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Novel Signal Noise Reduction Method through Cluster Analysis Applied to Photoplethysmography

机译:聚类分析的新型信号降噪方法在光电容积描记中的应用

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摘要

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.
机译:生理信号经常会被来自各种来源的噪音所污染。在本文中,描述了一种用于减少连续周期信号中的零星噪声的算法。该设计可用于需要周期性信号采样的地方,例如,当需要平均脉冲进行脉波分析和表征时。该算法基于聚类分析,用于从周期单中选择相似的重复或脉冲。此方法选择无噪声的单个脉冲,返回干净的脉冲信号,并在收到足够干净且有代表性的信号时终止。该算法设计得足够紧凑,可以在嵌入医疗设备的微控制器上实现。它已通过消除示例性光电容积描记(PPG)信号中的噪声得到了验证,随着信号噪声污染的增加,其收益也越来越大。该算法设计被普遍适用于广泛的生理(物理)信号。

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