Skip to main content
SpringerLink
Log in

Validation of foot pitch angle estimation using inertial measurement unit against marker-based optical 3D motion capture system

  • Original Article
  • Published:
Biomedical Engineering Letters Aims and scope Submit manuscript

Abstract

Gait analysis is relevant to a broad range of clinical applications in areas of orthopedics, neurosurgery, rehabilitation and the sports medicine. There are various methods available for capturing and analyzing the gait cycle. Most of gait analysis methods are computationally expensive and difficult to implement outside the laboratory environment. Inertial measurement units, IMUs are considered a promising alternative for the future of gait analysis. This study reports the results of a systematic validation procedure to validate the foot pitch angle measurement captured by an IMU against Vicon Optical Motion Capture System, considered the standard method of gait analysis. It represents the first phase of a research project which aims to objectively evaluate the ankle function and gait patterns of patients with dorsiflexion weakness (commonly called a “drop foot”) due to a L5 lumbar radiculopathy pre- and post-lumbar decompression surgery. The foot pitch angle of 381 gait cycles from 19 subjects walking trails on a flat surface have been recorded throughout the course of this study. Comparison of results indicates a mean correlation of 99.542% with a standard deviation of 0.834%. The maximum root mean square error of the foot pitch angle measured by the IMU compared with the Vicon Optical Motion Capture System was 3.738° and the maximum error in the same walking trail between two measurements was 9.927°. These results indicate the level of correlation between the two systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Baker R. Gait analysis methods in rehabilitation. J Neuroeng Rehabil. 2006;3:4.

    Article  Google Scholar 

  2. Tao W, Liu T, Zheng R, Feng H. Gait analysis using wearable sensors. Sensors (Basel). 2012;12(2):2255–83.

    Article  Google Scholar 

  3. Cloete T, Scheffer C. Repeatability of an off-the-shelf, full body inertial motion capture system during clinical gait analysis. In: 2010 annual international conference on ieee engineering in medicine and biology society EMBC’10, p. 5125–5128; 2010.

  4. Zhou H, Hu H. Human motion tracking for rehabilitation—a survey. Biomed Signal Process Control. 2008;3(1):1–18.

    Article  Google Scholar 

  5. Moeslund TB, Krüger V. A survey of advances in vision-based human motion capture and analysis. Comput Vis Image Underst. 2006;104(2):90–126.

    Article  Google Scholar 

  6. J. Cockcroft. An evaluation of inertial motion capture technology for use in the analysis and optimization of road cycling kinematics. no. March, 2011.

  7. Simon SR. Quantification of human motion: gait analysis—benefits and limitations to its application to clinical problems. J Biomech. 2004;37(12):1869–80.

    Article  Google Scholar 

  8. K. Tong, M.H. Granat. A practical gait analysis system using gyroscopes.pdf, vol. 21; 1999. p. 87–94.

  9. Pappas IPI, Keller T, Mangold S, Popovic MR, Dietz V, Morari M. A reliable gyroscope-based gait-phase detection sensor embedded in a shoe insole. IEEE Sens J. 2004;4(2):268–74.

    Article  Google Scholar 

  10. Auvinet B, et al. Reference data for normal subjects obtained with an accelerometric device. Gait Posture. 2002;16(2):124–34.

    Article  Google Scholar 

  11. Aminian K, Najafi B, Büla C, Leyvraz PF, Robert P. Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. J Biomech. 2002;35(5):689–99.

    Article  Google Scholar 

  12. Huang Y, Jirattigalachote W, Cutkosky MR, Zhu X, Shull PB. Novel foot progression angle algorithm estimation via foot-worn, magneto-inertial sensing. IEEE Trans Biomed Eng. 2016;63(11):2278–85.

    Article  Google Scholar 

  13. Coley B, Najafi B, Paraschiv-Ionescu A, Aminian K. Stair climbing detection during daily physical activity using a miniature gyroscope. Gait Posture. 2005;22(4):287–94.

    Article  Google Scholar 

  14. Mayagoitia RE, Nene AV, Veltink PH. Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. J Biomech. 2002;35(4):537–42.

