Ambulatory human motion tracking by fusion of inertial and magnetic sensing with adaptive actuation

Over the last years, inertial sensing has proven to be a suitable ambulatory alternative to traditional human motion tracking based on optical position measurement systems, which are generally restricted to a laboratory environment. Besides many advantages, a major drawback is the inherent drift cau...

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Bibliographic Details
Published in:Medical & biological engineering & computing 2010-01, Vol.48 (1), p.27-37, Article 27
Main Authors: Schepers, H. Martin, Roetenberg, Daniel, Veltink, Peter H
Format: Article
Language:English
Subjects:
Accelerometers
Algorithms
Approximation
Biomechanical Phenomena
Biomechanics
Biomedical and Life Sciences
Biomedical engineering
Biomedical Engineering and Bioengineering
Biomedicine
Computer Applications
Energy consumption
Human Physiology
Humans
Imaging
Magnetics
Mathematical analysis
Medical research
Models, Biological
Monitoring, Ambulatory - instrumentation
Monitoring, Ambulatory - methods
Movement - physiology
Orientation
Original
Original Article
Radiology
Sensors
Studies
Time & motion studies
Velocity
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Summary:Over the last years, inertial sensing has proven to be a suitable ambulatory alternative to traditional human motion tracking based on optical position measurement systems, which are generally restricted to a laboratory environment. Besides many advantages, a major drawback is the inherent drift caused by integration of acceleration and angular velocity to obtain position and orientation. In addition, inertial sensing cannot be used to estimate relative positions and orientations of sensors with respect to each other. In order to overcome these drawbacks, this study presents an Extended Kalman Filter for fusion of inertial and magnetic sensing that is used to estimate relative positions and orientations. In between magnetic updates, change of position and orientation are estimated using inertial sensors. The system decides to perform a magnetic update only if the estimated uncertainty associated with the relative position and orientation exceeds a predefined threshold. The filter is able to provide a stable and accurate estimation of relative position and orientation for several types of movements, as indicated by the average rms error being 0.033 m for the position and 3.6 degrees for the orientation.
ISSN:0140-0118
1741-0444
DOI:10.1007/s11517-009-0562-9