Fidelitous Augmentation of Human Accelerometric Data for Deep Learning-Reference-Cited by-同舟云学术

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Fidelitous Augmentation of Human Accelerometric Data for Deep Learning

Published:2023-12-15 Issue: Volume: Page:194-195
ISSN:
Container-title:2023 IEEE International Conference on E-health Networking, Application & Services (Healthcom)
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Author:

Lee T.K.M.¹,Chan H.W.²,Leo K.H.³,Chew E.⁴,Zhao L.⁴,Sanei S.⁵

Affiliation:

1. School of Electrical & Electronic Engineering, Singapore Polytechnic, Singapore School of Information Technology Monash University,Malaysia

2. University of Glasgow,Dept of Aerospace Engineering,Singapore

3. Singhealth Office for Organizational Transformation,Singapore

4. National University Hospital,Division of Neurology,Singapore

5. School of Science & Technology, Nottingham Trent University,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10472302/10472335/10472398.pdf?arnumber=10472398

Reference8 articles.

1. A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

2. A Novel Model to Generate Heterogeneous and Realistic Time-Series Data for Post-Stroke Rehabilitation Assessment

3. Data Augmentation techniques in time series domain: a survey and taxonomy

4. An empirical survey of data augmentation for time series classification with neural networks

5. Improving Rehabilitative Assessment with Statistical and Shape Preserving Surrogate Data and Singular Spectrum Analysis

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