Extracting Human Brain Signals from the EEG Records Using LabVIEW and Advanced Signal Processing

Abstract

Human brain signals recognition is increasingly becoming a very popular aspect for disease prediction. The main important features of EEG records are liveliness and the robustness against falsification. A comprehensive study on human brain signals based on EEG records remain the challenge. Nowadays, low-cost wireless EEG recording devices are growing very fast on the market. These devices from different vendors have a huge potential in many applications, and the user might need to test the bunch of the devices to choose the preferable one. To extract human brain signals from the complex record there is a need, at first, to remove noise, breathing, and heart beating components. In this study, we propose a method for human brain signal identification using EEG records obtained from low-cost devices using the LabVIEW library. After that, we suggest using the advanced signal processing of the human brain signals. In this article, the achieved results are very promising. A special antenna and signal processing toolchain were developed. The signal processing based on file record and playback. After playback processing, the results are separated into two main graphs: one is the breathing and heart beating components; another one is the brain signals graph. This method is very promising for predicting future areas of human brain damage.