Identification of blood pressure reflecting personalized traits using bilateral photoplethysmography

Blood pressure (BP) is currently diagnosed by cuff-based devices, which are inconvenient and provide discontinuous measurements. Photoplethysmography (PPG)-based cuffless techniques have recently been used to accurately estimate both systolic BP (SBP) and diastolic BP (DBP). However, it is difficult to use these SBP and DBP estimations to reflect the personalized traits in the peripheral vascular condition; thus, their accuracy is limited.

The purpose of this study is to describe a technique that can be distinguished simply among three BP categories (normotensive, prehypertensive, and hypertensive) and reflect individual traits using PPG only.

We measured BP over 120 s using the fingers of 105 subjects. The PPG waveforms varied in size and amplitude over time. Therefore, normalization for uniform features for individual traits was done after the extracted waveforms were divided into multiple windows. The feature is determined by the lowest amplitude in the waveform within each divided window. The features have been applied to distinguish three BP categories using the first-eigenvector (1-EV) and second-eigenvector (2-EV) in linear discriminant analysis.

The best decision boundary for each BP category was estimated using 1-EV (-0.02 to +0.02) and 2-EV (>+0.02) in the hypertensive category, 1-EV (< 0) and 2-EV (⩽+0.02) in the prehypertensive category, and 1-EV (⩾-0.02) and 2-EV (⩽+0.02) in the normotensive category. The overlap range with 1-EV (-0.02 to 0) and 2-EV (⩽+0.02) in particular accurately reflected individual traits.

Discrimination among the three BP categories reflecting individual traits was successfully achieved using PPG. This method could improve limitations of cuff-based techniques.