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Intelligent methods for identifying respiratory cycle phases from tracheal sound signal during sleep |
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| Authors: | A. Kulkas [Author Vitae] E. Huupponen [Author Vitae] [Author Vitae] M. Tenhunen [Author Vitae] [Author Vitae] E. Rauhala [Author Vitae] S.-L. Himanen [Author Vitae] |
| Affiliation: | a Department of Clinical Neurophysiology, Medical Imaging Centre, Pirkanmaa Hospital District, Tampere, Finland b Sleep Laboratory, Brain Work Research Center, Finnish Institute of Occupational Health, Helsinki, Finland c Department of Clinical Neurophysiology, Satakunta Central Hospital, Pori, Finland d Medical School, Tampere University, Tampere, Finland |
| Abstract: | We present two methods for identifying respiratory cycle phases from tracheal sound signal during sleep. The methods utilize the Hilbert transform in envelope extraction. They determine automatically a patient-specific amplitude threshold to be used in the detection. The core of one method is designed to be amplitude-independent whereas the other method uses solely the amplitude information. The methods provided average sensitivities of 98% and 99%, respectively, and positive prediction values of 100% on the total of 1434 respiratory cycles analysed from six different patients. The developed methods seem promising as such or as tools for analysing sleep disordered breathing. |
| Keywords: | Tracheal sound Respiratory cycle Hilbert transform Sleep disordered breathing Automated detection |
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