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METHOD FOR CLASSIFYING PHOTOPLETHYSMOGRAPHY PULSES AND MONITORING OF CARDIAC ARRHYTHMIAS

机译:分类光学质肌监测脉冲和心律失常监测的方法

摘要

A method based on pulse wave analysis for monitoring cardiovascular vital signs, including: measuring a photoplethysmography (PPG) signal during a measurement time period such as to obtain a time series of PPG pulses; and during the measurement time period, identifying individual PPG pulses in the PPG signal, each PPG pulse corresponding to a PPG pulse cycle. For each PPG pulse, the method uses a pulse-wave analysis technique to determine, within the pulse cycle, at least one of: a time-related feature comprising a time duration and a normalized amplitude-related pulse-related feature and a SNR-related pulse-related. For each PPG pulse, a machine learning model is used in combination with the determined time-related, normalized amplitude-related and SNR-related features, to classify each PPG pulse in the pre-processed PPG signal as “normal”, “pathological” or “non-physiological” such as to output a time series of pulse classes.
机译:一种基于脉冲波分析的脉冲波分析,用于监测心血管生态体征,包括:测量时间段期间的光电容量术(PPG)信号,例如获得PPG脉冲的时间序列; 并且在测量时间段内,识别PPG信号中的单个PPG脉冲,每个PPG脉冲对应于PPG脉冲周期。 对于每个PPG脉冲,该方法使用脉冲波分析技术来确定脉冲周期内的至少一个:时间相关的特征,包括持续时间和归一化幅度相关的脉冲相关特征和SNR- 相关脉冲相关。 对于每个PPG脉冲,机器学习模型与所确定的时间相关的,归一化幅度相关的和与SNR相关的特征结合使用,以将预处理的PPG信号中的每个PPG脉冲分类为“正常”,“病理” 或“非生理”,例如输出脉冲类的时间序列。

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