Indic Premananda, Paydarfar David, Barbieri Riccardo
Department of Neurology, University of Massachusetts Medical School, MA 01655, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:3804-7. doi: 10.1109/IEMBS.2011.6090771.
Interbreath interval (IBI), the time interval between breaths, and its variations in time around the mean, the IBI variability, are important measures associated with irregularity of breathing. The IBI histogram generally follows a power law distribution with its characterizing parameters changing with maturation. To assess the dynamics of breathing we propose a point process model of IBI with a lognormal parametric structure to appropriately represent the stochastic nature of the IBI distribution. We estimate the time varying evolution of the characterizing parameters to represent the dynamic nature of breathing, and thereby provide a time-varying measure of irregularity in breathing. The reliability of the model to capture the data is assessed using Kolmogorov-Smirnov (KS) and independence tests. Our results validate the novel approach in the assessment of the irregularity of breathing by analyzing respiratory recordings from newborn rats and preterm infants.
呼吸间隔（IBI），即两次呼吸之间的时间间隔，以及其围绕均值随时间的变化，即IBI变异性，是与呼吸不规则性相关的重要指标。IBI直方图通常遵循幂律分布，其特征参数随成熟度而变化。为了评估呼吸动力学，我们提出了一种具有对数正态参数结构的IBI点过程模型，以适当表示IBI分布的随机性质。我们估计特征参数随时间的演变，以表示呼吸的动态性质，从而提供呼吸不规则性的时变度量。使用柯尔莫哥洛夫-斯米尔诺夫（KS）检验和独立性检验来评估模型捕捉数据的可靠性。我们的结果通过分析新生大鼠和早产儿的呼吸记录，验证了这种评估呼吸不规则性的新方法。
