Biopotential signals are important to physicians for diagnosing medical conditions in patients. Traditionally, biopotentials are acquired using contact electrodes together with instrumentation amplifiers (INAs). The biopotentials are generally weak and in the presence of stronger common mode signals. The INA thus needs to have very good Common Mode Rejection Ratio (CMRR) to amplify the weak biopotential while rejecting the stronger common mode interferers. Opamp based INAs with a resistor-capacitor feedback are suitable for acquiring biopotentials with low power and low noise performance. However, CMRR of such INA topologies is typically very poor. In the presented research, a technique is proposed for improving the CMRR of opamp based INAs in RC feedback configurations by dynamically matching input and feedback capacitor pairs. Two instrumentation amplifiers (one fully differential and the other fully balanced fully symmetric) are designed with the proposed dynamic element matching scheme. Post layout simulation results show that with 1 percent mismatch between the limiting capacitor pairs, CMRR is improved to above 150dB when the proposed dynamic element matching scheme is used. The INAs draw about 10uA of quiescent current from a 1.5 dual power supply source. The input referred noise of the INAs is less than 3uV/sqrt(Hz).

This master thesis dwells on EEGbiofeedback (also called Neurofeedback) interface of human brain and the computer and its concrete realization in Java programming language. This system is founded on the basis of the computer, which is accomplishing biological feedback (biofeedback) and the electroencephalography (EEG) by helping that state's scanning of user's brain is realized. By this way is possible to practise the human brain effectively to achieve better concentration, the elimination of sleeping and learning deficiency. Hereafter is the suggestion of direction control of computer mouse by EEG device incorporated, which makes it possible for the man to regulate the direction of the cursor's movement on the screen by the frequency of brain's oscillation. The motivation for solution of this problem is the effort to help to handicapped people to communicate with surrounding world. The introduction of this paper contains the basic facts about human brain, electroencephalography and EEG biofeedback. The following chapters dwell on the specification of claims to developed application, its suggestion and description of actual realization. The final part relates to the BCI (Brain-Computer Interface) systems and suggestion of computer's control by EEGappliance with evaluation of attained results.