Embedded System Design of An256-lead EEG
|School||Guangdong University of Technology|
|Course||Control Theory and Control Engineering|
|Keywords||EEG multi-channel synchronous acquisition uIP real-time dataacquisition|
Electroencephalography (EEG) is the recording of electrical physiological activity of the brain nerve cells in the brain cortex. It contains a large amount of physiological and pathological information. With the development of EEG research, EEG has been widely used in the areas of clinical medicine, brain and cognitive science, bio-medicine, military medicine, intelligent control, and especially in the area of the diagnosis of brain disorders, such as diagnosis of epilepsy locating the epileptic focus and assessment of the effectiveness of epilepsy treatment. Compared with their abroad counterparts, the products of electroencephalograph in China suffer the weaknesses such as lower anti-interference ability, narrower bandwidth, and severe waveform distortion. Therefore, the study of256-channel EEG machine is becoming a hot research topic in China.This thesis purports to develop a high-performance EEG acquisition system, with an emphasis on the study of collection system design, acquisition and control, and network data transmission. Specifically, the work in this thesis contains three major parts, as follows.(1) The first part starts from introducing and discussing the traditional multi-channel data collection principle and the commonly used method. After that, parallel multi-channel data acquisition systems and various schemes are studied and analyzed. Then, a256-channel EEG data acquisition system is designed employing the ARM+FPGA as the underlying controller. The designed system not only improvements the EEG acquisition technology, but also has certain practical significance.(2) Based on the capability of processing multi-channel signal concurrently caused by FPGA’s parallelism, the second part proposes the design scheme of the synchronous and real-time data acquisition module to the large number of leads and the parallel AD conversion control. The scheme can effectively solve the difficulty of multi-channel data acquisition control. (3) Using the open source uIP protocol stack and UDP transmission protocol, the third part investigates the realization of remote monitoring of data network communication. Test results show that this method fully meets the application requirement of high speed data transmission in the simple network environment.The commissioning and analysis of collect waveforms from the developed EEG machine show that the precision EEG system design proposed in this thesis can achieve high-speed synchronous real-time acquisition for the256-lead EEG. All indices meet the design requirements. The system has the advantages of low internal noise, wide bandwidth, high anti-interference capability, and high fidelity of the collected waveform. The design method can provide certain guidance for developing multi-channel synchronous acquisition systems for biological signals.