Cycle detection in speech breathing signals

As with any physiological process, breathing behaviors can be represented by time-varying signals. Speech breathing, or breathing behavior that supports speech production, is one particular type of breathing that can be difficult and time-consuming to analyze visually. In this paper, we introduce a novel cycle identification algorithm using MATLAB programming that automatically identifies breath cycles in speech breathing signals. The results of simulations have shown that the proposed algorithm can identify breath cycles correctly and efficiently despite the complexity of speech breathing signals. The use of this algorithm can help researchers and clinicians more easily identify and analyze cycles associated with speech breathing.