Subject movement and a dark environment will increase the difficulty of image-based contactless pulse rate detection. In this paper, we detected the subject’s motion status based on complexion tracking and proposed a motion index (MI) to filter motion artifacts in order to increase pulse rate measurement accuracy. Additionally, we integrated the near infrared (NIR) LEDs with the adopted sensor and proposed an effective method to measure the pulse rate in a dark environment. To achieve real-time data processing, the proposed framework is constructed on a Field Programmable Gate Array (FPGA) platform. Next, the instant pulse rate and motion status are transmitted to a smartphone for remote monitoring. The experiment results showed the error of the pulse rate detection to be within ?3.44 to +4.53 bpm under sufficient ambient light and ?2.96 to + 4.24 bpm for night mode detection, when the moving speed is higher than 14.45 cm/s. These results demonstrate that the proposed method can improve the robustness of image-based contactless pulse rate detection despite subject movement and a dark environment.
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机译：主体移动和黑暗环境将增加基于图像的非接触式脉搏频率检测的难度。在本文中，我们基于肤色跟踪检测了对象的运动状态，并提出了一种运动指数（MI）来过滤运动伪影，以提高脉搏率测量的准确性。此外，我们将近红外（NIR）LED与采用的传感器集成在一起，并提出了一种有效的方法来测量在黑暗环境中的脉搏率。为了实现实时数据处理，在现场可编程门阵列（FPGA）平台上构建了所提出的框架。接下来，即时脉冲频率和运动状态被传输到智能手机以进行远程监控。实验结果表明，当移动速度高于14.45 cm / s时，在足够的环境光下，脉搏频率检测的误差在±3.44至+4.53 bpm之内，对于夜间模式检测，其误差在2.94至+ 4.24 bpm之内。这些结果表明，尽管对象运动和黑暗环境下，所提出的方法仍可以提高基于图像的非接触式脉搏率检测的鲁棒性。
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