Computer-aided arrhythmia diagnosis with bio-signal processing: A survey of trends and techniques
SMP Dinakarrao, A Jantsch, M Shafique - ACM Computing Surveys …, 2019 - dl.acm.org
Signals obtained from a patient, ie, bio-signals, are utilized to analyze the health of patient.
One such bio-signal of paramount importance is the electrocardiogram (ECG), which …
One such bio-signal of paramount importance is the electrocardiogram (ECG), which …
Detection of sleep apnea using deep neural networks and single-lead ECG signals
Sleep apnea causes frequent cessation of breathing during sleep. Feature extraction
approaches play a key role in the performance of apnea detection algorithms that use single …
approaches play a key role in the performance of apnea detection algorithms that use single …
Issues in the automated classification of multilead ECGs using heterogeneous labels and populations
Objective. The standard twelve-lead electrocardiogram (ECG) is a widely used tool for
monitoring cardiac function and diagnosing cardiac disorders. The development of smaller …
monitoring cardiac function and diagnosing cardiac disorders. The development of smaller …
Artificial intelligence for cardiac diseases diagnosis and prediction using ECG images on embedded systems
L Mhamdi, O Dammak, F Cottin, IB Dhaou - Biomedicines, 2022 - mdpi.com
The electrocardiogram (ECG) provides essential information about various human cardiac
conditions. Several studies have investigated this topic in order to detect cardiac …
conditions. Several studies have investigated this topic in order to detect cardiac …
Automatic classification of apnea and normal subjects using new features extracted from HRV and ECG-derived respiration signals
A novel framework for automatic detection of obstructive sleep apnea (OSA) is introduced in
which a symbolic dynamics method, alphabet entropy, along with other well-known features …
which a symbolic dynamics method, alphabet entropy, along with other well-known features …
Automated detection of cardiac arrhythmia using deep learning techniques
Cardiac arrhythmia is a condition where heart beat is irregular. The goal of this paper is to
apply deep learning techniques in the diagnosis of cardiac arrhythmia using ECG signals …
apply deep learning techniques in the diagnosis of cardiac arrhythmia using ECG signals …
Performance evaluation of the spectral autocorrelation function and autoregressive models for automated sleep apnea detection using single-lead ECG signal
Background and objective: This paper addresses the automated recognition of obstructive
sleep apnea (OSA) from the analysis of single-lead ECG signals. This is one of the most …
sleep apnea (OSA) from the analysis of single-lead ECG signals. This is one of the most …
Adaptive neuro-fuzzy estimation of autonomic nervous system parameters effect on heart rate variability
D Petković, Ž Ćojbašić - Neural Computing and Applications, 2012 - Springer
Heart rate signal can be used as certain indicator of heart disease. Spectral analysis of heart
rate variability (HRV) signal makes it possible to partly separate the low-frequency (LF) …
rate variability (HRV) signal makes it possible to partly separate the low-frequency (LF) …
Survey on the methods for detecting arrhythmias using heart rate signals
S Celin, K Vasanth - Journal of Pharmaceutical Sciences and …, 2017 - search.proquest.com
The electrical activity of heart is symbolized with the help of ECG signal. This ECG signal is
characterized by different peaks P, QRS, T and U that occur periodically at a particular …
characterized by different peaks P, QRS, T and U that occur periodically at a particular …
Adaptive neuro fuzzy selection of heart rate variability parameters affected by autonomic nervous system
D Petković, Ž Ćojbašić, S Lukić - Expert Systems with Applications, 2013 - Elsevier
Heart rate variability (HRV) parameters can be used as specific indicator of autonomic
nervous system (ANS) behavior. ANS, with its main two branches, sympathetic and …
nervous system (ANS) behavior. ANS, with its main two branches, sympathetic and …