IEEE Rev Biomed Eng. 2016;9:91-105. doi: 10.1109/RBME.2016.2551778. Epub 2016 Apr 7.
Human pulse rate (PR) can be estimated in several ways, including measurement instruments that directly count the PR through contact- and noncontact-based approaches. Over the last decade, computer-vision-assisted noncontact-based PR estimation has evolved significantly. Such techniques can be adopted for clinical purposes to mitigate some of the limitations of contact-based techniques. However, existing vision-guided noncontact-based techniques have not been benchmarked with respect to a challenging dataset. In view of this, we present a systematic review of such techniques implemented over a uniform computing platform. We have simultaneously recorded the PR and video of 14 volunteers. Five sets of data have been recorded for every volunteer using five different experimental conditions by varying the distance from the camera and illumination condition. Pros and cons of the existing noncontact image- and video-based PR techniques have been discussed with respect to our dataset. Experimental evaluation suggests that image- or video-based PR estimation can be highly effective for nonclinical purposes, and some of these approaches are very promising toward developing clinical applications. The present review is the first in this field of contactless vision-guided PR estimation research.
人体脉搏率(PR)可以通过多种方式进行估计,包括通过接触和非接触式方法直接计数 PR 的测量仪器。在过去的十年中,计算机视觉辅助的非接触式 PR 估计技术得到了显著发展。这些技术可以应用于临床,以减轻接触式技术的一些局限性。然而,现有的基于视觉的非接触式技术尚未在具有挑战性的数据集上进行基准测试。有鉴于此,我们对在统一计算平台上实现的此类技术进行了系统回顾。我们同时记录了 14 名志愿者的脉搏率和视频。使用不同的实验条件(通过改变与相机的距离和照明条件),为每位志愿者记录了五组数据。针对我们的数据集,讨论了现有的基于非接触式图像和视频的 PR 技术的优缺点。实验评估表明,基于图像或视频的 PR 估计对于非临床目的非常有效,其中一些方法在开发临床应用方面非常有前途。本综述是接触式视觉引导 PR 估计研究领域的第一篇综述。