【摘要】 心率是人身体健康的一个重要指标，从人脸视频中检测心率是一种正在快速发展的非接触式检测方法，但该方法的结果准确性易受光照变化及受试者头部运动等噪声影响。为了消除噪声影响，提高心率检测准确性，文章创新性地提出了一种新的思路：将光照变化和头部运动噪声作为目标进行趋势拟合并从相机原始信号中消除，以实现高信噪比的人体心率信号提取。为验证方法的可行性，以医用指夹式脉搏血氧仪的数值为参考心率，通过对比结果在参考心率处的平均信噪比和心率检测准确率，提出的方法相比POS方法提高了9.60%,37.19%;相比于ICA算法提高了48.48%,51.75%。实验结果表明，提出的新方法具有较好的去噪能力和较高的精准度。更多还原

【Abstract】 Heart rate is an important indicator of human health. Detecting heart rate from face videos is a rapidly developing non-contact detection method, but the accuracy of the results is susceptible to noise such as changes of illumination and head movements of the subject. In order to eliminate the influence of noise and improve the accuracy of heart rate detection, a new idea is innovatively proposed: Illumination changes and head motion noise are used as targets for trend fitting and eliminated from the camera raw signal to achieve human heart rate signal extraction with high signal-to-noise ratio. In order to verify the feasibility of the proposed method, the value of the medical finger-clip pulse oximeter is used as the reference heart rate. By comparing the average signal-to-noise ratio at the reference heart rate and heart rate detection accuracy, the proposed method has increased by 9.60% and 37.19% compared with the POS method. Compared with the ICA algorithm, it has increased by 48.48% and 51.75%. Experimental results show that the new proposed method has better denoising ability and higher accuracy.更多还原