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Context Awareness and Step Length Estimation by Shape Distance and H-Features
Author
Kim, Daehyun; Lee, Yonghyeon; Park, Chan Gook
Journal Title
International Journal of Control, Automation, and Systems
Publication Year
2020
Topics
Summary
This paper proposes a new algorithm for behavior context awareness and step length estimation based on shape distance and H-features. The algorithm assumes the shape feature of the IMU signal represents the context, classifies contexts based on shape similarity after excluding H-features via Helmert transformation, and establishes a relationship between step length and H-features. Experimental results using a neural network demonstrate over 97% context classification accuracy and an RMSE of under 8.3% for step length estimation, outperforming conventional algorithms.
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