PPG-Based Systolic Blood Pressure Estimation Method Using PLS and Level-Crossing Feature

Daisuke Fujita,Kazuteru Ryu,Arata Suzuki

doi:10.3390/app9020304

Abstract

This paper proposes a cuff-less systolic blood pressure (SBP) estimation method using partial least-squares (PLS) regression. Level-crossing features (LCFs) were used in this method, which were extracted from the contour lines arbitrarily drawn on the second-derivative photoplethysmography waveform. Unlike conventional height ratio features (HRFs), which are extracted on the basis of the peaks in the waveform, LCFs can be reliably extracted even if there are missing peaks in the waveform. However, the features extracted from adjacent contour lines show similar trends; thus, there is a strong correlation between the features, which leads to multicollinearity when conventional multiple regression analysis (MRA) is used. Hence, we developed a multivariate estimation method based on PLS regression to address this issue and estimate the SBP on the basis of the LCFs. Two-hundred-and-sixty-five subjects (95 males and 170 females [(Mean ± Standard Deviation) SBP: 133.1 ± 18.4 mmHg; age: 62.8 ± 16.8 years] participated in the experiments. Of the total number of subjects, 180 were considered as learning data, while 85 were considered as testing data. The values of the correlation coefficient between the measured and estimated values were found to be 0.78 for the proposed method (LCFs + PLS), 0.58 for comparison method 1 (HRFs + MRA), and 0.62 for comparison method 2 (HRFs + MRA). The proposed method was therefore found to demonstrate the highest accuracy among the three methods being compared.

Highlights

Hypertension is known as a risk factor of serious diseases such as stroke, myocardial infarction, and chronic kidney diseases [1]
In order to reliably obtain features from the second derivative of the photoplethysmography (SDPPG) waveform, we propose the use of level-crossing features (LCFs) extracted from the SDPPG waveforms, and we apply these features in Partial least-squares (PLS) regression to estimate the systolic blood pressure (SBP)
The explanatory ability of the blood pressure (BP) estimation model in comparison method 1 is weak owing to the small number of height ratio feature (HRF) (4), which we believe leads to the low estimation accuracy

Summary

Introduction

Hypertension is known as a risk factor of serious diseases such as stroke, myocardial infarction, and chronic kidney diseases [1]. A cuff-based BP measurement method is inconvenient because the measurement requires compression of the artery by the cuff. Cuffless BP estimation has recently attracted attention [2,3,4]. There has been considerable effort to develop cuffless BP estimation methods over the years, and one of them is based on the photoplethysmography (PPG). These BP estimation methods require two types of sensors to measure the ECG and PPG sensors, which increases the manufacturing costs of these devices. Studies have been carried out on developing cuffless BP estimation methods based only on PPG waveforms [5]

Methods

Results

Discussion

Conclusion