Limitations of Oximetry to Measure Heart Rate Variability Measures

Abstract

Measuring heart rate variability (HRV) is widely used to assess autonomic nervous system function. It requires accurate measurement of the interval between successive heartbeats. This can be achieved from recording the electrocardiogram (ECG), which is non-invasive and widely available. However, methodological problems inherent in recording and analyzing ECG traces have motivated a search for alternative means of measuring the interval between successive heartbeats. Recording blood oxygenation pulsations (photoplethysmography-PPG) is also convenient, non-invasive and widely available, and has been suggested as an effective alternative to ECG to derive HRV. Moreover, it has been claimed that the pulse waveforms produced by oximetry may be more practicable than R-R intervals measured from the by ECG, especially for ambulatory recordings. We have therefore compared PPG with ECG recordings to measure HRV applying the same signal analysis techniques to PPG and ECG recordings made simultaneously. Comparison of 5 min recording epochs demonstrated a very high degree of correlation, in temporal, frequency domains and non-linear analysis, between HRV measures derived from the PPG and ECG. However, we found that the PPG signal is especially vulnerable to motion artifacts when compared to the ECG, preventing any HRV analysis at all in a significant minority of PPG recordings. Our results demonstrate that even though PPG provides accurate interpulse intervals to measure heart rate variability under ideal conditions, it is less reliable due to its vulnerability to motion artifacts. Therefore it is unlikely to prove a practical alternative to the ECG in ambulatory recordings or recordings made during other activities.

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“…4 and Table 1). The lower correlation in response to respiratory and temperature changes may reflect the previously reported inaccuracy of PRV PPG under nonoptimal conditions, such as including motion artifacts, 6 physical strenuous exercise, 5 or mental stressors. 7 Although our subjects were instructed to keep the body as still as possible during the respiratory challenges, the breathing and temperature changes certainly induced minor body motions and mental stress, respectively, that may have contributed to the inaccuracy of PRV PPG .…”

“…Previous studies comparing PRV derived from PPG and ECG under optimal rest conditions did not report significant differences in PRV assessment. 6,45,46 However, studies that compared PPG and ECG under less optimal conditions have shown that PRV PPG assessed the parameters of short-term variability (HF, RMSSD, and SD1) considerable less reliable compared to ECG. 7,9 In line with these findings, our results showed that the cold temperature change (COLD) exhibited significant increases of the parameters reflecting short-term variability (i.e., HF activity, RMSSD, and SD1), whereas the parameters reflecting long-term variability did not change significantly compared to the control condition (CONTROL).…”

“…PRV PPG is convenient, noninvasive, and widely available and has, therefore, been suggested for simplifying ambulatory HRV monitoring. [5][6][7] Under resting conditions, recordings derived from PPG and ECG demonstrate a high degree of correlation (∼r > 0.93). 7,8 However, PRV PPG also has disadvantages.…”

“…7,8 However, PRV PPG also has disadvantages. While sufficient accuracy can be obtained when subjects are under optimal resting conditions, PRV PPG has been reported to be vulnerable to motion artifacts, 6 physical exercise, 5 or mental stressors, 7 making it considerably less accurate compared to ECG. The smaller accuracy may arise due to probe instability, sweating, artifacts during exercise, and the influence of different cardiovascular components.…”

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“…On the other hand, the pulse oximeter can also be used to diagnose heart diseases, but its analysis is not as extensive or as reliable as that of an ECG sensor. [2][3][4] The key algorithms for processing ECG signals include the Hamilton-Tompkins' algorithm 5 and the Genetic Algorithm. 6 The Hamilton-Tompkins' algorithm is a refined version of the Pan-Tompkins algorithm and was proposed in the late 1980s but has remained relevant today because its level of simplicity makes it useful for real-time ECG processing.…”