Data Augmentation to Address Various Rotation Errors of Wearable Sensors for Robust Pre-impact Fall Detection
Author:
Affiliation:
1. Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
Funder
Institute for Information & Communications Technology Promotion
National Research Foundation of Korea
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/10116032/09982375.pdf?arnumber=9982375
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1. Sensor Placement Variations in Wearable Activity Recognition
2. Limitations of data augmentation and outlook
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4. Unsupervised adaptation for acceleration-based activity recognition: robustness to sensor displacement and rotation
5. Augmenting wearable sensor data with physical constraint for DNN-based human-action recognition;ohashi;Proc ICML 2017 Times Ser Workshop,2017
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