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

symposium on vlsi circuits(2013)

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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.
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关键词
cmos,machine learning,learning artificial intelligence,cardiology,cmos integrated circuits,system on chip,computer architecture,health care,feature extraction,mobile device
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