A systematic review of machine learning and IoT applied to the prediction and monitoring of cardiovascular diseases
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 …
Feature-based information retrieval of multimodal biosignals with a self-similarity matrix: Focus on automatic segmentation
Biosignal-based technology has been increasingly available in our daily life, being a critical
information source. Wearable biosensors have been widely applied in, among others …
information source. Wearable biosensors have been widely applied in, among others …
Hybrid modeling on reconstitution of continuous arterial blood pressure using finger photoplethysmography
The continuous estimation of arterial blood pressure (ABP) waveforms directly from single-
channel photoplethysmography (PPG) signals will predictably change the way to monitor …
channel photoplethysmography (PPG) signals will predictably change the way to monitor …
[HTML][HTML] Application of Transfer Learning for Biomedical Signals: A Comprehensive Review of the Last Decade (2014-2024)
Precise and timely disease diagnosis is essential for making effective treatment decisions
and halting disease progression. Biomedical signals offer the potential for non-invasive …
and halting disease progression. Biomedical signals offer the potential for non-invasive …
STP: Self-supervised transfer learning based on transformer for noninvasive blood pressure estimation using photoplethysmography
Non-invasive blood pressure (BP) monitoring plays a crucial role in cardiovascular disease
prevention, but traditional cuff-based methods lack continuous monitoring capability …
prevention, but traditional cuff-based methods lack continuous monitoring capability …
BiGRU-attention for Continuous blood pressure trends estimation through single channel PPG
Background Physiological parameter monitoring based on photoplethysmography (PPG)
detection has the advantage of fast, portable, and non-invasive. Changes in the morphology …
detection has the advantage of fast, portable, and non-invasive. Changes in the morphology …
A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit
Intracranial pressure (ICP) is commonly monitored to guide treatment in patients with serious
brain disorders such as traumatic brain injury and stroke. Established methods to assess …
brain disorders such as traumatic brain injury and stroke. Established methods to assess …
DiffCNBP: Lightweight Diffusion Model for IoMT-Based Continuous Cuffless Blood Pressure Waveform Monitoring Using PPG
C Ma, L Guo, H Zhang, Z Liu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Continuous monitoring of blood pressure (BP) waveform is challenging in clinical
applications due to the invasive nature of traditional techniques. As a result, there is a …
applications due to the invasive nature of traditional techniques. As a result, there is a …
Design and validation of dual-point time-differentiated photoplethysmogram (2PPG) wearable for cuffless blood pressure estimation
Background & objectives Measurement of blood pressure (BP) in ambulatory patients is
crucial for at high-risk cardiovascular patients. A non-obtrusive, non-occluding device that …
crucial for at high-risk cardiovascular patients. A non-obtrusive, non-occluding device that …
[HTML][HTML] Comparison of seven shallow and deep regressors in continuous blood pressure and heart rate estimation using single-channel photoplethysmograms under …
Our objective is to compare seven blood pressure (BP) and heart rate (HR) estimation
models based on shallow and deep regressors using single-channel photoplethysmograms …
models based on shallow and deep regressors using single-channel photoplethysmograms …