Identification of Obstructive Sleep Apnea patients from tracheal breath sound analysis during wakefulness in polysomnographic studies
Document typeConference report
Rights accessRestricted access - publisher's policy
Obstructive Sleep Apnea (OSA) is currently diagnosed by a full nocturnal polysomnography (PSG), a very expensive and time-consuming method. In previous studies we were able to distinguish patients with OSA through formant frequencies of breath sound during sleep. In this study we aimed at identifying OSA patients from breath sound analysis during wakefulness. The respiratory sound was acquired by a tracheal microphone simultaneously to PSG recordings. We selected several cycles of consecutive inspiration and exhalation episodes in 10 mild-moderate (AHI<;30) and 13 severe (AHI>=30) OSA patients during their wake state before getting asleep. Each episode's formant frequencies were estimated by linear predictive coding. We studied several formant features, as well as their variability, in consecutive inspiration and exhalation episodes. In most subjects formant frequencies were similar during inspiration and exhalation. Formant features in some specific frequency band were significantly different in mild OSA as compared to severe OSA patients, and showed a decreasing correlation with OSA severity. These formant characteristics, in combination with some anthropometric measures, allowed the classification of OSA subjects between mild-moderate and severe groups with sensitivity (specificity) up to 88.9% (84.6%) and accuracy up to 86.4%. In conclusion, the information provided by formant frequencies of tracheal breath sound recorded during wakefulness may allow identifying subjects with severe OSA.
CitationSolà Soler, J. [et al.]. Identification of Obstructive Sleep Apnea patients from tracheal breath sound analysis during wakefulness in polysomnographic studies. A: IEEE Engineering in Medicine and Biology Society. "36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC)". Chicago: 2014, p. 4232-4235.
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos 
- IBEC - Institute for Bioengineering of Catalonia - Ponències/Comunicacions de congressos 
- BIOSPIN - Biomedical Signal Processing and Interpretation - Ponències/Comunicacions de congressos