8 channel mobile eeg device

Electroencephalography (EEG) is a method by which brain waves can be measured by electric currents generated on the skull or brain surface. It was proposed by the German physician Hans Berger in 1929. EEG measurements are used in the diagnosis of epilepsy, in detecting epileptic seizures, brain tumors, brain death and certain brain abnormalities in sleep disorders, in measurement of anesthesia depth and in making some psychiatric evaluations. Besides, Brain-Machine Interface applications using EEG signals have become increasingly popular in recent years. With these applications, the need for portable and wearable EEG measurements has increased. EEG signals are non-stationary, one-dimensional, very low-amplitude, high-frequency signals that are affected by noise sources. For this reason, it can be measured with low noise, high resolution, high common mode suppression ratio measurement systems. In this master thesis A portable 8 channel EEG measurement system is designed and implemented which can be used in applications such as long-term EEG measurements, applications where portable EEG measurement equipment is needed, human machine interface applications, anesthesia depth detection. The system have small size (54,5 x 29,0 mm2), high sensitivity (11 nV – 24 bit), low input noise (1 µV) and low power consumption (195 mW). In this measurement system design; ADS1299 Analog Front-End (AFE) integrated circuit customized for biopotential signals as amplifier and analog-digital converter, Microchip RN4020 bluetooth module as communication unit and Atmel Atmega328p microcontroller as control unit are used. The system is powered by 1400 mAh Li-po battery for long time (28 hours) operation. The measurements taken from the system are sent to a central computer (personal computer) via bluetooth communication, and the received data can be recorded with a computer software and analyzed with signal processing software. In the absence of a bluetooth connection, data is stored on the memory card to prevent data loss. During the first phase of the study, the performance of the ADS1299 integrated circuit was examined. Circuit designs were made in the light of the obtained information, tests were performed. Then control and computer software were written. Test and EEG signal measurements from the system have shown that the EEG measurement system can operate at acceptable accuracy for different scenarios. The proposed device design is open to development can be used as a modular in many engineering systems using EEG signals since small in volume, low power consumption and high accuracy