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Allumo: Preprocessing and Calibration Software for Wearable Accelerometers Used in Posture Tracking


Allumo: Preprocessing and Calibration Software for Wearable Accelerometers Used in Posture Tracking

Alexis Fortin-Côté et al. Sensors (Basel).


Inertial measurement units have recently shown great potential for the accurate measurement of joint angle movements in replacement of motion capture systems. In the race towards long duration tracking, inertial measurement units increasingly aim to ensure portability and long battery life, allowing improved ecological studies. Their main advantage over laboratory grade equipment is their usability in a wider range of environment for greater ecological value. For accurate and useful measurements, these types of sensors require a robust orientation estimation that remains accurate over long periods of time. To this end, we developed the Allumo software for the preprocessing and calibration of the orientation estimate of triaxial accelerometers. This software has an automatic orientation calibration procedure, an automatic erroneous orientation-estimate detection and useful visualization to help process long and short measurement periods. These automatic procedures are detailed in this paper, and two case studies are presented to showcase the usefulness of the software. The Allumo software is open-source and available online.

Keywords: accelerometer; calibration; human movement; inertial measurement units.

Conflict of interest statement

The authors declare no conflicts of interest.


Figure 1
Figure 1
Main interface of the software.
Figure 2
Figure 2
Geometric representation of the accelerometer.

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    1. Tan H., Wilson A.M., Lowe J. Measurement of stride parameters using a wearable GPS and inertial measurement unit. J. Biomech. 2008;41:1398–1406. doi: 10.1016/j.jbiomech.2008.02.021. - DOI - PubMed
    1. Benocci M., Rocchi L., Farella E., Chiari L., Benini L. A wireless system for gait and posture analysis based on pressure insoles and Inertial Measurement Units; Proceedings of the 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare; London, UK. 1–3 April 2009; pp. 1–6. - DOI
    1. Brodie M., Walmsley A., Page W. Fusion motion capture: A prototype system using inertial measurement units and GPS for the biomechanical analysis of ski racing. Sports Technol. 2008;1:17–28. doi: 10.1080/19346182.2008.9648447. - DOI
    1. Bebek O., Suster M.A., Rajgopal S., Fu M.J., Huang X., Cavusoglu M.C., Young D.J., Mehregany M., van den Bogert A.J., Mastrangelo C.H. Personal Navigation via High-Resolution Gait-Corrected Inertial Measurement Units. IEEE Trans. Instrum. Meas. 2010;59:3018–3027. doi: 10.1109/TIM.2010.2046595. - DOI
    1. Bonnet V., Mazzà C., Fraisse P., Cappozzo A. Real-time Estimate of Body Kinematics During a Planar Squat Task Using a Single Inertial Measurement Unit. IEEE Trans. Biomed. Eng. 2013;60:1920–1926. doi: 10.1109/TBME.2013.2245131. - DOI - PubMed