A wearable tele-health system towards monitoring COVID-19 and chronic diseases
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic
since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than …
since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than …
A practical guide to non-invasive foetal electrocardiogram extraction and analysis
Non-Invasive foetal electrocardiography (NI-FECG) represents an alternative foetal
monitoring technique to traditional Doppler ultrasound approaches, that is non-invasive and …
monitoring technique to traditional Doppler ultrasound approaches, that is non-invasive and …
A deep learning approach for ECG-based heartbeat classification for arrhythmia detection
Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
Automatic sleep stage classification using time–frequency images of CWT and transfer learning using convolution neural network
P Jadhav, G Rajguru, D Datta… - Biocybernetics and …, 2020 - Elsevier
For automatic sleep stage classification, the existing methods mostly rely on hand-crafted
features selected from polysomnographic records. In this paper, the goal is to develop a …
features selected from polysomnographic records. In this paper, the goal is to develop a …
Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG
The diagnosis of cardiovascular diseases such as atrial fibrillation (AF) is a lengthy and
expensive procedure that often requires visual inspection of ECG signals by experts. In …
expensive procedure that often requires visual inspection of ECG signals by experts. In …
Cardiac arrhythmia detection from 2d ecg images by using deep learning technique
Arrhythmia is irregular changes of normal heart rhythm and effective manual identifying of
them require a lot of time and depends on experience of clinicians. This paper proposes …
them require a lot of time and depends on experience of clinicians. This paper proposes …
An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms
Over the past decades, many studies have been published on the extraction of non-invasive
foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions …
foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions …
The PhysioNet/computing in cardiology challenge 2015: reducing false arrhythmia alarms in the ICU
High false alarm rates in the ICU decrease quality of care by slowing staff response times
while increasing patient delirium through noise pollution. The 2015 Physio-Net/Computing …
while increasing patient delirium through noise pollution. The 2015 Physio-Net/Computing …
An enhanced electrocardiogram biometric authentication system using machine learning
Traditional authentication systems use alphanumeric or graphical passwords, or token-
based techniques that require “something you know and something you have”. The …
based techniques that require “something you know and something you have”. The …
A non-invasive continuous blood pressure estimation approach based on machine learning
S Chen, Z Ji, H Wu, Y Xu - Sensors, 2019 - mdpi.com
Considering the existing issues of traditional blood pressure (BP) measurement methods
and non-invasive continuous BP measurement techniques, this study aims to establish the …
and non-invasive continuous BP measurement techniques, this study aims to establish the …