Improving the Accuracy of Human Body Orientation Estimation With Wearable IMU Sensors

2017 ◽  
Vol 66 (3) ◽  
pp. 535-542 ◽  
Author(s):  
Hamad Ahmed ◽  
Muhammad Tahir
2021 ◽  
Author(s):  
Karam Abughalieh ◽  
Shadi Alawneh

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhi-An Deng ◽  
Zhiyu Qu ◽  
Changbo Hou ◽  
Weijian Si ◽  
Chunjie Zhang

Accuracy performance of WiFi fingerprinting positioning systems deteriorates severely when signal attenuations caused by human body are not considered. Previous studies have proposed WiFi fingerprinting positioning based on user orientation using compasses built in smartphones. However, compasses always cannot provide required accuracy of user orientation estimation due to the severe indoor magnetic perturbations. More importantly, we discover that not only user orientations but also smartphone carrying positions may affect signal attenuations caused by human body greatly. Therefore, we propose a novel WiFi fingerprinting positioning approach considering both user orientations and smartphone carrying positions. For user orientation estimation, we deploy Rotation Matrix and Principal Component Analysis (RMPCA) approach. For carrying position recognition, we propose a robust Random Forest classifier based on the developed orientation invariant features. Experimental results show that the proposed WiFi positioning approach may improve positioning accuracy significantly.


2010 ◽  
Vol 52 (4) ◽  
pp. 281-290
Author(s):  
AKI TSURUHARA ◽  
SO KANAZAWA ◽  
MASAMI K. YAMAGUCHI
Keyword(s):  

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