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Jeong, Hongsik
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A 1.02-μW STT-MRAM-Based DNN ECG arrhythmia monitoring SoC with leakage-based delay MAC unit

Author(s)
Lee, Kyoung-RogKim, JihoonKim, ChanghyeonHan, DonghyeonLee, JuhyoungLee, JinsuJeong, HongsikYoo, Hoi-Jun
Issued Date
2020-10
DOI
10.1109/LSSC.2020.3024622
URI
https://scholarworks.unist.ac.kr/handle/201301/65351
Citation
IEEE SOLID-STATE CIRCUITS LETTERS, v.3, pp.390 - 393
Abstract
A low-power STT-MRAM-based mixed-mode electrocardiogram (ECG) arrhythmia monitoring SoC is proposed. The proposed SoC consists of 1-MB STT-MRAM, leakage-based delay multiply-and-accumulation (MAC) unit (LDMAC), and ECG analog front end (AFE). ResNet structure with 16 1-D convolution layers and max-pooling layers is adopted for the ECG arrhythmia detection with weight reusing and partial sum reusing scheme. A nonvolatile 1-MB STT-MRAM enables deep neural network (DNN) inference to achieve higher area efficiency, lower power consumption without external memory access. The proposed mixed-mode LDMAC consumes only 4.11-nW MAC power by reusing leakage current. The proposed SoC is fabricated in 28-nm FDSOI process with 7.29-mm2 area. It demonstrates ECG arrhythmia detection with 85.1% accuracy, which is the highest score reported, and the lowest power consumption of 1.02 μW. © 2018 IEEE.
Publisher
Institute of Electrical and Electronics Engineers Inc.
ISSN
2573-9603
Keyword (Author)
Biomedical deep neural network (DNN)DNN SoCelectrocardiogram arrhythmiamixed-mode multiply-and-accumulationSTT-MRAM

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