The prevalence of atrial fibrillation (AF) increases with the age，and the recurrence rate is very high．It is necessary to propose an accurate and fast algorithm to distinguish AF．Based on the fourth statistical theory，a quantitative method for distinguishing AF from normal sinus rhythm (NSR) is proposed in this paper combining the chaos character and Yin Yang nature of heart system．Firstly，the phase space with embedding dimension of 6 and delay time from 1 to 30 is constructed by using R-R interval data．The probability density function (PDF) graph is obtained in turn．Then the horizontal axis of PDF graph is taken as strength ξ，the cumulative sum of longitudinal axis is taken as distribution function x，and the fourth statistical theory parameter k value is fitted by the corresponding relation of ξ-x．Finally，differential summation with k and the result is defined as Ksd. From the experiment， Ksd=0.3 can be an important parameter to distinguish AF from NSR．This study can not only distinguish AF and NSR by describing Yin and Yang，but also open a new path for exploration of the fourth statistical theory and provide an important evidence for the accurate and rapid detection of AF in the future．