This paper presents an algorithm for accurate and improved detection of the first heart sound S1for heart sound cardiac cycle segmentation under noisy environments. The proposed algorithm integrates an S1/S2selection step and an S1identification step. An adaptive sub-level tracking algorithm based on wavelet transform is proposed to separate the S1and S2from other components such as murmurs and noises. This is followed by a detection procedure based on Shannon energy to reject the overlapping interference so that the peaks of S1and S2can be detected. Criteria of time interval, energy and phonocardiogram (PCG) collecting position are used to identify S1with respect to the beginning of each cardiac cycle. Experimental results show that the proposed algorithm leads to an efficient segmentation of PCG cycle. Due to its simplicity and fast implementation, the method can be deployed clinically for further analysis and eventual use.