Due to the complexity in respiratory signals, an experienced coder is often required to identify the acceptable cycles and mark the start and end times for each cycle. This algorithm is an important step toward timely identification and coding of more complex respiratory signals and more efficient analysis for physiological signals. Simulation results have shown that the proposed algorithm can identify cycles correctly and efficiently.