[HTML][HTML] A review of machine learning in hypertension detection and blood pressure estimation based on clinical and physiological data

E Martinez-Ríos, L Montesinos, M Alfaro-Ponce… - … Signal Processing and …, 2021 - Elsevier
The use of machine learning techniques in medicine has increased in recent years due to a
rise in publicly available datasets. These techniques have been applied in high blood …

The current state of optical sensors in medical wearables

E Vavrinsky, NE Esfahani, M Hausner, A Kuzma… - Biosensors, 2022 - mdpi.com
Optical sensors play an increasingly important role in the development of medical diagnostic
devices. They can be very widely used to measure the physiology of the human body …

Water quality classification using machine learning algorithms

N Nasir, A Kansal, O Alshaltone, F Barneih… - Journal of Water …, 2022 - Elsevier
Monitoring water quality is essential for protecting human health and the environment and
controlling water quality. Artificial Intelligence (AI) offers significant opportunities to help …

Thin, soft, wearable system for continuous wireless monitoring of artery blood pressure

J Li, H Jia, J Zhou, X Huang, L Xu, S Jia, Z Gao… - Nature …, 2023 - nature.com
Continuous monitoring of arterial blood pressure (BP) outside of a clinical setting is crucial
for preventing and diagnosing hypertension related diseases. However, current continuous …

Wearable photoplethysmography for cardiovascular monitoring

PH Charlton, PA Kyriacou, J Mant… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Smart wearables provide an opportunity to monitor health in daily life and are emerging as
potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands …

[HTML][HTML] Estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques

MH Chowdhury, MNI Shuzan, MEH Chowdhury… - Sensors, 2020 - mdpi.com
Hypertension is a potentially unsafe health ailment, which can be indicated directly from the
blood pressure (BP). Hypertension always leads to other health complications. Continuous …

Assessment of non-invasive blood pressure prediction from ppg and rppg signals using deep learning

F Schrumpf, P Frenzel, C Aust, G Osterhoff, M Fuchs - Sensors, 2021 - mdpi.com
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP)
measurement is interesting for various reasons. First, PPG can easily be measured using …

[HTML][HTML] A new machine learning method for predicting systolic and diastolic blood pressure using clinical characteristics

A Shrivastava, M Chakkaravarthy, MA Shah - Healthcare Analytics, 2023 - Elsevier
Hypertension describes elevated blood pressure, which significantly impacts cardiovascular
diseases. Typically, a sphygmomanometer, a cuff-like device, is used to measure a patient's …

An estimation method of continuous non-invasive arterial blood pressure waveform using photoplethysmography: A U-Net architecture-based approach

T Athaya, S Choi - Sensors, 2021 - mdpi.com
Blood pressure (BP) monitoring has significant importance in the treatment of hypertension
and different cardiovascular health diseases. As photoplethysmogram (PPG) signals can be …

Real-time cuffless continuous blood pressure estimation using deep learning model

YH Li, LN Harfiya, K Purwandari, YD Lin - Sensors, 2020 - mdpi.com
Blood pressure monitoring is one avenue to monitor people's health conditions. Early
detection of abnormal blood pressure can help patients to get early treatment and reduce …