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Published September 30, 2019 | Version v1
Conference paper Open

Towards an automatic parameter setting for MIMU sensor fusion algorithms

  • 1. Politecnico di Torino, Turin, Italy
  • 2. Scuola Superiore Sant'Anna, Pisa, Italy
  • 3. Università degli studi di Sassari, Sassari, Italy

Description

Magnetic and Inertial Measurement Units (MIMU) are widely used in human movement analysis. MIMU orientation can be determined by combining accelerometer, gyroscope, and magnetometer data in a sensor fusion framework. Any algorithm for orientation estimation requires to define a given number of input parameters. It has been shown that any algorithm performance greatly varies depending on the selection of the parameter values according to both hardware and motion characteristics [1]. It is common practice to choose parameters values as set by the authors in their original implementations or by following a trial and error approach [2]. Unfortunately, the latter solutions are time-demanding, require a good level of expertise and do not guarantee for generalization. The aim of this work was to propose a method for sub-optimal parameter values identification based on specific hardware characteristics, different angular rates and types of motion without requiring reference data. The method validity was assessed on a popular complementary filter [2] using data recorded from a motion capture optical system (SP) as reference.

This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.

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Additional details

Funding

MOBILISE-D – Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement 820820
European Commission

References

  • Bergamini, et al. Sensors 2014; 10: 18625 18649
  • Madgwick S. O. H. et al. 2011; ICORR, 2011.