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 …
Restoration of motion-corrupted EEG signals using attention-guided operational CycleGAN
Electroencephalogram (EEG) signals suffer substantially from motion artifacts even in
ambulatory settings. Signal processing techniques for removing motion artifacts from EEG …
ambulatory settings. Signal processing techniques for removing motion artifacts from EEG …
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
S Mahmud, MS Hossain, MEH Chowdhury… - Neural Computing and …, 2023 - Springer
Electroencephalogram (EEG) signals suffer substantially from motion artifacts when
recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many …
recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many …
[HTML][HTML] Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing …
Abstract Background and Motivations Physiological signals, such as the
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …
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 …
PPG2ABP: Translating photoplethysmogram (PPG) signals to arterial blood pressure (ABP) waveforms
Cardiovascular diseases are one of the most severe causes of mortality, annually taking a
heavy toll on lives worldwide. Continuous monitoring of blood pressure seems to be the …
heavy toll on lives worldwide. Continuous monitoring of blood pressure seems to be the …
M2ECG: Wearable mechanocardiograms to electrocardiogram estimation using deep learning
Chest surface vibrations induced by cardiac activities can provide valuable insights into
various heart conditions. Seismocardiogram (SCG) and Gyrocardiogram (GCG) signals …
various heart conditions. Seismocardiogram (SCG) and Gyrocardiogram (GCG) signals …
Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images
The human liver exhibits variable characteristics and anatomical information, which is often
ambiguous in radiological images. Machine learning can be of great assistance in …
ambiguous in radiological images. Machine learning can be of great assistance in …
Efficient multi-view fusion and flexible adaptation to view missing in cardiovascular system signals
The progression of deep learning and the widespread adoption of sensors have facilitated
automatic multi-view fusion (MVF) about the cardiovascular system (CVS) signals. However …
automatic multi-view fusion (MVF) about the cardiovascular system (CVS) signals. However …
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 …