Skip to main content

Using Inertial Sensors in Driver Posture Tracking Systems

  • Conference paper
  • First Online:
Proceedings of the 4th International Congress of Automotive and Transport Engineering (AMMA 2018) (AMMA2018 2018)

Abstract

Improving position of car drivers leads to superior driving performance. Ensuring an ideal position can be achieved by real-time tracking and evaluation of the driver’s posture. Thus, this paper proposes a lower-body tracking system using inertial sensors. The developed equipment has the ability to compare the driver’s posture at a given moment with an ideal posture, recorded in the calibration phase, with hardware equipment. In order to compare and evaluate the driver’s postures during driving the car, a mathematical model of the human body has been developed, having as input data the measurements realized with the inertial sensors. This product contains great added value (software component) on a hardware structure (parts such as: smartphone, inertial sensors and controller) which already exists on the market.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ciuti, G., Ricotti, L., Menciassi, A., Dario, P.: MEMS sensor technologies for human centred applications in healthcare, physical activities, safety and environmental sensing: a review on research activities in Italy. Sensors (Basel) 15, 6441–6468 (2015)

    Article  Google Scholar 

  2. Kim, J.-N., Ryu, M.-H., Choi, H.-R., Yang, Y.-S., Kim, T.-K.: Development and functional evaluation of an upper extremity rehabilitation system based on inertial sensors and virtual reality. Int. J. Distrib. Sens. Netw. 2013, 1–7 (2013)

    Article  Google Scholar 

  3. Leardini, A., Lullini, G., Giannini, S., Berti, L., Ortolani, M., Caravaggi, P.: Validation of the angular measurements of a new inertial-measurement-unit based rehabilitation system: comparison with state-of-the-art gait analysis. J. NeuroEng. Rehabil. 11, 2–7 (2014)

    Article  Google Scholar 

  4. Li, H.T., Huang, J.J., Pan, C.W., Chi, H.I., Pan, M.C.: Inertial sensing based assessment methods to quantify the effectiveness of post-stroke rehabilitation. Sensors (Basel) 15, 196–209 (2015)

    Google Scholar 

  5. Baba, M.J., Beyea, J., Landry, J., Sexton, A., McGibbon, C.A.: Comparison of strain-gage and fiber-optic goniometry for measuring knee kinematics during activities of daily living and exercise. J. Biomech. Eng. 134, 084502 (2012)

    Article  Google Scholar 

  6. Nerino, R., Contin, L., Tirri, A., Massazza, G., Chimienti, A., Pettiti, G., et al.: An improved solution for knee rehabilitation at home. In: 9th International Conference on Body Area Networks, London, UK, pp. 62–68 (2014)

    Google Scholar 

  7. Moncada-Torres, A., Leuenberger, K., Gonzenbach, R., Luft, A., Gassert, R.: Activity classification based on inertial and barometric pressure sensors at different anatomical locations. Physiol. Meas. 35, 1245–1263 (2014)

    Article  Google Scholar 

  8. Antonya, C., Butnariu, S., Pozna, C.: Real-time representation of the human spine with absolute orientation sensors. In: 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 (2017)

    Google Scholar 

  9. Voinea, G.-D., Butnariu, S., Mogan, G.: Measurement and geometric modelling of human spine posture for medical rehabilitation purposes using a wearable monitoring system based on inertial sensors. Sensors (Switzerland) 17(1), 3 (2017)

    Google Scholar 

  10. Qi, Y., Soh, C.B., Gunawan, E.K., Low, S., Thomas, R.: Lower extremity joint angle tracking with wireless ultrasonic sensors during a squat exercise. Sensors (Basel) 15, 9610–9627 (2015)

    Article  Google Scholar 

  11. Attal, F., Mohammed, S., Dedabrishvili, M., Chamroukhi, F., Oukhellou, L., Amirat, Y.: Physical human activity recognition using wearable sensors. Sensors (Basel) 15, 31314–31338 (2015)

    Article  Google Scholar 

  12. Papi, E., Osei-Kuffour, D., Chen, Y.M., McGregor, A.H.: Use of wearable technology for performance assessment: a validation study. Med. Eng. Phys. 37, 698–704 (2015)

    Article  Google Scholar 

  13. Patel, S., Park, H., Bonato, P., Chan, L., Rodgers, M.: Review of wearable sensors and systems with application in rehabilitation. J. NeuroEng. Rehabil. 9, 2–17 (2012)

    Article  Google Scholar 

  14. Bakhshi, S., Mahoor, M.H., Davidson, B.S.: Development of a body joint angle measurement system using IMU sensors. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, 30 August–3 September (2011). https://doi.org/10.1109/iembs.2011.6091743

  15. Kinect Sensor. https://msdn.microsoft.com/en-us/library/hh438998.aspx. Accessed 26 Apr 2018

  16. Bosch Sensortec. BNO055, Data Sheets. https://www.bosch-sensortec.com/bst/products/all_products/bno055. Accessed 26 Apr 2018

  17. Roetenberg, D., Luinge, H., Slycke, P.: Xsens MVN: full 6DOF human motion tracking using miniature inertial sensors, XSENS TECHNOLOGIES – ver. April 3 (2013)

    Google Scholar 

  18. Yuan, Q., Chen, I.-M.: Localization and velocity tracking of human via 3 IMU sensors. Sens. Actuators A 212, 25–33 (2014)

    Article  Google Scholar 

  19. Otani, T., Hashimoto, K., Miyamae, S., Ueta, H., Natsuhara, A., Sakaguchi, M., Kawakami, Y., Lim, H.-O., Takanishi, A.: Upper-body control and mechanism of humanoids to compensate for angular momentum in the yaw direction based on human running. Appl. Sci. 8, 44 (2018). https://doi.org/10.3390/app8010044

    Article  Google Scholar 

Download references

Acknowledgments

The publishing of this paper was supported by the project no. 1804/2018, entitled “SIM-TACK/Real-time motion tracking system for physiotherapy exercises for people with special educational needs” financed by Transilvania University of Brasov, programme “Grants for interdisciplinary teams”, competition 2018.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Silviu Butnariu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Butnariu, S., Mogan, G., Antonya, C. (2019). Using Inertial Sensors in Driver Posture Tracking Systems. In: Burnete, N., Varga, B. (eds) Proceedings of the 4th International Congress of Automotive and Transport Engineering (AMMA 2018). AMMA2018 2018. Proceedings in Automotive Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-94409-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-94409-8_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94408-1

  • Online ISBN: 978-3-319-94409-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics