▎ 摘　　要

NOVELTY - The method involves dropping a known sample to a graphene foam sensor. A resistance between foam graphene sensor electrodes is collected. A known sample electrochemical characteristic is extracted according to the output resistance. Feature vectors of the known sample are obtained. A training result of the known sample is obtained. The known sample is detected by utilizing a support vector machine algorithm. Normalization process is performed. A maximum resistance value of a resistor is calculated. USE - Support vector machine based foam graphene sensor sample detection method. DETAILED DESCRIPTION - An INDEPENDENT CLAIM is also included for a support vector machine based foam graphene sensor sample detection system. DESCRIPTION OF DRAWING(S) - The drawing shows a flow diagram illustrating a support vector machine based foam graphene sensor sample detection method. '(Drawing includes non-English language text)'