Temporal feature-based classification into myocardial infarction and other cvds merging cnn and bi-lstm from ecg signal

M Dey, N Omar, MA Ullah - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Heart attack else wise termed as myocardial infarction (MI) causes irreparable death of
cardiac muscles yielding the focal reason for most casualties among all cardiovascular …

[PDF][PDF] Performance analysis of Savitzky-Golay smoothing filter using ECG signal

MA Awal, SS Mostafa, M Ahmad - International Journal of Computer …, 2011 - academia.edu
Cardiovascular diseases (CVDs) are the most widespread cause of death in many countries
all over the world. Electrocardiogram (ECG) is one of the most basic useful, easily available …

Exploiting similar prior knowledge for compressing ECG signals

F Nasimi, MR Khayyambashi, N Movahhedinia… - … Signal Processing and …, 2020 - Elsevier
Background and objectives Data compression techniques have been used in order to
reduce power consumption when transmitting electrocardiogram (ECG) signals in wireless …

Redundancy cancellation of compressed measurements by QRS complex alignment

F Nasimi, MR Khayyambashi, N Movahhedinia - Plos one, 2022 - journals.plos.org
The demand for long-term continuous care has led healthcare experts to focus on
development challenges. On-chip energy consumption as a key challenge can be …

A cost-effective multichannel wireless ECG acquisition system

MA Ahamed, M Ahmad - 2018 10th International Conference on …, 2018 - ieeexplore.ieee.org
Electrocardiography (ECG) is a non-invasive technique which records the electrical activity
generated by heart muscle depolarization's and it is widely used for diagnosis of heart …

Detection of myocardial infarction from ECG signal through combining CNN and Bi-LSTM

N Omar, M Dey, MA Ullah - 2020 11th international conference …, 2020 - ieeexplore.ieee.org
Myocardia infarction (MI) otherwise known as heart attack, is one of the prime causes of
death of individuals worldwide. The electrocardiogram (ECG) signal is clinically used by …

Knowledge Discovery with Electrocardiography Using Interpretable Deep Neural Networks

L Lu, T Zhu, A H. Ribeiro, L Clifton, E Zhao… - medRxiv, 2022 - medrxiv.org
Despite the potentials of artificial intelligence (AI) in healthcare, very little work focuses on
the extraction of clinical information or knowledge discovery from clinical measurements …

Mitigating Data Variability and Overfitting in Deep Learning Models for Atrial Fibrillation Detection Using Single-Lead ECGs

K Benchaira, S Bitam… - International Journal of …, 2024 - journal.uob.edu.bh
Despite the growing potential of deep learning in diagnosing Atrial Fibrillation (Afib),
challenges such as overfitting and limited generalizability continue to persist. These …

Machine learning approach for ECG analysis and predicting different heart diseases

SR Tithi, A Aktar, F Aleem - 2018 - dspace.bracu.ac.bd
In the modern world, there have been some revolutionary advancement in the field of
medical science and research and this is no different for electrocardiogram …

[PDF][PDF] Correlation of heart-rate and cardiac cycle duration under different body positions and breathing

SS Mostafa, MA Awal, MM Islam… - … Conference on Advances …, 2011 - academia.edu
Electrocardiogram (ECG) is one of the inexpensive, simple to perform, risk-free tools for the
early analysis of many cardiac abnormalities. The relation between mechanical event and …