Automated respiratory phase and onset detection using only chest sound signal
The problem of non-invasive detection of respiratory phases and onsets without making direct airflow measurement is addressed here. Currently available techniques require the use of multichannel recorded sounds of both chest and trachea. In this paper, we propose a method which detects both respiratory phases and onsets using only chest sound data. Prior signal information in both time and frequency from the chest sound is exploited to isolate the lung component of the sound and the quasi-periodicity of its short-term energy is used to develop a configuration of nonlinear filters and bandpass filters to estimate the respiratory phase onsets. Performance results for the proposed method are reported for the case of low and medium flow rates. The average onset localizing accuracy of the proposed method is shown to be comparable to that obtained with data from more than one recording channel.