Human Arm Motion Tracking by Inertial/Magnetic Sensors Using Unscented Kalman Filter and Relative Motion Constraint

@article{Atrsaei2018HumanAM,
  title={Human Arm Motion Tracking by Inertial/Magnetic Sensors Using Unscented Kalman Filter and Relative Motion Constraint},
  author={Arash Atrsaei and Hassan Salarieh and Aria Alasty and Mohammad Abediny},
  journal={Journal of Intelligent \& Robotic Systems},
  year={2018},
  volume={90},
  pages={161-170}
}
Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation… 
Multi-Inertial Sensor-Based Arm 3D Motion Tracking Using Elman Neural Network
Recent years have witnessed the rapid development of microelectromechanical systems, and human motion tracking technology based on IMU (inertial measurement unit) has attracted much attention.
Towards Real-Time Partially Self-Calibrating Pedestrian Navigation With an Inertial Sensor Array
TLDR
The fusion algorithm is capable of real-time link geometry estimation, which allows for the imposition of biomechanical constraints without a priori knowledge regarding sensor placements, and estimates gyroscope and accelerometer bias, scaling, and non-orthogonality parameters in real- time.
Magnetic Condition-Independent 3D Joint Angle Estimation Using Inertial Sensors and Kinematic Constraints
TLDR
This study proposes a magnetic condition-independent three-dimensional (3D) joint angle estimation method based on IMU signals that could be reliably applied in various fields that require robust 3D joint angles estimation through IM U signals in an unspecified arbitrary magnetic environment.
Constraint-augmented Kalman Filter for Magnetometer-free 3D Joint Angle Determination
TLDR
The residual of the constraint is investigated to provide an insight into how well each approach satisfies the kinematic constraint, and in magnetically undesirable conditions, the proposed IMU-based approach produced higher accuracy than the IMMU-based approaches.
A Simplified Extended Kalman Filter Used for Magnetic and Inertial Measurement Units
As a sensor unit, a magnetic and inertial measurement unit (MIMU) is mainly composed of a tri-axis gyroscope, a tri-axis accelerometer and a tri-axis magnetometer. The Extended Kalman Filter (EKF) is
Robust Inertial Measurement Unit-Based Attitude Determination Kalman Filter for Kinematically Constrained Links
TLDR
A novel constraint-augmented Kalman filter (KF) that eliminates the acceleration-induced uncertainty for a robust IMU-based attitude determination when IMU is attached to a constrained link is presented.
Research on vehicle attitude and heading reference system based on multi-sensor information fusion
TLDR
This study addresses the problems of non-orthogonal error, carrier magnetic field interference and calibration to obtain accurate, long-term, stable magnetic field strength.
A Wearable IMU System for Flexible Teleoperation of a Collaborative Industrial Robot
TLDR
A novel wireless wearable system that uses only inertial measurement units (IMUs) to determine the orientation of the operator’s upper body parts and is robust enough for use in industrial collaborative robotic applications is presented.
Wearable IMMU-Based Relative Position Estimation between Body Segments via Time-Varying Segment-to-Joint Vectors
In biomechanics, estimating the relative position between two body segments using inertial and magnetic measurement units (IMMUs) is important in that it enables the capture of human motion in
...
...

References

SHOWING 1-10 OF 22 REFERENCES
Design, Implementation, and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking
TLDR
Experimental results validate the filter design, show the feasibility of using inertial/magnetic sensor modules for real-time human body motion tracking, and validate the quaternion-based Kalman filter design.
Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors
This paper presents a viable quaternion-based complementary observer (CO) that is designed for rigid body attitude estimation. We claim that this approach is an alternative one to overcome the
Adaptive Kalman filter for orientation estimation in micro-sensor motion capture
TLDR
A quaternion-based adaptive Kalman filter for drift-free orientation estimation with least error compared with the existing methods, and the use of motion acceleration compensation together with the adaptive mechanism can improve the accuracy of human motion capture.
Inertial and magnetic posture tracking for inserting humans into networked virtual environments
TLDR
A quaternion-based complementary filter algorithm for processing the output data from a nine-axis MARG (Magnetic field, Angular Rate, and Gravity) sensor unit containing three orthogonally mounted angular rate sensors, three Orthogonal linear accelerometers and three orthogsonal magnetometers is described.
Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing
  • A. Sabatini
  • Engineering
    IEEE Transactions on Biomedical Engineering
  • 2006
TLDR
Improvements in the accuracy of orientation estimates are demonstrated for the proposed quaternion based extended Kalman filter, as compared with filter implementations where either the in-line calibration procedure, the adaptive mechanism for weighting the measurements of the aiding system sensors, or both are not implemented.
An improved quaternion-based Kalman filter for real-time tracking of rigid body orientation
TLDR
The use of the Gauss-Newton method, particularly the reduced-order implementation introduced in the paper, significantly simplifies the Kalman filter design, and reduces computational requirements.
Hierarchical information fusion for human upper limb motion capture
TLDR
A novel motion estimation algorithm by hierarchical fusion of sensor data and constraints of human dynamic model for human upper limb motion capture is presented, which represents orientations of upper limb segments in quaternion, which is computationally effective and able to avoid singularity problem.
IMU-Based Joint Angle Measurement for Gait Analysis
TLDR
A set of new methods for joint angle calculation based on inertial measurement data in the context of human motion analysis are presented, including methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field.
Whole-body imitation of human motions with a Nao humanoid
TLDR
A system that enables a humanoid robot to imitate complex whole-body motions of humans in real time with a focus on ensuring static stability when the motions are executed which is a challenging task, depending on the complexity of the movements.
...
...