An atrial fibrillation detection system based on machine learning algorithm with mix-domain features and hardware acceleration *-Reference-Cited by-同舟云学术

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An atrial fibrillation detection system based on machine learning algorithm with mix-domain features and hardware acceleration *

Published:2021-11-01 Issue: Volume: Page:
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Container-title:2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Chen Chao,Ma Caiyun,Xing Yantao,Li Zinan,Gao Hongxiang,Zhang Xiangyu,Yang Chenxi,Liu Chengyu,Li Jianqin

Funder

Research and Development

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9629355/9629471/09629700.pdf?arnumber=9629700

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. BioWAP: A Reconfigurable Biomedical AI Processor with Adaptive Processing for Co-Optimized Accuracy and Energy Efficiency;2024 IEEE Custom Integrated Circuits Conference (CICC);2024-04-21

3. Dense neural network based arrhythmia classification on low-cost and low-compute micro-controller;Expert Systems with Applications;2024-04

4. AutoMLP: A Framework for the Acceleration of Multi-Layer Perceptron Models on FPGAs for Real-Time Atrial Fibrillation Disease Detection;IEEE Transactions on Biomedical Circuits and Systems;2023-12

5. A configurable hardware-efficient ECG classification inference engine based on CNN for mobile healthcare applications;Microelectronics Journal;2023-11

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