    Article  Google Scholar 

  15. Wu G, Ladin Z. The study of kinematic transients in locomotion using the integrated kinematic sensor. IEEE Trans Rehabil Eng. 1996;4(3):193–200.

    Article  Google Scholar 

  16. Lau H, Tong K. The reliability of using accelerometer and gyroscope for gait event identification on persons with dropped foot. Gait Posture. 2008;27(2):248–57.

    Article  Google Scholar 

  17. Fourati H. Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter. IEEE Trans Instrum Meas. 2015;64(1):221–9.

    Article  Google Scholar 

  18. F. Woyano, S. Lee, S. Park. Evaluation and comparison of performance analysis of indoor inertial navigation system based on foot mounted IMU. In: International conference on advanced communication technology ICACT, vol. 2016–March; 2016. p. 792–798.

  19. Li Q, Young M, Naing V, Donelan JM. Walking speed and slope estimation using shank-mounted inertial measurement units. 2009 IEEE Int Conf Rehabil Robot ICORR. 2009;2009:839–44.

    Google Scholar 

  20. Luinge HJ, Veltink PH, Baten CTM. Ambulatory measurement of arm orientation. J Biomech. 2007;40(1):78–85.

    Article  Google Scholar 

  21. Van Den Noort JC, Kortier HG, Van Beek N, Veeger DHEJ, Veltink PH. Measuring 3D hand and finger kinematics—a comparison between inertial sensing and an opto-electronic marker system. PLoS ONE. 2016;11(11):1–16.

    Google Scholar 

  22. Curtin university. Motion Anlysis Lab, Facilities and Locations, school and departments; 2015. http://healthsciences.curtin.edu.au/schools-and-departments/physiotherapy-exercise-science/facilities/.

  23. M. Windolf, N. Gö Tzen, M. Morlock. Systematic accuracy and precision analysis of video motion capturing systems—exemplified on the Vicon-460 system.

  24. S.W. List. Using the Arduino Pro Mini 3. 3 V. p. 1–9.

  25. R. Chokshi. Datasheet RS-MPU-6000A-00. p. 52, 2015.

  26. A. Noureldin, T.B. Karamat, J. Georgy. Fundamentals of inertial navigation, satellite-based positioning and their integration, vol. 58, no. 12. Springer, Berlin, 2013.

  27. Sharif Bidabadi S, Murray I, Lee G. The application of inertial measurements unit for the clinical evaluation and assessment of gait events. J Med Eng Technol. 2017;41:309–1902.

    Article  Google Scholar 

  28. A. Kim, M. Golnaraghi. A quaternion-based orientation estimation algorithm using an inertial measurement unit. In: Position Location and Navigation Symposium, 2004, no. May 2004, p. 268–272.

Download references

Acknowledgements

We are grateful to The Kailis foundation group, ST John of God healthcare group, for the funding of this project.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Curtin University of Technology, Perth, Australia

    Shiva Sharif Bidabadi

  2. Department of Electrical and Computer Engineering, Curtin University of Technology, Perth, Australia

    Iain Murray

  3. St John of God Subiaco Hospital, Perth, Australia

    Gabriel Yin Foo Lee

  4. School of Surgery, University of Western Australia, Perth, Australia

    Gabriel Yin Foo Lee

Authors
  1. Shiva Sharif Bidabadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Iain Murray
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gabriel Yin Foo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shiva Sharif Bidabadi.

Ethics declarations

Ethical approval

This study involves Human subjects and the relevant ethical approvals obtained from Curtin University of Technology (Human Research Ethics Office): HR 12/2016 and St John of God healthcare group (HREC): 823.

Conflict of interest

The authors report no financial or other conflict of interest relevant to the subject of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharif Bidabadi, S., Murray, I. & Lee, G.Y.F. Validation of foot pitch angle estimation using inertial measurement unit against marker-based optical 3D motion capture system. Biomed. Eng. Lett. 8, 283–290 (2018). https://doi.org/10.1007/s13534-018-0072-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13534-018-0072-5

Keywords

Search

Navigation