The present paper proposes a novel methodology to monitor sleep apnea through thermal imaging. First, the nostril region is segmented and it is tracked over time via a network of cooperating probabilistic trackers. Then, the mean thermal signal of the nostril region, carrying the breathing information, is analyzed through wavelet decomposition. The experimental set included 22 subjects (12 men and 10 women). The sleep-disordered incidents were detected by both thermal and standard polysomnographic methodologies. The high accuracy confirms the validity of the proposed approach, and brings non-obtrusive clinical monitoring of sleep disorders within reach. © 2009 Springer-Verlag.
CITATION STYLE
Fei, J., Pavlidis, I., & Murthy, J. (2009). Thermal vision for sleep apnea monitoring. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5762 LNCS, pp. 1084–1091). https://doi.org/10.1007/978-3-642-04271-3_131
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