Adams Alexander T, Mandel Ilan, Gao Yixuan, Heckman Bryan W, Nandakumar Rajalakshmi, Choudhury Tanzeem
Information Science, Cornell Tech, New York, NY, United States.
The Center for the Study of Social Determinants of Health, Meharry Medical College, Nashville, TN, United States.
JMIR Biomed Eng. 2022 Apr 22;7(1):e34934. doi: 10.2196/34934.
Many commodity pulse oximeters are insufficiently calibrated for patients with darker skin. We demonstrate a quantitative measurement of this disparity in peripheral blood oxygen saturation (SpO) with a controlled experiment. To mitigate this, we present OptoBeat, an ultra-low-cost smartphone-based optical sensing system that captures SpO and heart rate while calibrating for differences in skin tone. Our sensing system can be constructed from commodity components and 3D-printed clips for approximately US $1. In our experiments, we demonstrate the efficacy of the OptoBeat system, which can measure SpO within 1% of the ground truth in levels as low as 75%.
The objective of this work is to test the following hypotheses and implement an ultra-low-cost smartphone adapter to measure SpO: skin tone has a significant effect on pulse oximeter measurements (hypothesis 1), images of skin tone can be used to calibrate pulse oximeter error (hypothesis 2), and SpO can be measured with a smartphone camera using the screen as a light source (hypothesis 3).
Synthetic skin with the same optical properties as human skin was used in ex vivo experiments. A skin tone scale was placed in images for calibration and ground truth. To achieve a wide range of SpO for measurement, we reoxygenated sheep blood and pumped it through synthetic arteries. A custom optical system was connected from the smartphone screen (flashing red and blue) to the analyte and into the phone's camera for measurement.
The 3 skin tones were accurately classified according to the Fitzpatrick scale as types 2, 3, and 5. Classification was performed using the Euclidean distance between the measured red, green, and blue values. Traditional pulse oximeter measurements (n=2000) showed significant differences between skin tones in both alternating current and direct current measurements using ANOVA (direct current: F=3.1170 × 10, P<.01; alternating current: F=8.07 × 10, P<.01). Continuous SpO measurements (n=400; 10-second samples, 67 minutes total) from 95% to 75% were captured using OptoBeat in an ex vivo experiment. The accuracy was measured to be within 1% of the ground truth via quadratic support vector machine regression and 10-fold cross-validation (R=0.97, root mean square error=0.7, mean square error=0.49, and mean absolute error=0.5). In the human-participant proof-of-concept experiment (N=3; samples=3 × N, duration=20-30 seconds per sample), SpO measurements were accurate to within 0.5% of the ground truth, and pulse rate measurements were accurate to within 1.7% of the ground truth.
In this work, we demonstrate that skin tone has a significant effect on SpO measurements and the design and evaluation of OptoBeat. The ultra-low-cost OptoBeat system enables smartphones to classify skin tone for calibration, reliably measure SpO as low as 75%, and normalize to avoid skin tone-based bias.
许多商用脉搏血氧仪对肤色较深的患者校准不足。我们通过一项对照实验对这种外周血氧饱和度(SpO)差异进行了定量测量。为缓解这一问题,我们推出了OptoBeat,这是一种基于智能手机的超低成本光学传感系统,可在校准肤色差异的同时获取SpO和心率。我们的传感系统可以用商用组件和3D打印夹子构建,成本约为1美元。在我们的实验中,我们展示了OptoBeat系统的有效性,该系统在低至75%的水平下测量SpO时,与真实值的误差在1%以内。
本研究的目的是检验以下假设,并实现一种用于测量SpO的超低成本智能手机适配器:肤色对脉搏血氧仪测量有显著影响(假设1),肤色图像可用于校准脉搏血氧仪误差(假设2),并且可以使用智能手机摄像头以屏幕作为光源测量SpO(假设3)。
在体外实验中使用了具有与人体皮肤相同光学特性的合成皮肤。在图像中放置肤色量表用于校准和获取真实值。为实现广泛的SpO测量范围,我们对羊血进行复氧并通过合成动脉泵送。一个定制的光学系统从智能手机屏幕(闪烁红色和蓝色)连接到分析物,再接入手机摄像头进行测量。
根据菲茨帕特里克量表,三种肤色被准确分类为2型、3型和5型。使用测量的红、绿、蓝值之间的欧几里得距离进行分类。传统脉搏血氧仪测量(n = 2000)显示,使用方差分析(ANOVA),在肤色的交流和直流测量中均存在显著差异(直流:F = 3.1170×10,P <.01;交流:F = 8.07×10,P <.01)。在体外实验中,使用OptoBeat从95%到75%进行了连续SpO测量(n = 400;10秒样本,共67分钟)。通过二次支持向量机回归和10折交叉验证,测量精度在真实值的1%以内(R = 0.97,均方根误差 = 0.7,均方误差 = 0.49,平均绝对误差 = 0.5)。在人体参与者概念验证实验(N = 3;样本 = 3×N,每个样本持续时间 = 20 - 30秒)中,SpO测量与真实值的误差在0.5%以内,脉搏率测量与真实值的误差在1.7%以内。
在本研究中,我们证明了肤色对SpO测量以及OptoBeat的设计和评估有显著影响。超低成本的OptoBeat系统使智能手机能够对肤色进行分类以进行校准,可靠地测量低至75%的SpO,并进行归一化以避免基于肤色的偏差。