Detailed evaluation of sleep apnea using heart rate variability: a machine learning and statistical method using ECG data

HRV parameters can efficiently reflect autonomic disruption induced by SAAs, especially nonlinear and frequency domain indices. Augmented by machine learning, HRV analysis is a powerful and scalable technique toward real-time, non-invasive screening of sleep disordered breathing that can be implemented in to wearable health technology and digital sleep medicine.