Real-time detection, classification, and quantification of apneic episodes using miniature surface motion sensors in rats Academic Article uri icon


  • Background: Real-time detection and classification of apneic episodes remain significant challenges. This study explores the applicability of a novel method of monitoring the respiratory effort and dynamics for rapid detection and classification of apneic episodes. Methods: Obstructive apnea (OA) and hypopnea/central apnea (CA) were induced in nine tracheostomized rats, by short-lived airway obstruction and administration of succinylcholine, respectively. Esophageal pressure (EP), EtCO2, arterial O2 saturation (SpO2), heart rate, and blood pressure were monitored. Respiratory dynamics were monitored utilizing three miniature motion sensors placed on the chest and epigastrium. Three indices were derived from these sensors: amplitude of the tidal chest wall displacement (TDi), breath time length (BTL), that included inspiration and rapid expiration phases, and amplitude time integral (ATI), the integral of breath amplitude over time. Results: OA induced a progressive 6.42 ± 3.48-fold increase in EP from baseline, which paralleled a 3.04 ± 1.19-fold increase in TDi (P < 0.0012), a 1.39 ± 0.22-fold increase in BTL (P < 0.0002), and a 3.32 ± 1.40-fold rise in the ATI (P < 0.024). During central hypopneic/apneic episodes, each sensor revealed a gradual decrease in TDi, which culminated in absence of breathing attempts. Conclusion: Noninvasive monitoring of chest wall dynamics enables detection and classification of central and obstructive apneic episodes, which tightly correlates with the EP.

publication date

  • January 1, 2015