We are in process of developing an image-free, single element ultrasound system for automated evaluation of arterial stiffness, we call it ARTSENS. The lack of a guiding image for arterial visualization necessitates intelligent analysis of ultrasound radio frequency (RF) echo signals to obtain reliable measurements. In this paper, we propose a novel algorithm to parameterize the echo signal received from the common carotid artery (CCA) to improve accuracy and reliability of arterial stiffness measurement. The echo signal quality is parameterized using features such as sharpness of arterial wall and energy ratio. A signal quality score is calculated by integrating the results from each feature. This score is used to triage the set of available echo signals recorded from each subject and select the best signal for computation of stiffness values. The performance of signal quality algorithm is tested using a database of carotid artery echo signals recorded from 28 human volunteers. It was observed that both the accuracy and reliability of the stiffness measurements were improved after triaging using the signal quality parameterization algorithm. © 2014 IEEE.