A 48.6-to-105.2μW machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring

Shu Yu Hsu, Yingchieh Ho, Po Yao Chang, Pei Yu Hsu, Chien Ying Yu, Yuhwai Tseng, Tze Zheng Yang, Ten Fang Yang, Ray Jade Chen, Chauchin Su, Chen Yi Lee

研究成果: 書貢獻/報告類型會議貢獻

13 引文 斯高帕斯(Scopus)

摘要

A machine-learning (ML) assisted cardiac sensor SoC (CS-SoC) is designed for healthcare monitoring with mobile devices. The architecture realizes the cardiac signal acquisition with versatile feature extractions and classifications, enabling higher order analysis over traditional DSPs. Besides, the dynamic standby controller further suppresses the leakage power dissipation. Implemented in 90nm CMOS, the CS-SoC dissipates 48.6/105.2μW at 0.5-1.0V for real-time arrhythmia/myocardial infarction syndrome detection with 95.8/99% accuracy.

原文英語
主出版物標題IEEE Symposium on VLSI Circuits, Digest of Technical Papers
出版狀態已發佈 - 2013
事件2013 Symposium on VLSI Circuits, VLSIC 2013 - Kyoto, 日本
持續時間: 六月 12 2013六月 14 2013

其他

其他2013 Symposium on VLSI Circuits, VLSIC 2013
國家日本
城市Kyoto
期間6/12/136/14/13

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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    Hsu, S. Y., Ho, Y., Chang, P. Y., Hsu, P. Y., Yu, C. Y., Tseng, Y., Yang, T. Z., Yang, T. F., Chen, R. J., Su, C., & Lee, C. Y. (2013). A 48.6-to-105.2μW machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring. 於 IEEE Symposium on VLSI Circuits, Digest of Technical Papers [6578683]