Using Artificial Intelligence (AI) for Monitoring and Diagnosing Electric Motor Faults Based on Vibration Signals
VN Pham, QH Do Ba, DAT Le… - 2024 International …, 2024 - ieeexplore.ieee.org
Detecting bearing faults in electric motors is highly crucial for improving production efficiency
and reducing accidents in complex mechanical systems, which poses significant challenges …
and reducing accidents in complex mechanical systems, which poses significant challenges …
Enhancing ECG signal classification through pre-trained stacked-CNN embeddings: a transfer learning approach
K Benchaira, S Bitam - Biomedical Physics & Engineering …, 2024 - iopscience.iop.org
Rapid and accurate electrocardiogram (ECG) signal classification is crucial in high-stakes
healthcare settings. However, existing computational models often struggle to balance high …
healthcare settings. However, existing computational models often struggle to balance high …
A novel method for automatic detection of arrhythmias using the unsupervised convolutional neural network
J Zhang, R Yao, J Gao, G Li, H Wu - Journal of Artificial Intelligence and …, 2023 - sciendo.com
In recent years, various models based on convolutional neural networks (CNN) have been
proposed to solve the cardiac arrhythmia detection problem and achieved saturated …
proposed to solve the cardiac arrhythmia detection problem and achieved saturated …
Patient Remote Monitoring System Using MQTT Protocol for ECG Signals
DAT Le, BT Vo, VN Pham, QH Do Ba… - … Circuits, Design, and …, 2024 - ieeexplore.ieee.org
The healthcare sector is increasingly benefiting from the integration of the Internet of Things
(IoT), particularly in the real-time monitoring of patients' health conditions. One notable …
(IoT), particularly in the real-time monitoring of patients' health conditions. One notable …