Abstract: Focusing on the discriminant for human body physiological state,this paper presented that the pulse period and height of systolic peak from the time domain are extracted as the input feature vectors of support vector machine (SVM).Through a binary classification model built by the method of supervised learning,the physiological state is judged as normal state or event state.Finally,we took three experiments:movement,sleep and drink.The statistical analysis and evaluation result show that the classification performance of SVM is excellent.

Key words: Pulse,Support vector machine,Physiological state