RESEARCH ARTICLE Sleep-Wake Evaluation fromWhole-Night Non-Contact Audio Recordings of Breathing Sounds

Study Objectives To develop and validate a novel non-contact system for whole-night sleep evaluation using breathing sounds analysis (BSA). Design Whole-night breathing sounds (using ambient microphone) and polysomnography (PSG) were simultaneously collected at a sleep laboratory (mean recording time 7.1 hours). A set of acoustic features quantifying breathing pattern were developed to distinguish between sleep and wake epochs (30 sec segments). Epochs (n = 59,108 design study and n = 68,560 validation study) were classified using AdaBoost classifier and validated epoch-by-epoch for sensitivity, specificity, positive and negative predictive values, accura-cy, and Cohen's kappa. Sleep quality parameters were calculated based on the sleep/wake classifications and compared with PSG for validity. Setting University affiliated sleep-wake disorder center and biomedical signal processing laboratory. Patients One hundred and fifty patients (age 54.0±14.8 years, BMI 31.6±5.5 kg/m2, m/f 97/53) re-ferred for PSG were prospectively and consecutively recruited. The system was trained (de-sign study) on 80 subjects; validation study was blindly performed on the additional 70 subjects. Measurements and Results Epoch-by-epoch accuracy rate for the validation study was 83.3 % with sensitivity of 92.2% (sleep as sleep), specificity of 56.6 % (awake as awake), and Cohen's kappa of 0.508