A Low-Power Intelligent ECG monitoring System for Wearable Devices
Author:
Affiliation:
1. University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10210847/10211258/10212004.pdf?arnumber=10212004
Reference15 articles.
1. An Energy-Efficient Cardiac Arrhythmia Classification Processor using Heartbeat Difference based Classification and Event-Driven Neural Network Computation with Adaptive Wake-Up
2. ULECGNet: An Ultra-Lightweight End-to-End ECG Classification Neural Network
3. 4.5 BioAIP: A Reconfigurable Biomedical AI Processor with Adaptive Learning for Versatile Intelligent Health Monitoring
4. A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors
5. Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction
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1. Performance Evaluation of Cardiac Signal Recording Framework (CARDIF)-A Quantitative Assessment for Long Term Monitoring Applications;Biomedical and Pharmacology Journal;2024-03-20
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