Designing of Battery-Based Low Noise Electroencephalography (EEG) Amplifier for Brain Signal Monitoring: A Simulation Study

An electroencephalogram (EEG) is a noninvasive technique that records electrical activity in the human brain for diagnosing and treating numerous brain diseases and disorders. The common mode rejection ratio and signal-to-noise ratio tend to reduce by the insertion of noise signals into the microvolt (μV) level of the EEG signal. EEG based brain disease detection can be conducted with an EEG signal acquisition system (BB-ESAS) which can be developed with the EEG sensors/electrodes, instrumentation amplifiers, filtering circuits, analog to digital converter, data acquisition card, and signal processing algorithm. The selection of instrumentation amplifiers plays a significant role in developing an efficient ESAS. Moreover, the battery based instrumentation has a capability of reducing the noises present in the EEG signal. In this paper, a battery based ESAS (BB-ESAS) has been modeled and simulated in NI Multisim software and the frequency response and the noise response have been studied with AD8428. AD8428 is found as an ultralow noise amplifier and delivers leading gain accuracy, noise, and bandwidth. The proposed BB-ESAS is studied, verified, and assessed with low frequency low amplitude signals in circuit simulation software. Results from the circuit simulation showed that the established BB-ESAS with AD8428 is suitable for the EEG signal acquisition with high SNR for the brain disease detection system.