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Updated: Oct 2, 2025

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Published on: February 8, 2019
Zanru Yang1, Le Chung Tran1, Farzad Safaei1
1School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia.
This study estimates human step length using wireless channel properties and received signal strength indicator (RSSI). A novel filtering technique based on on-ankle path loss histograms achieves highly accurate step length estimation.
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