Preprocessing for QEEG Analysis

Background Quantitative Electroencephalography (QEEG) analysis has been attempted in earnest since 1980. Power is squared to the amplitude and applied to Gamma band calculated analysis. Recently, electrodes in QEEG was set to a point in a specific area, making new analyses called Network analysis, which analyzes the various relationships among different electrodes, such as connectivity, consistency, phase locking value. However, the data from the clinical collection of the patient are thought to lack preparation skill for QEEG analysis. Therefore, this section discusses what preparations should be made before performing the end of QEEG recording. Methods Before recording, QEEG sited to sampling rate and filters provided the software by the QEEG equipment. The use of filters can be measured using preprocessing that removing the oily substances and foreign substances from the scalp and attaching them to the scalp as closely as possible using gauze. During the measurement, the various stimuli, such as a photic, hyperventilation, and sleep, are used to trigger abnormal QEEG. Before these measurements, the resting state without sleeping with the eyes closed can be measured for about 5 minutes and used as a control in the analysis results. In addition, quality data can be obtained by monitoring QEEG during measurement and eliminating repetitive noise. Results We can make good quality data, used to recommending our methods. Conclusion The Korean Journal of Clinical Laboratory Science finds eight studies by “QEEG” from 1982 to 2018. That results in very lack than another research area. Because of analyzing EEG represented by pictures to monitor and EEG isn’t familiar to quantitative analysis methods. This paper introduced how to make good quality data before performing a full-scale analysis. Based on this information, we hope to use good data to produce good results and to produce good research in the field of clinical physiology [This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No.NRF-2016R1CB2010739)].