Temporal feature-based classification into myocardial infarction and other cvds merging cnn and bi-lstm from ecg signal
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 …
cardiac muscles yielding the focal reason for most casualties among all cardiovascular …
[PDF][PDF] Performance analysis of Savitzky-Golay smoothing filter using ECG signal
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 …
all over the world. Electrocardiogram (ECG) is one of the most basic useful, easily available …
Exploiting similar prior knowledge for compressing ECG signals
Background and objectives Data compression techniques have been used in order to
reduce power consumption when transmitting electrocardiogram (ECG) signals in wireless …
reduce power consumption when transmitting electrocardiogram (ECG) signals in wireless …
Redundancy cancellation of compressed measurements by QRS complex alignment
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 …
development challenges. On-chip energy consumption as a key challenge can be …
A cost-effective multichannel wireless ECG acquisition system
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 …
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
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 …
death of individuals worldwide. The electrocardiogram (ECG) signal is clinically used by …
Knowledge Discovery with Electrocardiography Using Interpretable Deep Neural Networks
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 …
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 …
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 …
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
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 …
early analysis of many cardiac abnormalities. The relation between mechanical event and …