the doctor. The number of deaths
increases due to lack of preventive measures.
Proposed system:
The system is divided into two phases. The first is the acquisition module and wireless
transmission module, second is data receiver module. The device used in the acquisition module
is responsible for acquiring EEG signal; the driver drowsiness is sensed by electroencephalogram
(EEG) sensor. The EEG sensor output is connected with PIC microcontroller, then the
microcontroller monitoring driver drowsiness according to sensor signal. If the sensor value is

2. exceeding the limit of threshold value, the microcontroller enables the buzzer and shows EEG
status in LCD. The PIC transmits the EEG data to the PC using Bluetooth wireless protocol.
Based on stored in PC. Doctor can know the patient status.
Block Diagram:
Transmitter Section:
Power Supply
LCD
Alarm
EEG Sensor
PIC
16F877A
Bluetooth

3. Receiver Section:
Bluetooth
Hardware Requirements:
 PIC Microcontroller.
 EEG Sensor
 Bluetooth module.
 LCD
 Buzzer
 PC
Software Requirements:
 Embedded C

4.  CCS or MP Lab Compiler