Quantification of Error Sources with Inertial Measurement Units in Sports

Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimiz...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-12, Vol.22 (24), p.9765
Main Authors: Kamstra, Haye, Wilmes, Erik, van der Helm, Frans C T
Format: Article
Language:English
Subjects:
Accelerometers
Biomechanical Phenomena
Calibration
Cameras
Data processing
Error analysis
error quantification
Error reduction
football
Humans
inertial measurement unit
Inertial platforms
Kinematics
Magnetic fields
Motion
Movement
Optoelectronics
orientation filter
Research Design
Sensors
Skin
soft tissue artefact
Soft tissues
Sports
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Summary:Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to present a method to quantify each of the sources of error of an IMU separately. An optoelectronic system was used as a gold standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different football-specific movements, varying both in the type of movement, and in movement intensity. The error of the definition of the body frames (11.3-18.7 deg RMSD), the STA (3.8-9.1 deg RMSD) and the error of the orientation filter (3.0-12.7 deg RMSD) were all quantified separately for each body segment. The error sources of IMU-based motion analysis were quantified separately. This allows future studies to quantify and optimize the effects of error reduction techniques.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22249765