<p>Arterial pulse wave measurement is beneficial in clinical health assessment and is important for effectively diagnosing different types of cardiovascular disease. Computational pulse signal analysis utilizes sensors and signal processing techniques to understand, classify, and predict disease pulse patterns. However, the choice of sensor types impacts the measurement results. This study presents the first comprehensive quantitative comparison of three sensor modalities (acoustic, optical, and pressure) for radial pulse measurement, employing a novel multi-parameter analysis framework that combines time-domain, frequency-domain, and PRV measures. Among various available types, three types of sensors are compared: an acoustic sensor, an optical sensor, and a pressure sensor. Pulse wave signals were recorded from the radial artery of 30 participants using these three sensors, and the performance was evaluated using various feature extraction methods like time domain, frequency domain and pulse rate variability (PRV) measures. Further, statistical analysis (ANOVA) of the PRV measures was carried out to compare the differences in the means of the various PRV measures. Time and frequency domain features varied across sensor types, but no statistical differences were found in PRV measures across sensors. Based on the experimental results, the pressure sensor was found to perform better in capturing comprehensive wrist pulse information. The research provides evidence-based guidelines for sensor selection in pulse wave analysis applications. The findings have direct applications in developing wearable cardiovascular monitoring devices, where sensor choice critically impacts device accuracy and reliability. and clinical settings requiring pulse wave analysis for cardiovascular disease diagnosis.</p>