Automated Arrhythmia Classification System: Proof-of-Concept With Lightweight Model on an Ultra-Edge Device
Arrhythmia can lead to severe complications and early detection of arrhythmia is crucial to prevent progression. Electrocardiograms are the most reliable measure for detecting arrhythmia. This study aims to implement a practical ultra-edge-computing system for automated arrhythmia classification, in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10704628/ |
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