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Non-Contact Heart Rate Monitoring Using Lab Color Space

机译:使用实验室颜色空间的非接触式心率监测

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摘要

Research progressing during the last decade focuses more on non-contact based systems to monitor Heart Rate (HR) which are simple, low-cost and comfortable to use. Most of the non-contact based systems are using RGB videos which is suitable for lab environment. However, it needs to progress considerably before they can be applied in real life applications. As luminance (light) has significance contribution on RGB videos HR monitoring using RGB videos are not efficient enough in real life applications in outdoor environment. This paper presents a HR monitoring method using Lab color facial video captured by a webcam of a laptop computer. Lab color space is device independent and HR can be extracted through facial skin color variation caused by blood circulation considering variable environmental light. Here, three different signal processing methods i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA) have been applied on the color channels in video recordings and blood volume pulse (BVP) has been extracted from the facial regions. In this study, HR is subsequently quantified and compare with a reference measurement. The result shows that high degrees of accuracy have been achieved compared to the reference measurements. Thus, this technology has significant potential for advancing personal health care, telemedicine and many real life applications such as driver monitoring.
机译:在过去十年中的研究进展更多地关注基于非接触的系统,以监测简单,低成本和使用舒适的心率(HR)。大多数非联系人的系统都使用适用于实验室环境的RGB视频。但是,在可以在现实生活中应用之前,它需要大大进展。作为亮度(光)对RGB视频的显着贡献,使用RGB视频的HR监控在室外环境中的现实生活中不足以效率。本文介绍了使用笔记本电脑的网络摄像头捕获的实验室彩色面部视频的HR监测方法。实验室颜色空间是设备独立的,可以通过考虑变量环境光的血液循环引起的面部肤色变化来提取HR。这里,三种不同的信号处理方法即,快速傅里叶变换(FFT),独立分量分析(ICA)和主成分分析(PCA)已经应用于视频记录中的颜色通道,并从中提取了血容量脉冲(BVP)面部地区。在该研究中,随后量化HR并与参考测量进行比较。结果表明,与参考测量相比,已经实现了高精度。因此,该技术具有推进个人医疗保健,远程医疗和许多现实生活应用的重要潜力,例如驾驶员监测。

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