A systematic review of machine learning and IoT applied to the prediction and monitoring of cardiovascular diseases
A Cuevas-Chavez, Y Hernandez, J Ortiz-Hernandez… - Healthcare, 2023 - mdpi.com
According to the Pan American Health Organization, cardiovascular disease is the leading
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
Self-Attention LSTM-FCN model for arrhythmia classification and uncertainty assessment
This paper presents ArrhyMon, a self-attention-based LSTM-FCN model for arrhythmia
classification from ECG signal inputs. ArrhyMon targets to detect and classify six different …
classification from ECG signal inputs. ArrhyMon targets to detect and classify six different …
Cuffless blood pressure measurement using smartwatches: a large-scale validation study
This study aimed to evaluate the performance of cuffless blood pressure (BP) measurement
techniques in a large and diverse cohort of participants. We enrolled 3077 participants …
techniques in a large and diverse cohort of participants. We enrolled 3077 participants …
A Review of Deep Learning Methods for Photoplethysmography Data
Photoplethysmography (PPG) is a highly promising device due to its advantages in
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …
Blood pressure estimation from photoplethysmography by considering intra-and inter-subject variabilities: guidelines for a fair assessment
Cardiovascular diseases are the leading causes of death, and blood pressure (BP)
monitoring is essential for prevention, diagnosis, assessment, and treatment …
monitoring is essential for prevention, diagnosis, assessment, and treatment …
HGCTNet: Handcrafted Feature-Guided CNN and Transformer Network for Wearable Cuffless Blood Pressure Measurement
Biosignals collected by wearable devices, such as electrocardiogram and
photoplethysmogram, exhibit redundancy and global temporal dependencies, posing a …
photoplethysmogram, exhibit redundancy and global temporal dependencies, posing a …
OVAR-BPnet: A General Pulse Wave Deep Learning Approach for Cuffless Blood Pressure Measurement
Y Cen, J Luo, H Wang, L Chen, X Zhu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Pulse wave analysis, a non-invasive and cuffless approach, holds promise for blood
pressure (BP) measurement in precision medicine. In recent years, pulse wave learning for …
pressure (BP) measurement in precision medicine. In recent years, pulse wave learning for …
Robust Feature Selection for BP Estimation in Multiple Populations: Towards Cuffless Ambulatory BP Monitoring
Current blood pressure (BP) estimation methods have not achieved an accurate and
adaptable approach for ambulatory diagnosis and monitoring applications of populations at …
adaptable approach for ambulatory diagnosis and monitoring applications of populations at …
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 …
Large Language Models for Cuffless Blood Pressure Measurement From Wearable Biosignals
Large language models (LLMs) have captured significant interest from both academia and
industry due to their impressive performance across various textual tasks. However, the …
industry due to their impressive performance across various textual tasks. However, the …