Blood pressure is an important indicator of people's health. With the increasing distribution of hypertension, continuous blood pressure monitoring becomes more and more important. This paper presents a method for continuous noninvasive measurement of blood pressure based on long-term recursive convolution network. Firstly, the pulse wave signal collected by optical capacitance product method is normalized, threshold processing and feature extraction, and then the blood pressure is calculated from the pulse wave by long-term recursive convolution network. The experimental results show that when the pulse wave signal of optical capacitance product is directly input, the average absolute error and mean square error of the method are increased by 56.00% and 73.25% respectively. When the characteristic parameters are used as input, the average absolute error and mean square error of the experiment are increased by 59.55% and 87.41% compared with the direct input of optical capacitance product pulse wave signal. Compared with the direct input, the experimental effect of characteristic parameter input is better, and the accurate measurement of blood pressure is realized.