Novel blood pressure and pulse pressure estimation based on pulse transit time and stroke volume approximation

Abstract

BackgroundNon-invasive continuous blood pressure monitors are of great interest to the medical community due to their value in hypertension management. Recently, studies have shown the potential of pulse pressure as a therapeutic target for hypertension, but not enough attention has been given to non-invasive continuous monitoring of pulse pressure. Although accurate pulse pressure estimation can be of direct value to hypertension management and indirectly to the estimation of systolic blood pressure, as it is the sum of pulse pressure and diastolic blood pressure, only a few inadequate methods of pulse pressure estimation have been proposed.MethodsWe present a novel, non-invasive blood pressure and pulse pressure estimation method based on pulse transit time and pre-ejection period. Pre-ejection period and pulse transit time were measured non-invasively using electrocardiogram, seismocardiogram, and photoplethysmogram measured from the torso. The proposed method used the 2-element Windkessel model to model pulse pressure with the ratio of stroke volume, approximated by pre-ejection period, and arterial compliance, estimated by pulse transit time. Diastolic blood pressure was estimated using pulse transit time, and systolic blood pressure was estimated as the sum of the two estimates. The estimation method was verified in 11 subjects in two separate conditions with induced cardiovascular response and the results were compared against a reference measurement and values obtained from a previously proposed method.ResultsThe proposed method yielded high agreement with the reference (pulse pressure correlation with reference R ≥ 0.927, diastolic blood pressure correlation with reference R ≥ 0.854, systolic blood pressure correlation with reference R ≥ 0.914) and high estimation accuracy in pulse pressure (mean root-mean-squared error ≤ 3.46 mmHg) and blood pressure (mean root-mean-squared error ≤ 6.31 mmHg for diastolic blood pressure and ≤ 8.41 mmHg for systolic blood pressure) over a wide range of hemodynamic changes.ConclusionThe proposed pulse pressure estimation method provides accurate estimates in situations with and without significant changes in stroke volume. The proposed method improves upon the currently available systolic blood pressure estimation methods by providing accurate pulse pressure estimates.

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.…”

“…Of the 73 studies that reported correlation results, 22 met this criterion. Three studies [21][22][23] included in this analysis reported the coefficient of determination (r 2 ) instead of r. To include these studies, we used the square root (r) of this value. On a few occasions, studies did not report an overall mean error or r and instead reported multiple values of each population they tested.…”

“…On a few occasions, studies did not report an overall mean error or r and instead reported multiple values of each population they tested. These studies separately analyzed male and female groups [21], healthy participants and participants with heart disease [22], and participants whose BP was estimated during static exercise and those whose BP was estimated with a cold pressor test [23]. In the first two, to account for the multiple r values and include them in our results, we took the average between the two study populations to produce a combined r. In the third, we used static exercise data on the grounds that it was more applicable to the results of this review.…”

“…The use of devices with SCG, BCG, and ICG has not been widely validated or accepted, largely owing to their susceptibility to error caused by motion artifacts and device complexity with an extra sensor [33,61]. Interestingly, one of the highest correlations (0.92 and 0.85 for SBP and DBP, respectively) was reported by a study [23] that investigated a combination of PPG, ECG, and SCG during static exercise; however, this method has not yet been validated during ambulation or for individuals other than young healthy males. To reduce the number of required measurement devices, researchers have become increasingly creative in trying to eliminate the need for ECG and produce a more compact design.…”

“…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].…”