iPhone 4s Photoplethysmography: Which Light Color Yields the Most Accurate Heart Rate and Normalized Pulse Volume Using the iPhysioMeter Application in the Presence of Motion Artifact?

Recent progress in information and communication technologies has made it possible to measure heart rate (HR) and normalized pulse volume (NPV), which are important physiological indices, using only a smartphone. This has been achieved with reflection mode photoplethysmography (PPG), by using a smartphone’s embedded flash as a light source and the camera as a light sensor. Despite its widespread use, the method of PPG is susceptible to motion artifacts as physical displacements influence photon propagation phenomena and, thereby, the effective optical path length. Further, it is known that the wavelength of light used for PPG influences the photon penetration depth and we therefore hypothesized that influences of motion artifact could be wavelength-dependant. To test this hypothesis, we made measurements in 12 healthy volunteers of HR and NPV derived from reflection mode plethysmograms recorded simultaneously at three different spectral regions (red, green and blue) at the same physical location with a smartphone. We then assessed the accuracy of the HR and NPV measurements under the influence of motion artifacts. The analyses revealed that the accuracy of HR was acceptably high with all three wavelengths (all rs > 0.996, fixed biases: −0.12 to 0.10 beats per minute, proportional biases: r = −0.29 to 0.03), but that of NPV was the best with green light (r = 0.791, fixed biases: −0.01 arbitrary units, proportional bias: r = 0.11). Moreover, the signal-to-noise ratio obtained with green and blue light PPG was higher than that of red light PPG. These findings suggest that green is the most suitable color for measuring HR and NPV from the reflection mode photoplethysmogram under motion artifact conditions. We conclude that the use of green light PPG could be of particular benefit in ambulatory monitoring where motion artifacts are a significant issue.

近年来，信息与通信技术的发展进步使得仅依托智能手机即可采集心率（heart rate, HR）与归一化脉搏容积（normalized pulse volume, NPV）这两类关键生理指标。该方案基于反射式光电容积描记法（reflection mode photoplethysmography, PPG）实现：利用智能手机内置闪光灯作为光源，以机身摄像头作为光传感器。尽管该方法应用广泛，但光电容积描记法极易受运动伪影（motion artifacts）干扰——物理位移会扰动光子传播过程，进而改变有效光程。此外，已有研究证实，光电容积描记法所用光波的波长会影响光子穿透深度，据此我们提出假设：运动伪影的影响程度可能与波长存在相关性。为验证该假设，我们招募12名健康志愿者，借助智能手机在同一物理位置，同步采集红、绿、蓝三个不同光谱波段下的反射式容积描记信号，从中提取心率与归一化脉搏容积，并在运动伪影干扰环境下评估二者的测量准确性。分析结果表明，三种波长下的心率测量准确性均处于可接受的较高水平（所有相关系数rs > 0.996，固定偏倚范围为-0.12~0.10次/分钟，比例偏倚范围为r=-0.29~0.03）；而归一化脉搏容积的测量准确性则以绿光波段最优（相关系数r=0.791，固定偏倚为-0.01任意单位，比例偏倚r=0.11）。此外，采用绿光与蓝光光电容积描记法获得的信噪比，显著高于红光光电容积描记法的信噪比。上述研究结果提示，在运动伪影干扰条件下，绿光波段是反射式光电容积描记法测量心率与归一化脉搏容积的最优选择。综上，在运动伪影问题较为突出的动态监测场景中，采用绿光光电容积描记法将具备显著的应用价值。