Waugh William, Allen John, Wightman James, Sims Andrew J, Beale Thomas A W
Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK.
Northern Medical Physics and Clinical Engineering, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK.
Comput Math Methods Med. 2018 Jan 29;2018:6812404. doi: 10.1155/2018/6812404. eCollection 2018.
Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.
生理信号常常会受到来自各种源头的噪声污染。本文描述了一种用于减少连续周期性信号中散发性噪声的算法。该设计可用于需要周期性信号样本的情况，例如，当需要平均脉搏用于脉搏波分析和特征描述时。该算法基于聚类分析，用于从周期性单波中选择相似的重复波形或脉搏。此方法选择无噪声的单个脉搏，返回一个干净的脉搏信号，并在接收到足够干净且具有代表性的信号时终止。该算法设计得足够紧凑，可在医疗设备内嵌入的微控制器上实现。通过从一个典型的光电容积脉搏波描记图（PPG）信号中去除噪声，该算法得到了验证，结果表明随着信号噪声污染的增加，其益处也在增加。该算法设计具有通用性，适用于广泛的生理（物理）信号。
