接收器工作特性分析揭示尺度相关小波和频谱测量用于评估心功能不全的优越性
Receiver-Operating-Characteristic Analysis Reveals Superiority of Scale-Dependent Wavelet and Spectral Measures for Assessing Cardiac Dysfunction
摘要：
受试者工作特征（ROC）分析用于评估各种心率变异性（HRV）测量的适用性，以将不同长度的心电图记录正确分类为正常或显示心力衰竭的存在。尺度相关的心率变异性的措施被认为是显著优于尺度独立的措施（标度指数）区分两类数据在广泛的记录长度。小波系数标准偏差在一个规模近32心跳间隔，其光谱对应的1/32周期每间隔，提供可靠的结果，使用记录长度只有几分钟长。围绕分形高斯噪声内核构建的抖动积分和发射模型提供了一个逼真的，但不完美的心跳序列模拟。
英文摘要：
Receiver-operating-characteristic (ROC) analysis was used to assess the suitability of various heart rate variability (HRV) measures for correctly classifying electrocardiogram records of varying lengths as normal or revealing the presence of heart failure. Scale-dependent HRV measures were found to be substantially superior to scale-independent measures (scaling exponents) for discriminating the two classes of data over a broad range of record lengths. The wavelet-coefficient standard deviation at a scale near 32 heartbeat intervals, and its spectral counterpart near 1/32 cycles per interval, provide reliable results using record lengths just minutes long. A jittered integrate-and-fire model built around a fractal Gaussian-noise kernel provides a realistic, though not perfect, simulation of heartbeat sequences.
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