Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals

MR Prusty, TN Pandey, PS Lekha, G Lellapalli… - Scientific Reports, 2024 - nature.com
Heart diseases are leading to death across the globe. Exact detection and treatment for
heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one …

Adaptive neuro-fuzzy inference system for classification of ECG signals

TM Nazmy, H El-Messiry… - 2010 The 7th international …, 2010 - ieeexplore.ieee.org
This paper, presents an Intelligent diagnosis system using Hybrid approach of Adaptive
Neuro-Fuzzy Inference System (ANFIS) model for classification of Electrocardiogram (ECG) …

Proposal for a home sleep monitoring platform employing a smart glove

R Lazazzera, P Laguna, E Gil, G Carrault - Sensors, 2021 - mdpi.com
The present paper proposes the design of a sleep monitoring platform. It consists of an
entire sleep monitoring system based on a smart glove sensor called UpNEA worn during …

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 …

A curvelet-based lacunarity approach for ulcer detection from wireless capsule endoscopy images

A Eid, VS Charisis, LJ Hadjileontiadis… - Proceedings of the …, 2013 - ieeexplore.ieee.org
Wireless Capsule Endoscopy (WCE) is a fairly new technology that offers a low-risk, non
invasive visual inspection of the patient's digestive tract, especially the small bowel, that was …

Research on the physiological and psychological impacts of extraordinary nature on emotions and restorative effects for young adults

S Hao, L Zhang, R Hou, SSY Lau, SSY Lau - Journal of Environmental …, 2024 - Elsevier
Research indicates that exposure to natural environments positively impacts both
physiological and psychological well-being. However, extraordinary, awesome landscapes …

Arrhythmia detection by extracting hybrid features based on refined Fuzzy entropy (FuzEn) approach and employing machine learning techniques

L Hussain, W Aziz, S Saeed, IA Awan… - Waves in Random …, 2020 - Taylor & Francis
Cardiac arrhythmias are disturbances in the rhythm of the heart manifested by irregularity or
by abnormally fast rates ('tachycardia') or abnormally slow rates ('bradycardias'). In the past …

A framework for the atrial fibrillation prediction in electrophysiological studies

P Vizza, A Curcio, G Tradigo, C Indolfi… - Computer methods and …, 2015 - Elsevier
Background and objective Cardiac arrhythmias are disorders in terms of speed or rhythm in
the heart's electrical system. Atrial fibrillation (AFib) is the most common sustained …

Cardiac Arrhythmia Diagnosis with an Intelligent Algorithm using Chaos Features of Electrocardiogram Signal and Compound Classifier

E Zarei, N Barimani… - Journal of AI and Data …, 2022 - jad.shahroodut.ac.ir
Cardiac Arrhythmias are known as one of the most dangerous cardiac diseases. Applying
intelligent algorithms in this area, leads into the reduction of the ECG signal processing time …

QRS subtraction for atrial electrograms: flat, linear and spline interpolations

A Ahmad, JL Salinet, P Brown, JH Tuan… - Medical & biological …, 2011 - Springer
The main objective of this article is to implement and compare QRS subtraction techniques
for intra-cardiac atrial electrograms based on using the surface ECG as a reference. A band …