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Non-Contact Real-Time Heart Rate Measurement Algorithm Based on PPG-Standard Deviation

机译:基于PPG标准偏差的非接触式实时心率测量算法

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摘要

Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as the heart rate signal for processing. However, this method is not accurate when the pixel values are changing greatly. To overcome this problem, non-contact real-time heart rate measurement method is proposed in this paper based on pixel standard deviation. Because of the changes in skin color caused by heart rate, the standard deviation signal of the green channel pixels in the region of interest (ROI) is filtered and extracted by the forward and inverse Fourier transform respectively, measuring the heart rate. The experimental results show that the improved algorithm can measure heart rate with faster speed and higher accuracy comparing to traditional methods. And we hope that our algorithm can apply in intelligent elder caring.
机译:心率是临床诊断的重要生理学参数,它可以推断人体的健康。因此,高效和准确的心率测量对于疾病诊断和健康监测很重要。有两种方法可以测量心率。一个是接触式,另一个是非接触。接触测量方法包括脉冲切割,心电图等。由于这种方法的不便,已经提出了一种非接触心率法。基于图像的传统非接触式测量方法在连续视频中收集RGB三声道信号,并选择绿色通道像素的平均值作为用于处理的心率信号。然而,当像素值大大改变时,这种方法不准确。为了克服这个问题,基于像素标准偏差,本文提出了非接触式实时心率测量方法。由于心率引起的皮肤颜色的变化,因此感兴趣区域(ROI)中的绿色通道像素的标准偏差信号分别通过前向和逆傅立叶变换进行滤波并提取,测量心率。实验结果表明,与传统方法相比,改进的算法可以以更快的速度和更高的准确度测量心率。我们希望我们的算法可以应用于智能长老的关怀。

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