Energy-Aware Design Methodology for Myocardial Infarction Detection on Low-Power Wearable Devices-Reference-Cited by-同舟云学术

Energy-Aware Design Methodology for Myocardial Infarction Detection on Low-Power Wearable Devices

Published:2021-01-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th Asia and South Pacific Design Automation Conference
language:
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Author:

Odema Mohanad¹,Rashid Nafiul¹,Al Faruque Mohammad Abdullah¹

Affiliation:

1. Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, California, USA

Funder

NSF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394885.3431513

Reference19 articles.

1. Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

2. R. Bousseljot D. Kreiseler and A. Schnabel. 1995. Use of the PTB's ECG signal database CARDIODAT via the Internet. 40(s1) (1995) 317--318. R. Bousseljot D. Kreiseler and A. Schnabel. 1995. Use of the PTB's ECG signal database CARDIODAT via the Internet. 40(s1) (1995) 317--318.

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