Removal of motion artifacts in capacitive electrocardiogram acquisition: A review
Capacitive electrocardiogram (cECG) systems are increasingly used for the monitoring of
cardiac activity. They can operate within the presence of a small layer of air, hair or cloth and …
cardiac activity. They can operate within the presence of a small layer of air, hair or cloth and …
[HTML][HTML] Intracranial pressure monitoring signals after traumatic brain injury: a narrative overview and conceptual data science framework
Continuous intracranial pressure (ICP) monitoring is a cornerstone of neurocritical care after
severe brain injuries such as traumatic brain injury and acts as a biomarker of secondary …
severe brain injuries such as traumatic brain injury and acts as a biomarker of secondary …
Deep learning models for denoising ECG signals
Effective and powerful methods for denoising electrocardiogram (ECG) signals are important
for wearable sensors and devices. Deep Learning (DL) models have been used extensively …
for wearable sensors and devices. Deep Learning (DL) models have been used extensively …
R-peak detection based chaos analysis of ECG signal
Electrocardiography (ECG) is a non-invasive test that is used for recording contraction and
relaxation activities of the heart by using an electrocardiogram. Early detection of …
relaxation activities of the heart by using an electrocardiogram. Early detection of …
[HTML][HTML] Noise detection on ECG based on agglomerative clustering of morphological features
Biosignals are usually contaminated with artifacts from limb movements, muscular
contraction or electrical interference. Many algorithms of the literature, such as threshold …
contraction or electrical interference. Many algorithms of the literature, such as threshold …
Two-stage motion artefact reduction algorithm for electrocardiogram using weighted adaptive noise cancelling and recursive Hampel filter
The presence of motion artefacts in ECG signals can cause misleading interpretation of
cardiovascular status. Recently, reducing the motion artefact from ECG signal has gained …
cardiovascular status. Recently, reducing the motion artefact from ECG signal has gained …
Ventricular fibrillation and tachycardia detection using features derived from topological data analysis
A Mjahad, JV Frances-Villora, M Bataller-Mompean… - Applied Sciences, 2022 - mdpi.com
Featured Application Automated External Defibrillation (AED) and Implantable Cardioverter
Defibrillators (ICD) require accurate algorithms to detect arrhythmias and discriminate …
Defibrillators (ICD) require accurate algorithms to detect arrhythmias and discriminate …
Efficient extraction of deep image features using a convolutional neural network (CNN) for detecting ventricular fibrillation and tachycardia
To safely select the proper therapy for ventricular fibrillation (VF), it is essential to distinguish
it correctly from ventricular tachycardia (VT) and other rhythms. Provided that the required …
it correctly from ventricular tachycardia (VT) and other rhythms. Provided that the required …
[HTML][HTML] A PCA/ICA based fetal ECG extraction from mother abdominal recordings by means of a novel data-driven approach to fetal ECG quality assessment
AK Rahmati, SK Setarehdan… - Journal of biomedical …, 2017 - ncbi.nlm.nih.gov
Background: Fetal electrocardiography is a developing field that provides valuable
information on the fetal health during pregnancy. By early diagnosis and treatment of fetal …
information on the fetal health during pregnancy. By early diagnosis and treatment of fetal …
Optimized naive‐Bayes and decision tree approaches for fMRI smoking cessation classification
This paper aims at developing new theory‐driven biomarkers by implementing and
evaluating novel techniques from resting‐state scans that can be used in relapse prediction …
evaluating novel techniques from resting‐state scans that can be used in relapse prediction …