Next Article in Journal
Single Neural Adaptive PID Control for Small UAV Micro-Turbojet Engine
Next Article in Special Issue
Automatic Classification of Squat Posture Using Inertial Sensors: Deep Learning Approach
Previous Article in Journal
Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks
Previous Article in Special Issue
Hydrophobic Paper-Based SERS Sensor Using Gold Nanoparticles Arranged on Graphene Oxide Flakes
Article

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

1
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
2
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
3
Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities, Key Laboratory of Ministry of Industry and Information Technology, Nanjing 211100, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(2), 344; https://doi.org/10.3390/s20020344
Received: 18 November 2019 / Revised: 31 December 2019 / Accepted: 3 January 2020 / Published: 7 January 2020
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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. View Full-Text
Keywords: indoor localization; motion analysis; wearable sensing devices; inertial measurement unit (IMU); ultra-wide band (UWB) indoor localization; motion analysis; wearable sensing devices; inertial measurement unit (IMU); ultra-wide band (UWB)
Show Figures

Figure 1

MDPI and ACS Style

Zhang, H.; Zhang, Z.; Gao, N.; Xiao, Y.; Meng, Z.; Li, Z. Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU. Sensors 2020, 20, 344. https://doi.org/10.3390/s20020344

AMA Style

Zhang H, Zhang Z, Gao N, Xiao Y, Meng Z, Li Z. Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU. Sensors. 2020; 20(2):344. https://doi.org/10.3390/s20020344

Chicago/Turabian Style

Zhang, Hui, Zonghua Zhang, Nan Gao, Yanjun Xiao, Zhaozong Meng, and Zhen Li. 2020. "Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU" Sensors 20, no. 2: 344. https://doi.org/10.3390/s20020344

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop