Full Body Three Dimensional Joint Angles Validation Using TEA Ergo Inertial Measurement Units

  • Thomas PeetersEmail author
  • Stijn Verwulgen
  • Raman Garimella
  • Koen Beyers
  • Steven Truijen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 876)


Current literature shows the interesting opportunities of inertial measurement units (IMUs) for outdoor motion capturing. This study validated the accuracy of the TEA ergo IMU for full body joint angles tracking in diverse activities. One subject performed three exercises, consisting of a gait pattern, limb movements and cyclical arm movements. Comparison is Vicon infrared markers. For walking, the average root mean square error (RMSE) is 1.9° for flexion/extension, 2.6° for abduction/adduction and 3.7° for rotation angles. The accuracy of the IMU decreases for fast and complicated limb movements (RMSE ≤8.0°). However, these values are still acceptable, which demonstrates the applicability of the IMUs for use in various domains.


Motion capture Human joint angles Inertial measurement unit 


  1. 1.
    Mjøsund, H.L., Boyle, E., Kjaer, P., et al.: Clinically acceptable agreement between the ViMove wireless motion sensor system and the Vicon motion capture system when measuring lumbar region inclination motion in the sagittal and coronal planes. BMC Musculoskelet. Disord. 18, 124 (2017). Scholar
  2. 2.
    Tadano, S., Takeda, R., Miyagawa, H.: Three dimensional gait analysis using wearable acceleration and gyro sensors based on quaternion calculations. Sensors (Basel) 13, 9321–9343 (2013). Scholar
  3. 3.
    Ayachi, F.S., Nguyen, H.P., Lavigne-Pelletier, C., et al.: Wavelet-based algorithm for auto-detection of daily living activities of older adults captured by multiple inertial measurement units (IMUs). Physiol. Meas. 37, 442–461 (2016). Scholar
  4. 4.
    Zhang, J., Novak, A.C., Brouwer, B., Li, Q.: Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics. Physiol. Meas. 34, N63–N69 (2013). Scholar
  5. 5.
    Lin, J.F.S., Kulić, D.: Human pose recovery using wireless inertial measurement units. Physiol. Meas. 33, 2099–2115 (2012). Scholar
  6. 6.
    Marin-Perianu, R., Marin-Perianu, M., Havinga, P., et al.: A performance analysis of a wireless body-area network monitoring system for professional cycling. Pers. Ubiquitous Comput. 17, 197–209 (2013). Scholar
  7. 7.
    Li, G., Liu, T., Yi, J., et al.: The lower limbs kinematics analysis by wearable sensor shoes. IEEE Sens. J. 16, 2627–2638 (2016). Scholar
  8. 8.
    El-Gohary, M., McNames, J.: Shoulder and elbow joint angle tracking with inertial sensors. IEEE Trans. Biomed. Eng. 59, 2635–2641 (2012). Scholar
  9. 9.
    Bauer, C.M., Rast, F.M., Ernst, M.J., et al.: Concurrent validity and reliability of a novel wireless inertial measurement system to assess trunk movement. J. Electromyogr. Kinesiol. 25, 782–790 (2015). Scholar
  10. 10.
    Morrow, M.M.B., Lowndes, B.R., Fortune, E., et al.: Validation of inertial measurement units for upper body kinematics. J. Appl. Biomech. 33, 227–232 (2017). Scholar
  11. 11.
    Seel, T., Raisch, J., Schauer, T.: IMU-based joint angle measurement for gait analysis. Sensors 14, 6891–6909 (2014). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Thomas Peeters
    • 1
    Email author
  • Stijn Verwulgen
    • 1
  • Raman Garimella
    • 1
    • 2
  • Koen Beyers
    • 2
  • Steven Truijen
    • 3
  1. 1.Department Product Development, Faculty of Design SciencesUniversity of AntwerpAntwerpBelgium
  2. 2.VoxdaleWijnegemBelgium
  3. 3.Rehabilitation and Physiotherapy, Faculty of Medicine and Health SciencesUniversity of AntwerpAntwerpBelgium

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