Over the past two decades, machine learning systems have been proliferating in the
healthcare industry domains, such as digital health, fitness tracking, patient monitoring, and …

Blood pressure (BP) estimation is one of the most popular and long-standing topics in health-
care monitoring area. The utilization of machine learning (ML) and deep learning (DL) for BP …

This paper presents an overview of the cuffless, continuous time, non-invasive blood
pressure measuring devices (cNIBP) based on photoplethysmography (PPG). The cNIBP …

In this work, we propose a feature exploration method for learning-based cuffless blood
pressure measurement. More specifically, to efficiently explore a large feature space from …

The objective is to develop a cuffless modelling approach to accurately estimate the blood
pressure (BP) waveform and extract important BP features, such as the systolic BP (SBP) …

Photoplethysmography (PPG) has become ubiquitous with the development of smart
watches and the mobile healthcare market. However, PPG is vulnerable to various types of …

Biomedical measurement systems (BMS) have provided new solutions for healthcare
monitoring and the diagnosis of various chronic diseases. With a growing demand for BMS …

Cardiovascular disease, like hypertension, is one of the top killers of human life and early
detection of cardiovascular disease is of great importance. However, traditional medical …

Background Blood pressure diseases have increasingly been identified as among the main
factors threatening human health. How to accurately and conveniently measure blood …

Hypertension is a very significant public health problem and has become a potential risk for
cardiovascular and renal diseases. Blood pressure (BP) including systolic BP (SBP) and …