4.0 Article

Automated Detection of Left Bundle Branch Block from ECG Signal Utilizing the Maximal Overlap Discrete Wavelet Transform with ANFIS

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Assessment of Dual-Tree Complex Wavelet Transform to Improve SNR in Collaboration with Neuro-Fuzzy System for Heart-Sound Identification

Bassam Al-Naami et al.

Summary: This research paper proposes a novel denoising method to improve heart-condition identification using heart-sound signals. The method combines the use of DTCWT and ANFIS classifier, resulting in improved signal-to-noise ratio and successful classification of heart-sound recordings.

ELECTRONICS (2022)

Article Mathematical & Computational Biology

A Study on Arrhythmia via ECG Signal Classification Using the Convolutional Neural Network

Mengze Wu et al.

Summary: This paper proposes a robust and efficient 12-layer deep one-dimensional convolutional neural network for classifying the five micro-classes of heartbeat types in the MIT-BIH Arrhythmia database. By using wavelet self-adaptive threshold denoising method in experiments, the five types of heartbeat features were accurately classified. Compared with BP neural network, random forest, and other CNN networks, the results show that the model proposed in this paper has better performance in accuracy, sensitivity, robustness, and anti-noise capability, effectively saving medical resources and having a positive impact on clinical practice.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2021)

Article Computer Science, Information Systems

A Novel Approach for Heart Ventricular and Atrial Abnormalities Detection via an Ensemble Classification Algorithm Based on ECG Morphological Features

Hui Yang et al.

Summary: In this study, a novel ensemble classification algorithm based on ECG morphological features is proposed for accurate detection of heart ventricular and atrial abnormalities. The method achieved an overall accuracy of 98.68% on fifteen heartbeat types and outperformed component classification algorithms and recent peer works.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

AMSOM: artificial metaplasticity in SOM neural networks-application to MIT-BIH arrhythmias database

Santiago Torres-Alegre et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Computer Science, Artificial Intelligence

An intelligent learning approach for improving ECG signal classification and arrhythmia analysis

Arun Kumar Sangaiah et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)

Article Engineering, Electrical & Electronic

LSTM-Based Auto-Encoder Model for ECG Arrhythmias Classification

Borui Hou et al.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)

Article Clinical Neurology

Kurtosis and skewness of high-frequency brain signals are altered in paediatric epilepsy

Jing Xiang et al.

BRAIN COMMUNICATIONS (2020)

Article Computer Science, Artificial Intelligence

A novel ICA-based clustering algorithm for heart arrhythmia diagnosis

E. Naseri et al.

PATTERN ANALYSIS AND APPLICATIONS (2019)

Article Multidisciplinary Sciences

Automatic diagnosis of strict left bundle branch block using a wavelet-based approach

Alba Martin-Yebraid et al.

PLOS ONE (2019)

Article Health Care Sciences & Services

An Efficient Cardiac Arrhythmia Onset Detection Technique Using a Novel Feature Rank Score Algorithm

Hemalatha Karnan et al.

JOURNAL OF MEDICAL SYSTEMS (2019)

Article Computer Science, Theory & Methods

A novel electrocardiogram feature extraction approach for cardiac arrhythmia classification

Leandro B. Marinho et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2019)

Article Engineering, Biomedical

Developing of robust and high accurate ECG beat classification by combining Gaussian mixtures and wavelets features

Ali Mohammad Alqudah et al.

AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE (2019)

Proceedings Paper Engineering, Biomedical

A Novel Detection Method of Bundle Branch Block from Multi-lead ECG

Jing Hu et al.

2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) (2019)

Proceedings Paper Engineering, Multidisciplinary

Arrhythmia Detection - A Machine Learning based Comparative Analysis with MIT-BIH ECG Data

Vishavpreet Singh et al.

2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT) (2019)

Article Health Care Sciences & Services

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm

Qin Qin et al.

JOURNAL OF HEALTHCARE ENGINEERING (2017)

Article Computer Science, Artificial Intelligence

Cardiac arrhythmia classification using statistical and mixture modeling features of ECG signals

Rashid Ghorbani Afkhami et al.

PATTERN RECOGNITION LETTERS (2016)

Article Biology

Heartbeat classification using disease-specific feature selection

Zhancheng Zhang et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2014)

Article Computer Science, Artificial Intelligence

An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks

Suranai Poungponsri et al.

NEUROCOMPUTING (2013)

Article Engineering, Electrical & Electronic

A new method for classification of ECG arrhythmias using neural network with adaptive activation function

Yueksel Ozbay et al.

DIGITAL SIGNAL PROCESSING (2010)

Article Computer Science, Artificial Intelligence

ECG beat classification using particle swarm optimization and radial basis function neural network

Mehmet Koruerek et al.

EXPERT SYSTEMS WITH APPLICATIONS (2010)

Article Meteorology & Atmospheric Sciences

Maximal overlap wavelet statistical analysis with application to atmospheric turbulence

Charles R. Cornish et al.

BOUNDARY-LAYER METEOROLOGY (2006)

Article Computer Science, Artificial Intelligence

Application of independent component analysis in removing artefacts from the electrocardiogram

TG He et al.

NEURAL COMPUTING & APPLICATIONS (2006)

Article Computer Science, Artificial Intelligence

ECG beat classification using neuro-fuzzy network

M Engin

PATTERN RECOGNITION LETTERS (2004)

Article Computer Science, Interdisciplinary Applications

Automatic arrhythmia detection based on time and time-frequency analysis of heart rate variability

MG Tsipouras et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2004)

Article Engineering, Biomedical

The impact of the MIT-BIH arrhythmia database

GA Moody et al.

IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE (2001)