An artificial intelligence-based (AI-based) noninvasive Pulse AudioGram (PAG) monitoring device with arrhythmia screening algorithm has been developed in this research study. The PAG monitoring device consists of four components, including an audiogram sensor, an analog-digital converter, a microprocessor, and a data storage unit. The main function of the proposed AI-based non-invasive PAG is to measure the audio signal in radial artery generated by hemodynamics. Hemodynamics under arrhythmia and sinus rhythm (SR) conditions might exhibit different patterns as the heart rhythm becomes irregular under arrhythmia condition. PAG signals of SR and other arrhythmia symptoms such as atrial fibrillation (AF), aortic regurgitation (AR), and congestive heart failure (CHF) were collected during this research. In the experiment results, the proposed method can achieve accuracy of 99.29% when discriminating SR and AF; the proposed method can achieve accuracy of 98.92% when discriminating SR, AF, AR, and CHF. In this study, we have successfully developed an AI-based non-invasive PAG monitoring device for arrhythmia screening, and have plan to use it in on large-scale screening for arrhythmia in the near future.