Arteriosclerosis, increasing future risks of cardiovascular events even in its early stages, occurs in the vessel walls where stimulation stress, known as wall shear stress (WSS), is constantly lower than 0.4 Pa (referred to as low-WSS vessels). For early arteriosclerosis detection, we previously proposed a WSS-measurement method and detected low-WSS vessels by comparing the threshold value with the WSS calculated at a given moment when the mean flow-velocity maximized, presuming that the WSS maximized simultaneously at all measurement points. However, in reality, the moments were different between the upstream and downstream of blood flows because of the pulse wave propagation, and this difference resulted in false identification of low-WSS vessels. The objective of this study is to precisely identify low-WSS vessels by detecting the maximum-WSS during heartbeat cycles for each measurement point. We propose a method for identifying low-WSS vessels by calculating the WSS distributions in every frame and comparing the maximum-WSS with the threshold value for each measurement point. To evaluate the method, we compared it with the conventional one while identifying low-WSS vessels in a carotid-artery phantom. The precision of the classifications was assessed by the agreement rate between the echographic method and the ground truth, which was classified by the maximum-WSS measured by particle image velocimetry (PIV). The results revealed that the classification by our method agreed with that by the PIV in 84% of cases, and that by the conventional method agreed in 64%. In conclusion, our method increases the precision of low-WSS vessel identification.