Automatic identification of hypertension and assessment of its secondary effects using artificial intelligence: A systematic review (2013–2023)
Artificial intelligence (AI) techniques are increasingly used in computer-aided diagnostic
tools in medicine. These techniques can also help to identify hypertension (HTN) in its early …
tools in medicine. These techniques can also help to identify hypertension (HTN) in its early …
Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction …
S Liu, Z Huang, J Zhu, B Liu, P Zhou - Biomedical Signal Processing and …, 2024 - Elsevier
Blood pressure (BP) is an important indicator of a person's cardiovascular status, but
accurate, continuous BP monitoring remains a challenge. To improve the monitoring …
accurate, continuous BP monitoring remains a challenge. To improve the monitoring …
[HTML][HTML] Tiny-PPG: A lightweight deep neural network for real-time detection of motion artifacts in photoplethysmogram signals on edge devices
Y Zheng, C Wu, P Cai, Z Zhong, H Huang, Y Jiang - Internet of Things, 2024 - Elsevier
Photoplethysmogram (PPG) signals are easily contaminated by motion artifacts in real-world
settings, despite their widespread use in Internet-of-Things (IoT) based wearable and smart …
settings, despite their widespread use in Internet-of-Things (IoT) based wearable and smart …
An improved deep regression model with state space reconstruction for continuous blood pressure estimation
L Lyu, L Lu, H Chen, DA Clifton, Y Zhang… - Computers and …, 2024 - Elsevier
Continuous blood pressure (BP) monitoring is crucial for diagnosing and preventing
cardiovascular disease (CVD). However, existing approaches for continuous cuffless BP …
cardiovascular disease (CVD). However, existing approaches for continuous cuffless BP …
Cuffless blood pressure estimation from photoplethysmography using deep convolutional neural network and transfer learning
HM Koparır, Ö Arslan - Biomedical Signal Processing and Control, 2024 - Elsevier
Blood pressure (BP) monitoring is an essential indicator for diseases of the cardiovascular
system. Early detection of abnormalities in BP helps to significantly reduce the risk of …
system. Early detection of abnormalities in BP helps to significantly reduce the risk of …
Prediction of arterial blood pressure waveforms based on Multi-Task learning
G Ma, L Zheng, W Zhu, X Xing, L Wang, Y Yu - … Signal Processing and …, 2024 - Elsevier
Background Continuous and regular blood pressure (BP) monitoring has great significance
for the prevention and treatment of cardiovascular diseases. Arterial blood pressure (ABP) …
for the prevention and treatment of cardiovascular diseases. Arterial blood pressure (ABP) …
A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip …
K Lai, X Wang, C Cao - Sensors, 2024 - mdpi.com
Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health
assessments, with the precise forecasting of continuous blood pressure assuming a critical …
assessments, with the precise forecasting of continuous blood pressure assuming a critical …
Real-time tracking of radial artery vessel wall using a Kalman filter-based ultrasound single-plane wave RF signal time-frequency information fusion algorithm
L Liu, X Geng, F Yao, Z Guo, C Zhang, Y Zhang… - … Signal Processing and …, 2024 - Elsevier
Objective The goal of our study was to achieve real-time dynamic tracking of the radial artery
vessel wall in everyday life, which is crucial for blood pressure estimation and …
vessel wall in everyday life, which is crucial for blood pressure estimation and …
SleepBP-Net: A time-distributed convolutional network for nocturnal blood pressure estimation from photoplethysmogram
Nocturnal blood pressure (BP) monitoring offers valuable insights into various aspects of
human wellbeing, particularly cardiovascular health. Despite recent advancements in …
human wellbeing, particularly cardiovascular health. Despite recent advancements in …
Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications
Goal: To establish Pulse2AI as a reproducible data preprocessing framework for pulsatile
signals that generate high-quality machine-learning-ready datasets from raw wearable …
signals that generate high-quality machine-learning-ready datasets from raw wearable …