The development and application of pulse diagnostic instruments provide an objective basis for the intelligent diagnosis of traditional Chinese medicine. However， the existing pulse diagnostic instruments do not consider the influence of the collection region （Cun， Guan， Chi） and pressure （Fu， Zhong， Chen） on the diagnostic results， and there is still room for the improvement of the diagnostic accuracy. In order to recognize pulse condition more accurately， this paper presents an intelligent pulse diagnosis system based on flexible sensors and the corresponding pulse signal processing method. By installing three array flexible sensors at the collection region of Cun， Guan and Chi and setting different pressure thresholds of Fu， Zhong and Chen， multiple pulse signals are obtained. Signal features are then extracted， and multi-channel features are integrated based on multi-set canonical correlations analysis （MCCA） to get more pulse information. Experimental results show that the proposed method can further improve the accuracy of pulse condition classification in four typical pulse types. The multi-point pulse condition induction designed in this paper based on two aspects of region and pressure can simulate and restore the real Chinese medicine diagnosis process and help to extract real pulse signals， providing a theoretical basis and reference value for the subsequent research and development of intelligent pulse diagnosis instruments based on flexible sensors.