Sparse Magnetometer-free Inertial Motion Tracking - A Condition for Observability in Double Hinge Joint Systems
@article{Eckhoff2020SparseMI, title={Sparse Magnetometer-free Inertial Motion Tracking - A Condition for Observability in Double Hinge Joint Systems}, author={Karsten Eckhoff and Manon Kok and Sergio Lucia and Thomas Seel}, journal={ArXiv}, year={2020}, volume={abs/2002.00902} }
11 Citations
Observability of the relative motion from inertial data in kinematic chains
- MathematicsControl Engineering Practice
- 2022
Sparse Magnetometer-Free Real-Time Inertial Hand Motion Tracking
- Engineering2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
- 2020
A real-time capable, sparse motion tracking solution for hand motion tracking that requires only five IMUs, one on each of the distal finger segments and one on the back of the hand, in contrast to recently proposed full-setup solution with 16 IMUs is presented.
Estimating Lower Limb Kinematics Using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements †
- EngineeringSensors
- 2020
A novel Lie group constrained extended Kalman filter is presented to estimate lower limb kinematics using IMU and inter-IMU distance measurements in a reduced sensor count configuration and shows that performance improved substantially for dynamic movements, even at large noise levels.
RIANN—A Robust Neural Network Outperforms Attitude Estimation Filters
- Computer ScienceAI
- 2021
RIANN is proposed, a ready-to-use, neural network-based, parameter-free, real-time-capable inertial attitude estimator, which generalizes well across different motion dynamics, environments, and sampling rates, without the need for application-specific adaptations.
Robust Neural Networks Outperform Attitude Estimation Filters
- Computer ScienceArXiv
- 2021
This work proposes RIANN, a real-time-capable neural network for robust IMUbased attitude estimation, which generalizes well across different motion dynamics, environments, and sampling rates, without the need for application-specific adaptations.
Gait Analysis in a Box: A System Based on Magnetometer-Free IMUs or Clusters of Optical Markers with Automatic Event Detection
- PhysicsSensors
- 2020
This study presents a MoCap gait analysis system called Move Human Sensors (MH), which incorporates proposals to overcome both limitations and can be configured via magnetometer-free IMUs (MH-IMU) or clusters of optical markers ( MH-OPT).
Estimating Lower Limb Kinematics Using a Reduced Wearable Sensor Count
- EngineeringIEEE Transactions on Biomedical Engineering
- 2021
An algorithm for accurately estimating pelvis, thigh, and shank kinematics during walking using only three wearable inertial sensors using a constrained Kalman filter is presented.
Magnetometer Robust Deep Human Pose Regression With Uncertainty Prediction Using Sparse Body Worn Magnetic Inertial Measurement Units
- Computer ScienceIEEE Access
- 2021
A deep learning based framework that learns data-driven temporal priors to perform 3D human pose estimation from six body worn Magnetic Inertial Measurement units sensors and derives and implements a 3D angle representation that eliminates yaw angle and improves the accuracy.
Inertial Motion Capture-Based Wearable Systems for Estimation of Joint Kinetics: A Systematic Review
- BiologySensors
- 2022
The aim of this review is to explore the methodology of the current studies on estimating joint kinetic variables by means of an IMC system, and summarizes the content of the selected literature in terms of the study characteristics, methodologies, and study results.
Technology-Based Complex Motor Tasks Assessment: A 6-DOF Inertial-Based System Versus a Gold-Standard Optoelectronic-Based One
- EngineeringIEEE Sensors Journal
- 2021
A novel inertial-sensor based system (Movit System G1, by Captiks) with an innovative calibration is reported, testing its strengths and weaknesses when compared to an optoelectronic gold standard one.
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