Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU

Hui Zhang; Zonghua Zhang; Nan Gao; Yanjun Xiao; Zhaozong Meng; Zhen Li

doi:10.3390/s20020344

Sensors (Jan 2020)

Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU

Hui Zhang,
Zonghua Zhang,
Nan Gao,
Yanjun Xiao,
Zhaozong Meng,
Zhen Li

Affiliations

Hui Zhang: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Zonghua Zhang: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Nan Gao: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Yanjun Xiao: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Zhaozong Meng: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Zhen Li: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

DOI: https://doi.org/10.3390/s20020344
Journal volume & issue: Vol. 20, no. 2
p. 344

Abstract

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Wearable indoor localization can now find applications in a wide spectrum of fields, including the care of children and the elderly, sports motion analysis, rehabilitation medicine, robotics navigation, etc. Conventional inertial measurement unit (IMU)-based position estimation and radio signal indoor localization methods based on WiFi, Bluetooth, ultra-wide band (UWB), and radio frequency identification (RFID) all have their limitations regarding cost, accuracy, or usability, and a combination of the techniques has been considered a promising way to improve the accuracy. This investigation aims to provide a cost-effective wearable sensing solution with data fusion algorithms for indoor localization and real-time motion analysis. The main contributions of this investigation are: (1) the design of a wireless, battery-powered, and light-weight wearable sensing device integrating a low-cost UWB module-DWM1000 and micro-electromechanical system (MEMS) IMU-MPU9250 for synchronized measurement; (2) the implementation of a Mahony complementary filter for noise cancellation and attitude calculation, and quaternions for frame rotation to obtain the continuous attitude for displacement estimation; (3) the development of a data fusion model integrating the IMU and UWB data to enhance the measurement accuracy using Kalman-filter-based time-domain iterative compensations; and (4) evaluation of the developed sensor module by comparing it with UWB- and IMU-only solutions. The test results demonstrate that the average error of the integrated module reached 7.58 cm for an arbitrary walking path, which outperformed the IMU- and UWB-only localization solutions. The module could recognize lateral roll rotations during normal walking, which could be potentially used for abnormal gait recognition.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

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