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; Chau-Chin Su; Chen-Yi Lee

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, Chau-Chin Su, Chen-Yi Lee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2013 Symposium on VLSI Circuits, VLSIC 2013 - Digest of Technical Papers
Chapter	20-3
Pages	C252-C253
Number of pages	2
State	Published - 12 Jun 2013
Event	2013 Symposium on VLSI Circuits, VLSIC 2013 - Kyoto, Japan Duration: 12 Jun 2013 → 14 Jun 2013

Publication series

Name	IEEE Symposium on VLSI Circuits, Digest of Technical Papers

Conference

Conference	2013 Symposium on VLSI Circuits, VLSIC 2013
Country/Territory	Japan
City	Kyoto
Period	12/06/13 → 14/06/13

Cite this

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-C., & Lee, C-Y. (2013). A 48.6-to-105.2μW machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring. In 2013 Symposium on VLSI Circuits, VLSIC 2013 - Digest of Technical Papers (pp. C252-C253). [6578683] (IEEE Symposium on VLSI Circuits, Digest of Technical Papers).

@inproceedings{7529bb34d4004ccf9183bda5ab1f44f3,

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

abstract = "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.",

author = "Hsu, {Shu Yu} and Yingchieh Ho and Chang, {Po Yao} and Hsu, {Pei Yu} and Yu, {Chien Ying} and Yuhwai Tseng and Yang, {Tze Zheng} and Ten-Fang Yang and Chen, {Ray Jade} and Chau-Chin Su and Chen-Yi Lee",

year = "2013",

month = jun,

day = "12",

language = "English",

isbn = "9784863483484",

series = "IEEE Symposium on VLSI Circuits, Digest of Technical Papers",

pages = "C252--C253",

booktitle = "2013 Symposium on VLSI Circuits, VLSIC 2013 - Digest of Technical Papers",

note = "2013 Symposium on VLSI Circuits, VLSIC 2013 ; Conference date: 12-06-2013 Through 14-06-2013",

}

Hsu, SY, Ho, Y, Chang, PY, Hsu, PY, Yu, CY, Tseng, Y, Yang, TZ, Yang, T-F, Chen, RJ, Su, C-C & Lee, C-Y 2013, A 48.6-to-105.2μW machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring. in 2013 Symposium on VLSI Circuits, VLSIC 2013 - Digest of Technical Papers., 6578683, IEEE Symposium on VLSI Circuits, Digest of Technical Papers, pp. C252-C253, 2013 Symposium on VLSI Circuits, VLSIC 2013, Kyoto, Japan, 12/06/13.

A 48.6-to-105.2μW machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring. / Hsu, Shu Yu; Ho, Yingchieh; Chang, Po Yao et al.
2013 Symposium on VLSI Circuits, VLSIC 2013 - Digest of Technical Papers. 2013. p. C252-C253 6578683 (IEEE Symposium on VLSI Circuits, Digest of Technical Papers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Yu, Chien Ying

AU - Tseng, Yuhwai

AU - Yang, Tze Zheng

AU - Yang, Ten-Fang

AU - Chen, Ray Jade

AU - Su, Chau-Chin

AU - Lee, Chen-Yi

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M3 - Conference contribution

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

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