Nocturnal sound analysis for the diagnosis of obstructive sleep apnea
| Autor: | Yaniv Zigel, Nir Ben-Israel, Ariel Tarasiuk |
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| Předmět: |
Male
medicine.medical_specialty Polysomnography Bayes classifier Audiology Cepstrum Medicine Humans Respiratory Sounds Sleep Apnea Obstructive business.industry Snoring Sleep apnea Apnea Acoustics Darkness Middle Aged medicine.disease respiratory tract diseases Obstructive sleep apnea Noise Apnea–hypopnea index Female Mel-frequency cepstrum medicine.symptom business |
| Zdroj: | Scopus-Elsevier |
| Popis: | A novel method for screening obstructive sleep apnea syndrome (OSAs) based on nocturnal acoustic signal is proposed. Full-night audio signals from sixty subjects were segmented into snore, noise and silence events using semi-automatic algorithm based on Gaussian mixture models which achieves more than 90% (92%) sensitivity (specificity) and produces an average of 2,000 snores per subject. A classification into 3 groups is proposed for the diagnosis: comparison group - non-OSA subjects (apnea hypopnea index, AHI10), mild to moderate OSA (10AHI30) and severe OSA (AHI30). A Bayes classifier was implemented, fed with five acoustic features, all correlated with the severity of the syndrome: (1) Inter Event Silence, which quantifies segments suspicious as apnea; (2) Mel Cepstability, measures the entire night stability of the spectrum, expressed using mel-frequency cepstrum; (3) Energy Running Variance, a criterion for the variation of the nocturnal acoustic pattern; (4) Apneic Phase Ratio, exploiting the finding that snores around apnea events expressing larger acoustic variation; and (5) Pitch Density. Correct classification of 92% for resubstitution method and 80% for 5-fold cross validation method was achieved. Moreover, in a case of two groups with a threshold of AHI=10, a sensitivity (specificity) of 96.5% (90.6%) and 87.5% (82.1%) for resubstitution and cross-validation respectively were obtained. |
| Databáze: | OpenAIRE |
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