Using physiological signals to predict apnea in preterm infants

摘要: Apnea of prematurity, a common developmental disorder in preterm infants, is implicated long-term neurodevelopmental deficits. Preventative clinical interventions, such as mechanosensory stimulation, would benefit from predictive knowledge when the patient at high risk for apnea. In this study, utility features derived breathing rate and heart explored. Specifically, multiscale correlation structure interbreath intervals heartbeat used to train patient-specific apnea prediction algorithm. The algorithm's results are significantly better than chance three six patients it evaluated on. These preliminary studies suggest that cardiopulmonary signals can anticipate occurrence clinically significant apneas infants.