Photoplethysmography derivatives and pulse transit time in overnight blood pressure monitoring

Abstract

Overnight continuous blood pressure measurement provides simultaneous monitoring of blood pressure and sleep architecture. By this means, we are able to investigate whether different sleep events are associated to blood pressure fluctuations. In this paper, we used the Pulse Transit Time (PTT) to develop and evaluate functions for measurement of blood pressure. We focused on the first and second derivatives of fingertip Photoplethysmography (PPG) recordings to detect PPG critical points. By applying R wave of ECG and PPG critical points, we created two PTT-based models for estimation of systolic and diastolic blood pressure (SBP and DBP). Seven subjects polysomnography datasets that contained PPG, ECG and blood pressure recordings were utilised to validate and compare developed PTT-BP functions. Results found that if the peak of the first derivative of PPG (VPG) was considered as the pulse pressure arrival point, the resulted PTT (PTTV) would more accurately predict both SBP and DBP. The average R-squared coefficient for SBP and DBP were correspondingly 0.593 and 0.416. The obtained mean error for PTTV based functions in SBP was ±3.96 mmHg with standard deviation of 1.41 mmHg and in DBP was ±6.88 mmHg with standard deviation of 3.03 mmHg. We concluded PTT detected from VPG is a reliable and suitable maker for overnight continuous blood pressure monitoring.

Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension

“…M1 is the modality with the most data points and the strongest r. M1 is also the only category to include studies with sample sizes over 30, making the correlations stronger than those of studies with small sample sizes. Across most modalities, SBP estimations have consistently higher correlations with real SBP than DBP estimations do with real DBP [17,21,23,25,27,40,43,44,51,52,55,60,61,65,81,82]. Three studies from M2 [15], M1 [59], and M1 [67] showed the opposite trend and two studies from M1 [31] and M4 [20] reported the same r for both SBP and DBP.…”

“…In more recent years, we see a rising trend in the emergence of new combinations of various biosignals (Figure 4). Of the 73 included studies, 22 reported the correlation (r) between estimated and reference BP for both SBP and DBP [15,17,20,21,23,25,27,29,31,40,43,44,51,52,55,[59][60][61]65,67,81,82]. Further, 15 studies reported the measurement variance in estimated versus reference BP for both SBP and DBP through mean error and standard deviation [21,22,33,34,38,51,59,60,64,67,69,72,78,82,83].…”

Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms

“…Thus, using the acronym VPG (velocity of PPG) to describe the first derivative of the PPG waveform is a fitting name choice. Likewise, it is fitting to use the acronym APG (acceleration plethysmogram) to refer to the second derivative of the PPG signal, which provides the acceleration of blood flow in the fingers [ 7 ]. Note that the use of the acronym APG was recommended in [ 6 ].…”

Estimation of Quasi-Continuous Blood Pressure based on Harmonic Phase-Shifts in Signals using Non-Invasive Photoplethysmographic Measurements

“…The general relationship between BP and PTT was subject of a series of investigations. In [6,[14][15][16][17][18][19][20][21][22] different magnitudes for the computation of the PTT are based on the calculation of the time difference between the ECG R-peak and some reference within the PPG signal and are methodically described and validated by calculating a correlation to the IBP. In addition to the methodological aspects of the BP computation using the PTT, [23] also discusses the impact of influencing factors, like changes in individual arterial stiffness.…”