Nonlinear dynamics of heart rate variability in children with asthmatic symptoms

Abstract

Asthma is a chronic lung disease that is prone to start during chilhood. Although symptoms can be usually controlled with medication, early diagnosis is crucial to reduce the risk of permanent airway obstruction. Despite the fact that origin of asthma is still uncertain, abnormal parasympathetic nervous system (PNS) activity has been pointed out to play a major role in its pathogenesis. In this work the use of nonlinear heart rate variability (HRV) indexes is proposed in order to look for differences between children classified as high- or low-risk of suffering from asthma in the future. PNS activity is assessed trough a filtered HRV signal. Correlation dimension analysis showed statistically significant differences distinguishing high-and low-risk. Decreased complexity observed in high-risk group suggests that abnormal PNS activity might be related with increased risk of developing asthma.