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DisPad: Flexible On-Body Displacement of Fabric Sensors for Robust Joint-Motion Tracking

Authors :
Chen, Xiaowei
Jiang, Xiao
Fang, Jiawei
Guo, Shihui
Lin, Juncong
Liao, Minghong
Luo, Guoliang
Fu, Hongbo
Publication Year :
2023

Abstract

The last few decades have witnessed an emerging trend of wearable soft sensors; however, there are important signal-processing challenges for soft sensors that still limit their practical deployment. They are error-prone when displaced, resulting in significant deviations from their ideal sensor output. In this work, we propose a novel prototype that integrates an elbow pad with a sparse network of soft sensors. Our prototype is fully bio-compatible, stretchable, and wearable. We develop a learning-based method to predict the elbow orientation angle and achieve an average tracking error of 9.82 degrees for single-user multi-motion experiments. With transfer learning, our method achieves the average tracking errors of 10.98 degrees and 11.81 degrees across different motion types and users, respectively. Our core contributions lie in a solution that realizes robust and stable human joint motion tracking across different device displacements.<br />Comment: 25 pages, 14 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2301.06249
Document Type :
Working Paper