High Accuracy Abnormal ECG Detection Chip Using a Simple Neural Network

被引:2
作者
Chang, Kai-Fen [1 ]
Chen, Yuan-Ho [2 ]
机构
[1] Chang Gung Univ, Dept Elect Engn, Taoyuan, Taiwan
[2] Chang Gung Mem Hosp, Dept Radiat Oncol, Taoyuan, Taiwan
来源
2022 19TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC) | 2022年
关键词
Very-large-scale integration (VLSI); Electrocardiogram (ECG); convolutional neural network (CNN);
D O I
10.1109/ISOCC56007.2022.10031526
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Arrhythmias can be a sign of heart disease. If the heart is abnormal, using a wearable to monitor the heart rate can help us seek immediate medical attention. This work uses a deep learning network to build a simple architecture with only 3 layers that can achieve 98.5% high accuracy. Of the 3 layers, only 2 have computational power, Dense and Softmax. Therefore, the use of multipliers is reduced, and the area can be reduced in hardware implementation. This work implemented the proposed chip using TSMC 90nm CMOS technology, realizing a chip with an operating frequency of 50MHz, an area of 0.654x0.651mm(2), and maximum power consumption of 0.64 mW.
引用
收藏
页码:177 / 178
页数:2
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