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Review
. 2023 Aug 19;23(16):7277.
doi: 10.3390/s23167277.

Integrated UWB/MIMU Sensor System for Position Estimation towards an Accurate Analysis of Human Movement: A Technical Review

Vinish Yogesh  1   2 , Jaap H Buurke  1   2 , Peter H Veltink  2 , Chris T M Baten  1
Affiliations
Review

Integrated UWB/MIMU Sensor System for Position Estimation towards an Accurate Analysis of Human Movement: A Technical Review

Vinish Yogesh et al. Sensors (Basel). .

Abstract

Integrated Ultra-wideband (UWB) and Magnetic Inertial Measurement Unit (MIMU) sensor systems have been gaining popularity for pedestrian tracking and indoor localization applications, mainly due to their complementary error characteristics that can be exploited to achieve higher accuracies via a data fusion approach. These integrated sensor systems have the potential for improving the ambulatory 3D analysis of human movement (estimating 3D kinematics of body segments and joints) over systems using only on-body MIMUs. For this, high accuracy is required in the estimation of the relative positions of all on-body integrated UWB/MIMU sensor modules. So far, these integrated UWB/MIMU sensors have not been reported to have been applied for full-body ambulatory 3D analysis of human movement. Also, no review articles have been found that have analyzed and summarized the methods integrating UWB and MIMU sensors for on-body applications. Therefore, a comprehensive analysis of this technology is essential to identify its potential for application in 3D analysis of human movement. This article thus aims to provide such a comprehensive analysis through a structured technical review of the methods integrating UWB and MIMU sensors for accurate position estimation in the context of the application for 3D analysis of human movement. The methods used for integration are all summarized along with the accuracies that are reported in the reviewed articles. In addition, the gaps that are required to be addressed for making this system applicable for the 3D analysis of human movement are discussed.

Keywords: data fusion; human movement analysis; integrated UWB/MIMU; position accuracy; position estimation.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Review process flow diagram and inclusion results.
Figure 2
Figure 2
Number of relevant publications found per year.
Figure 3
Figure 3
Star UWB sensor system configuration.
Figure 4
Figure 4
Schematic of the MIMU position estimation algorithms applied; Integration method (top) and traditional Pedestrian Dead Reckoning (PDR) algorithm (bottom).
Figure 5
Figure 5
UWB sensor placement (left) and MIMU sensor placement (right) locations on the human subject in the reviewed articles along with the number of corresponding articles for each location.
Figure 6
Figure 6
Distribution of data fusion methods for position estimation.
See this image and copyright information in PMC

References

    1. Filippeschi A., Schmitz N., Miezal M., Bleser G., Ruffaldi E., Stricker D. Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion. Sensors. 2017;17:1257. doi: 10.3390/s17061257. - DOI - PMC - PubMed
    1. Sabatini A.M. Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing. Sensors. 2011;11:1489–1525. doi: 10.3390/s110201489. - DOI - PMC - PubMed
    1. Rekant J., Rothenberger S., Chambers A. Inertial Measurement Unit-Based Motion Capture to Replace Camera-Based Systems for Assessing Gait in Healthy Young Adults: Proceed with Caution. Meas. Sens. 2022;23:100396. doi: 10.1016/j.measen.2022.100396. - DOI - PMC - PubMed
    1. Roetenberg D., Luinge H.J., Baten C.T., Veltink P.H. Compensation of Magnetic Disturbances Improves Inertial and Magnetic Sensing of Human Body Segment Orientation. IEEE Trans. Neural Syst. Rehabil. Eng. 2005;13:395–405. doi: 10.1109/TNSRE.2005.847353. - DOI - PubMed
    1. Vitali R.V., McGinnis R.S., Perkins N.C. Robust Error-State Kalman Filter for Estimating IMU Orientation. IEEE Sens. J. 2021;21:3561–3569. doi: 10.1109/JSEN.2020.3026895. - DOI

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