https://www.selleckchem.com/products/fdi-6.html The purpose of this work is to study whether the active state and species of biological tissues can influence changes in their dielectric properties. In this paper, the dielectric properties of liver, kidney and spleen tissues from human active, human inactive and animal tissues are measured in the frequency range of 10 Hz to 100 MHz. The four- and two-electrode methods are used to measure dielectric properties at different frequencies. Statistical analysis and the pattern recognition method are used to compare the dielectric properties of human active tissues, human inactive tissues, animal tissues and data provided by the IFAC database. The results show that the dielectric properties of human active tissues are significantly different from those of human inactive tissues and animal tissues, resulting in a great difference between the dielectric properties provided by the IFAC database and those of human active tissues. The dielectric properties of human active tissues can be identified by the pattern recognition method based on principal component analysis, which further proves that the dielectric properties of human active tissues cannot be replaced. The dielectric properties of biological tissues are closely related to the activity and species of tissues. The dielectric properties of human active tissues cannot be replaced by those of human cadaver tissues or animal tissues. The significance of this study is suggesting that the IFAC database should be updated with the dielectric properties of human active tissues to provide accurate data for bioelectromagnetics research. The significance of this study is suggesting that the IFAC database should be updated with the dielectric properties of human active tissues to provide accurate data for bioelectromagnetics research.This article shows the interest in deep learning techniques to detect motor imagery (MI) from raw electroencephalographic (EEG) signals when a function