An Approach to Magnetometer-free On-body Inertial Sensors Network Alignment

被引:1
|
作者
Lorenz, Michael [1 ]
Taetz, Bertram [1 ]
Bleser, Gabriele [1 ]
机构
[1] Tech Univ Kaiserslautern, Kaiserslautern, Germany
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
基金
欧盟地平线“2020”;
关键词
Human body motion capture; inertial sensors; sensor network; sensor alignment; spatial synchronization; motion estimation; information and sensor fusion; parameter and state estimation;
D O I
10.1016/j.ifacol.2020.12.393
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To capture human motion with inertial sensors, they are attached as a network on different segments. Typically the measurements received from each sensor are fused to obtain its orientation. A challenging task is to align the orientation of each sensor w.r.t. to a single common coordinate frame. To fulfill this task typically the local magnetic field is measured to provide information about the heading direction. Since especially in indoor environments magnetic field disturbances can be present, this information is not a reliable source. To overcome this problem, we present a method that aligns an on-body inertial sensor network using gyroscopes and accelerometers only. The subject wearing the network had to fulfill a predefined procedure, consisting of standing still and walking straight. To extract the heading direction, we estimated the linear acceleration and angular velocity using a maximum-a-posteriori estimator. Performing a principal component analysis on the estimated states we computed two heading directions for each estimate. Instead of using them separately, we used a fusing approach that exploits symmetrical effects. We validated the approach on a lower body configuration using an optical motion capture system. The heading direction of sensors attached on a single leg could be aligned up to median maximal deviation of 2.6 degrees and on the complete lower body of 6.6 degrees. Especially deviations of the pelvis were higher, due to a lack of motion excitation. To be able to quantify the excitation needed, we proposed an indicator based on the ratio of the eigenvalues of the principal component analysis of the angular velocities. Copyright (C) 2020 The Authors.
引用
收藏
页码:15982 / 15989
页数:8
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    Powell, Harry C., Jr.
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    Brandt-Pearce, Maite
    [J]. SIXTH INTERNATIONAL WORKSHOP ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS, PROCEEDINGS, 2009, : 181 - 186
  • [2] Location Determination of On-body Inertial Sensors
    Madcor, Hisham
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    Gomaa, Walid
    [J]. PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (ICINCO), 2021, : 693 - 700
  • [3] Sparse Magnetometer-Free Real-Time Inertial Hand Motion Tracking
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    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS (MFI), 2020, : 94 - 100
  • [4] Magnetometer-free inertial motion tracking of arbitrary joints with range of motion constraints
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    [J]. IFAC PAPERSONLINE, 2020, 53 (02): : 16016 - 16022
  • [5] RNN-based Observability Analysis for Magnetometer-Free Sparse Inertial Motion Tracking
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    Weber, Daniel
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    [J]. 2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022), 2022,
  • [6] Dynamic Magnetometer Calibration and Alignment to Inertial Sensors by Kalman Filtering
    Wu, Yuanxin
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    Yu, Wenxian
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2018, 26 (02) : 716 - 723
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    [J]. IFAC PAPERSONLINE, 2020, 53 (02): : 16023 - 16030
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    [J]. 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 1233 - 1238