Prediction of electrocardiography features points using seismocardiography data-Reference-Cited by-同舟云学术

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Prediction of electrocardiography features points using seismocardiography data

Published:2018-10-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 ACM International Symposium on Wearable Computers
language:
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Author:

Dürichen Robert¹,Verma Keshav Deep²,Yee Seow Yuen³,Rocznik Thomas³,Schmidt Philip¹,Bödecker Joschka⁴,Peters Christian³

Affiliation:

1. Robert Bosch GmbH, Corporate Research, Germany

2. Robert Bosch GmbH, Corporate Research, Germany & University of Freiburg, Machine Learning Lab, Germany

3. Robert Bosch LLC, Research and Technolgy Center, Sunnyvale, CA, USA

4. University of Freiburg, Machine Learning Lab, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3267242.3267283

Reference8 articles.

1. Mozziyar Etemadi et al. 2016. A wearable patch to enable long-term monitoring of environmental activity and hemodynamics variables. IEEE transactions on biomedical circuits and systems 10 2 (2016). Mozziyar Etemadi et al. 2016. A wearable patch to enable long-term monitoring of environmental activity and hemodynamics variables. IEEE transactions on biomedical circuits and systems 10 2 (2016).

2. Ballistocardiography and seismocardiography: A review of recent advances;Omer T;IEEE Journal of Biomedical and Health Informatics,2015

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5. Morphological Changes of Seismocardiogram Due to Different Sensor Placements on the Sternum;2020 Computing in Cardiology Conference (CinC);2020-12-30

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