文章基本信息

标题：An Approach to Magnetometer-free On-body Inertial Sensors Network Alignment
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作者：Michael Lorenz ; Bertram Taetz ; Gabriele Bleser 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：15982-15989
DOI：10.1016/j.ifacol.2020.12.393
语种：English
出版社：Elsevier
摘要：AbstractTo 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.
关键词：KeywordsHuman body motion captureinertial sensorssensor networksensor alignmentspatial synchronizationmotion estimationinformationsensor fusionparameterstate estimation