Figure 1:

Proposed workflow for developing and validating the CNN enabling prediction of the severity of OSA in children based on their overnight raw ECG signal recordings. CHAT: Childhood Adenotonsillectomy Trial; PSG: polysomnography; ECG: LPF: low pass filter; electrocardiogram; CNN: convolutional neural network; AHI: apnea-hypopnea index; SVR: support vector regression; OSA: obstructive sleep apnea. $AH{I}_{cnn}$: rate of apnea events per subject calculated after CNN regression; $AH{I}_{\mathit{\text{actual}}}$: actual AHI extracted from CHAT database; $AH{I}_{est}$: final estimated AHI after SVR fitting. ${\mathrm{S}}_{\mathrm{N}}$: segment $\mathrm{N};{\widehat{y}}_{\mathrm{N}}$: estimation of apneic events in segment N.