Key result
Including heart rate and photoplethysmogram TDB alongside pulse arrival time in multiple regression analysis maintained valid non-intrusive blood pressure estimation (r ≈ 0.8).
Why the study?
Does incorporating heart rate and TDB as confounding factors improve the accuracy of blood pressure estimation using pulse arrival time?
Does incorporating heart rate and TDB as confounding factors improve the accuracy of blood pressure estimation using pulse arrival time?
Incorporating heart rate and arterial stiffness markers into pulse arrival time-based blood pressure estimation maintains validity with a correlation of approximately 0.8.
Advances non-invasive BP estimation; extends PAT models but leaves open prospective validation before clinical use.
Two confounding factors were selected and analyzed in blood pressure estimation using pulse arrival time (PAT) for each individual. The heart rate was used as the confounding factor for the cardiac cycle, and the duration from the maximum derivative point to the dicrotic peak (TDB) in the photoplethysmogram was used as another confounding factor representing arterial stiffness. By considering these factors with PAT in multiple regression analysis, the performance of blood pressure estimation is enhanced significantly in the diastolic phase as well as in the systolic phase. The reproducibility of this method was also validated with formerly obtained regression equations from the training set. The correlation between estimated and measured blood pressure decreased a little, but the validity was still maintained (r congruent with 0.8). This shows the value of the method in non-intrusive blood pressure estimation for individual patients and may be useful for various applications.
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Kim et al. (2008) studied Blood pressure estimation. Pulse arrival time combined with heart rate and TDB (arterial stiffness) was evaluated on Correlation between estimated and measured blood pressure (r ≈ 0.8). Including heart rate and photoplethysmogram TDB alongside pulse arrival time in multiple regression analysis maintained valid non-intrusive blood pressure estimation (r ≈ 0.8).
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