Background 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 (SpO2) with a controlled experiment. To mitigate this, we present OptoBeat, an ultra–low-cost smartphone-based optical sensing system that captures SpO2 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 SpO2 within 1% of the ground truth in levels as low as 75%. Objective The objective of this work is to test the following hypotheses and implement an ultra–low-cost smartphone adapter to measure SpO2: 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 SpO2 can be measured with a smartphone camera using the screen as a light source (hypothesis 3). Methods 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 SpO2 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. Results 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: F2,5997=3.1170 × 105, P<.01; alternating current: F2,5997=8.07 × 106, P<.01). Continuous SpO2 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 (R2=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), SpO2 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. Conclusions In this work, we demonstrate that skin tone has a significant effect on SpO2 measurements and the design and evaluation of OptoBeat. The ultra-low-cost OptoBeat system enables smartphones to classify skin tone for calibration, reliably measure SpO2 as low as 75%, and normalize to avoid skin tone–based bias.
BACKGROUND Many commodity pulse oximeters are insufficiently calibrated for patients of darker skin. We demonstrate a quantitative measurement of this disparity in SpO2 measurement with a controlled experimental set up using synthetic skin. To mitigate this, we present OptoBeat, an ultra-low-cost smartphone based optical sensing system that captures SpO2 and heart rate while calibrating for differences in skin tone. Our sensing system can be constructed from commodity plastics, fiber-optic cable and three clips that can be 3D printed for approximately $1, or cheaply manufactured at scale. In our experiments, we demonstrate the efficacy of the OptoBeat system, which can measure SpO2 levels within 1% accuracy of the ground truth (an FDA approved pulse oximeter) in SpO2 levels as low as 75%. OBJECTIVE The objective of this work is to test the following hypothesis and implement an ultra-low-cost smartphone adaptor to measure SpO2. • H1: Skin tone has a significant effect on pulse oximeter measurements. • H2: Pulse oximeter error based on skin tone can be corrected if skin tone is known. • H3: SpO2 can be measured with a smartphone camera using the screen as a light source. METHODS We used three tones of synthetic skin (Syndaver), with the same optical and chemical properties as human skin, to conduct all ex-vivo experiments. A skin tone scale was printed out and placed in the images captured by a mobile phone to calibrate and serve as a ground truth. To achieve a wide range of SpO2 measurements, we used sheep blood (Hardy Diagnostics) that was reoxygenated in a pressure chamber and pulsed through synthetic arteries with a peristaltic pump system. Custom optical clips coupled with fiberoptic cables focus the light from a smartphone screen through the analyte into the phone’s camera. SpO2 measurements are captured by pulsing the screen red and blue. RESULTS Skin tones were accurately classified as being type 2, 3, and 5 on the Fitzpatrick scale using the Euclidian distance of the captured RGB values. Traditional pulse oximeter measurements showed significant differences between skin tones in both AC and DC measurements. The standard deviations in the ratio of IR/red were 0.4184% for type 5, 0.2484% for type 3, and 0.2536% for type 2. Results show a significant difference between the three skin tones as shown in the results of an ANOVA test: 5997 Degrees of Freedom, F score of 3.1170e+05, and p < 0.001. Using our system, SpO2 measurements between 98-75% blood oxygen saturation were reliably captured in an ex-vivo experiment and are accurate to within 1% of ground the truth. In the human subject’s validation experiment, SpO2 measurements were accurate to within 0.5% of ground truth and pulse rate measurements were accurate within 2% of the ground truth. CONCLUSIONS Skin tone has a significant effect on SpO2 measurements using standard commodity hardware. This can be corrected by normalizing for variations in skin tone using an RGB image and reference scale. Leveraging existing smartphone hardware, we classify skin tone, measure SpO2, and normalize the measurements. To do this, we designed OptoBeat, an ultra-low-cost optical system
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.