The electrocardiograph (ECG) and photoplethysmograph (PPG) are two methods of detecting heart rate (HR) and heart rate variability (HRV). A PPG sensor detects the pulse wave as it travels through the vascular tree. HRV estimates from pulse wave variability are termed pulse rate variability (PRV). Graphic © paulista/Shutterstock.com.
PRV may be a poor ECG surrogate for measuring HRV when participants stand, perform slow-paced breathing, or have low HRV (Jan et al., 2019). Moreover, BVP and ECG methods may yield different HRV values with marked sympathetic activation. ECG values will be more accurate since they are not affected by vasoconstriction.
Discount studies that report that PVR and HRV measurements are correlated if they don't report their measurement conditions (e.g., paced breathing) and limits of agreement (i.e., allowable error; Shaffer, Meehan, & Zerr, 2020).
Consumer biofeedback devices incorporating PPG sensors have become increasingly popular for recreation and self-regulation. Shown below are products by Elite HRV, HeartMath, myithlete, and Thought Technology Ltd.
Finally, there is increasing evidence that pulse oximeters overestimate oxygen saturation in Black and Hispanic patients because most were standardized using light-skinned individuals. Graphic © TomoTaro/Shutterstock.com.
Due to this racial bias, dark-skinned COVID-19 patients were 25% less likely to be flagged for treatment (Bajaj, 2022). This inaccuracy may have contributed to COVID-19 deaths due to missed low oxygen saturations (e.g., values below 85% reported as 92-95%; Tobin & Jubran, 2022). Graphic © Ground Picture/Shutterstock.com.
Summary
Correlations between ECG and PPG estimates of heart rate and heart rate variability must be qualified. PRV may be a poor ECG surrogate for measuring HRV when participants stand, perform slow-paced breathing, have low HRV, or experience vasoconstriction. Dark pigmentation in patients of color can cause pulse oximeters to underestimate blood oxygen saturation, possibly contributing to COVID-19 deaths.
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References Bajaj, S. (2022). Racial bias is built into the design of pulse oximeters. The Washington Post. Jan, H.-Y., Chen, M.-F., Fu, T.-C., Lin, W.-C., Tsai, C.-L., & Lin, K.-P. (2019). Evaluation of coherence between ECG and PPG derived parameters on heart rate variability and respiration in healthy volunteers with/without controlled breathing. Journal of Medical and Biological Engineering, 39, 783-795. https://doi.org/10.1007/s40846-019-00468-9
Shaffer, F., Meehan, Z. M., & Zerr, C. L. (2020). A critical review of ultra-short-term heart rate variability norms research. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2020.594880 Tobin, M. J., & Jubran, A. (2022). Pulse oximetry, racial bias and statistical bias. Annals of intensive care, 12(1), 2. https://doi.org/10.1186/s13613-021-00974-7