Institute of Microelectronics of Chinese Academy of Sciences, No. 3 Beitucheng West Road, Chaoyang District, Beijing 100029, China; University of Chinese Academy of Sciences, China; Beijing Key Laboratory for Next Generation RF Communication Chip Technology, China.
Institute of Microelectronics of Chinese Academy of Sciences, No. 3 Beitucheng West Road, Chaoyang District, Beijing 100029, China; Beijing Key Laboratory for Next Generation RF Communication Chip Technology, China.
Comput Methods Programs Biomed. 2020 Jun;189:105321. doi: 10.1016/j.cmpb.2020.105321. Epub 2020 Jan 10.
Pulse wave is one of the biomedical signals that has been studied over the past years. Accurate recognition of feature points is the basis of verifying the connections between pulse waves and certain diseases. Therefore, the aim of the study is to discuss the use of angle mapping on feature points recognition.
The mathematical method is based on the application of angle curve with parameter " k " on pulse wave. The data used is collected by PVDF sensor. Approximate curve and mathematical model are used for the discussion of the influence of parameter k and pulse wave amplitude by numerical calculation. The conclusion drawn from the numerical solution is that when k changes to maximize the angle extremum value, the corresponding position of angle extremum point is the feature point position. For the sampling rate f = 455Hz in this paper, k can be taken from 5 to 15.
We present the recognition results of unobvious feature points based on the "angle extremum maximum method" and corresponding angle values. The results are compared with traditional methods and the determination of angle threshold value is discussed.
This method can be used for accurate and efficient feature points identification, and it can be better applied to pulse waves with noise or unobvious feature points.
脉搏波是近年来研究较多的生物医学信号之一。准确识别特征点是验证脉搏波与某些疾病之间关联的基础。因此，本研究旨在探讨角度映射在特征点识别中的应用。
该数学方法基于应用参数“k”的角度曲线对脉搏波进行分析。使用 PVDF 传感器采集数据。通过数值计算，对参数 k 和脉搏波幅度对近似曲线和数学模型的影响进行讨论。数值解得出的结论是，当 k 变化以最大化角度极值时，角度极值点的相应位置就是特征点位置。对于本文中采样率 f=455Hz 的情况，k 可以取 5 到 15。
我们提出了基于“角度极值最大法”的不明显特征点识别结果及其相应的角度值。并将结果与传统方法进行了比较，讨论了角度阈值的确定。
该方法可用于准确高效的特征点识别，并且可以更好地应用于具有噪声或不明显特征点的脉搏波。
