Eeg Detection Asic Design Study

The brain neural signal is a kind of the bioelectricity, and is caused by the activity of brain neural in nervous central. The professor Hans Berger is the first man to find and record the regular brain neural signal in 1924. After then, the research of the brain neural signal has been playing an important role for the biomedicine research and clinical application. And with the science's improvement, it's possible to realize the brain neural signal which is related to someone's thought, this makes a new research focus. So it's an important thigh to make the extraction of brain neural signal real, and my paper is done for this reason.In general, the amplitude of EEG in the cortex is about 10mV, but decreased to 1uV~100uV after passing through the cranium and skull. The patient oneself environment and circuit layout affect the measured EEG signal quality easily. The objective of this research is to design an analog integrated circuit chip for an EEG acquisition. The design is suitable for an analog front-end circuit of a portable EEG acquisition. By reducing the number of circuit component and noise, it can greatly enhance the signal quality to insure a better signal-to-noise ratio for preceding signal process and analysis tasks.The main blocks of the EEG acquisition chip includes one chopper-stabilized differential difference amplifier (CHSDDA), one band-pass filter, one 50Hz notch, other gain amplifier, one non-overlapping clock generator, and voltage reference circuit. I have never seen a 50Hz notch circuit integrated with other amplifiers in the same chip in the papers I have seen, so it's a creative thing in my paper. Because a chip used in the EEG acquisition with a 50Hz notch can improve the quality of signal. These circuits have been designed with standard CMOS IC process of CSMC 0.5um CMOS double poly double metal. Full custom design flow has been used in this research.In order to evaluate the performance of these designs, these circuits has simulated by the Cadence Spectre. The results demonstrate that it meets the system specifications. It is proved that by the integrating method, the System-On-a-Chip (SOC) approach for the medical instrumentation design is feasible.