Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …
Novel DERMA fusion technique for ECG heartbeat classification
An electrocardiogram (ECG) consists of five types of different waveforms or characteristics
(P, QRS, and T) that represent electrical activity within the heart. Identification of time …
(P, QRS, and T) that represent electrical activity within the heart. Identification of time …
Estimating leaf nitrogen content in corn based on information fusion of multiple-sensor imagery from UAV
With the rapid development of unmanned aerial vehicle (UAV) and sensor technology, UAVs
that can simultaneously carry different sensors have been increasingly used to monitor …
that can simultaneously carry different sensors have been increasingly used to monitor …
IoT based system for heart monitoring and arrhythmia detection using machine learning
RE Cañón-Clavijo… - Journal of …, 2023 - Wiley Online Library
Internet of Things (IoT) technologies allow building a digital representation of people,
objects, or physical phenomena to be available on the Internet. Thus, stakeholders can …
objects, or physical phenomena to be available on the Internet. Thus, stakeholders can …
Multi-features based arrhythmia diagnosis algorithm using xgboost
J Bao - 2020 International Conference on Computing and Data …, 2020 - ieeexplore.ieee.org
Arrhythmia is the common disease in today's society. In order to judge the specific situation
of the patient, doctors often observe the ECG (Electrocardiograph) signal to get enough …
of the patient, doctors often observe the ECG (Electrocardiograph) signal to get enough …
Classification of cardiac arrhythmia of 12 lead ecg using combination of smoteenn, xgboost and machine learning algorithms
BR Manju, AR Nair - 2019 9th International Symposium on …, 2019 - ieeexplore.ieee.org
Cardiac Arrhythmia is one of those common diseases leading to severe health problems for
patients and even sudden death in some cases. Early detection of arrhythmias has a great …
patients and even sudden death in some cases. Early detection of arrhythmias has a great …
Investigating feature selection and random forests for inter-patient heartbeat classification
JF Saenz-Cogollo, M Agelli - Algorithms, 2020 - mdpi.com
Finding an optimal combination of features and classifier is still an open problem in the
development of automatic heartbeat classification systems, especially when applications …
development of automatic heartbeat classification systems, especially when applications …
A fully automatic model for premature ventricular heartbeat arrhythmia classification using the internet of medical things
Cardiac arrhythmias are one of the leading causes of increased mortality worldwide and
place a heavy burden on the medical environment. Premature ventricular contraction is the …
place a heavy burden on the medical environment. Premature ventricular contraction is the …
Arrhythmia classification based on wavelet transformation and random forests
G Pan, Z Xin, S Shi, D Jin - Multimedia Tools and Applications, 2018 - Springer
Cardiovascular disease accompanied by arrhythmia reduces an individual's lifespan and
health, and long term ECG monitoring would generate large amounts of data. Fortunately …
health, and long term ECG monitoring would generate large amounts of data. Fortunately …
Morphological Arrhythmia Classification Based on Inter-patient and Two Leads ECG using Machine Learning
Arrhythmia is a heart disorder in which the heart beats irregularly. Electrocardiogram (ECG)
has been widely used as a tool for detecting arrhythmias. However, the interpretation of ECG …
has been widely used as a tool for detecting arrhythmias. However, the interpretation of ECG …