Journal de bio-ingénierie et des sciences biomédicales

Automatic Cycle Identification in Tidal Breathing Signals

Abstract

Zuojun Wang, Yanwu Ding, Douglas F. Parham and Kanghee Lee

In this paper, we introduce a novel cycle identification algorithm using MATLAB programming to automatically identify cycles in tidal breathing signals. The algorithm was designed in four steps using filtering, derivation, and other signal processing techniques. To verify the accuracy of the proposed algorithm, its results were compared with those of cycles identified manually by a human coder. Simulations results showed that despite the complexity of respiratory signals, the proposed algorithm could identify cycles more accurately than the human coder. This algorithm could serve as an important first step toward timely identification and coding for more complex respiratory signals, such as those underlying speech productions.