Golemati Spyretta, Moupagiatzis Ioannis, Athanasopoulos Dimitrios, Vasilopoulou Maroula, Roussos Charalambos, Vogiatzis Ioannis
Medical School, National Kapodistrian University of Athens, Greece.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:2871-4. doi: 10.1109/IEMBS.2009.5333106.
Asynchronous breathing movements may be observed in the presence of pulmonary disease, such as chronic obstructive pulmonary disease (COPD). This study was undertaken in an attempt to propose a reliable methodology to quantify this asynchrony. Five methods for estimating phase differences between two signals, based on the phase angle of the Fourier Transform (PhD(FT)), paradoxical motion (PhD(PM)), the Lissajous figure (PhD(LF)), maximal linear correlation (PhD(P)) and least-squares filtering (PhD(LS)), were compared. Frequency-modulated signals, simulating compartmental chest wall volumes, were used to evaluate the methods. Breathing asynchrony was quantified in two ways; by estimating (a) a single PhD value for the entire recording and (b) time-varying PhDs, representing non-stationarities of human breathing. PhD(PM) and PhD(LF) had the lowest average errors (4%), and PhD(LS) had a slightly higher error. PhD(FT) had zero error when estimating a single PhD value but a considerable error when estimating time-varying PhDs. PhD(P) presented the highest errors in all cases. An application of this methodology is proposed in real compartmental chest wall volume signals of normal and COPD subjects. Preliminary results indicate that the methodology is promising in quantifying differences in asynchronous breathing between thoracic volumes of COPD patients and healthy controls.
在存在肺部疾病(如慢性阻塞性肺疾病(COPD))的情况下,可能会观察到异步呼吸运动。本研究旨在提出一种可靠的方法来量化这种异步性。比较了基于傅里叶变换的相位角(PhD(FT))、矛盾运动(PhD(PM))、李萨如图形(PhD(LF))、最大线性相关性(PhD(P))和最小二乘滤波(PhD(LS))这五种估计两个信号之间相位差的方法。使用模拟胸壁各部分容积的调频信号来评估这些方法。通过两种方式对呼吸异步性进行量化:(a)估计整个记录的单个PhD值;(b)估计随时间变化的PhD值,以表示人类呼吸的非平稳性。PhD(PM)和PhD(LF)的平均误差最低(4%),PhD(LS)的误差略高。PhD(FT)在估计单个PhD值时误差为零,但在估计随时间变化的PhD值时误差较大。PhD(P)在所有情况下误差最高。建议将该方法应用于正常人和COPD患者的实际胸壁各部分容积信号。初步结果表明,该方法在量化COPD患者和健康对照者胸廓容积之间的异步呼吸差异方面具有前景。