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Using Kinect to Capture the Joint Angles of Static Driving Posture

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Advances in Physical Ergonomics & Human Factors (AHFE 2018)

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Abstract

Anthropometric measurements of driving posture have been an attractive scientific issue concerning drivers’ comfort and safety. However, Kinect, as a low-cost motion capture device, was seldom used. In this study, 10 participants were recruited and 40 experiments were conducted. The driving posture of all participants was captured twice from frontal and sagittal plane. Shoulder flexion angles (SFA) and elbow flexion angles (EFA) were calculated using Kinect-captured skeletal data and compared with the corresponding angles measured with a protractor. Our study revealed a significant lower bias compared with the protractor measured angles (p = 0.000) and more accurate angles (p = 0.026) were found in the sagittal plane than in the frontal plane. The mean bias of SFA and EFA for the frontal plane was 18.8°, while it was 9.7° for the sagittal plane. More robust algorithms are anticipated in future study, and group Kinects may compensate for the low accuracy of single Kinect use.

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References

  1. Grujicic, M., Pandurangan, B., Xie, X., Gramopadhye, A.K., Wagner, D., Ozen, M.: Musculoskeletal computational analysis of the influence of car-seat design/adjustments on long-distance driving fatigue. Int. J. Ind. Ergonom. 40, 345–355 (2010)

    Article  Google Scholar 

  2. Coelho, D.A., Dahlman, S.: Articulation at shoulder level: a pilot experimental study on car seat comfort. Appl. Ergon. 43, 2–37 (2012)

    Article  Google Scholar 

  3. Pannetier, R., Wang, X.G.: A comparison of clutching movements of freely adjusted and imposed pedal configurations for identifying discomfort assessment criteria. Appl. Ergon. 45, 101–1018 (2014)

    Article  Google Scholar 

  4. Kovacevic, S., Vučinić, J., Kirin, S., Pejnović, N.: Impact of anthropometric measurements on ergonomic driver posture and safety. Period. Biol. 112, 51–54 (2010)

    Google Scholar 

  5. Andreoni, G., Santambrogio, G.C., Rabuffetti, M., Pedotti, A.: Method for the analysis of posture and interface pressure of car drivers. Appl. Ergon. 33, 511–522 (2002)

    Article  Google Scholar 

  6. Eger, T., Stevenson, J., Callaghan, J.P., Grenier, S.: VibRG: Predictions of health risks associated with the operation of load-haul-dump mining vehicles: Part 2-Evaluation of operator driving postures and associated postural loading. Int. J. Ind. Ergonom. 38, 801–815 (2008)

    Article  Google Scholar 

  7. Zhao, C.H., Gao, Y.S., He, J., Lian, J.: Recognition of driving postures by multiwavelet transform and multilayer perceptron classifier. Eng. Appl. Artif. Intel. 25, 1677–1686 (2012)

    Article  Google Scholar 

  8. Kondyli, A., Sisiopiku, V., Barmpoutis, A.: A 3D experimental framework for exploring drivers’ body activity using infrared depth sensors. Connected Vehicles and Expo (ICCVE). Las Vegas, NV, pp. 574–579. IEEE (2013)

    Google Scholar 

  9. Bonnechère, B., Jansen, B., Salvia, P., Bouzahouene, H., Omelina, L., Cornelis, J., Rooze, M., Jan, S.V.S.: What are the current limits of the Kinect™ sensor? In: Proceedings of the 9th International Conference Disability, Virtual Reality & Associated Technologies. France: Laval, 2012, 287 (2012)

    Google Scholar 

  10. Staranowicz, A., Brown, G., Mariottini, G.L.: Evaluating the accuracy of a mobile kinect-based gait-monitoring system for fall prediction. In: Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA 2013)

    Google Scholar 

  11. Dutta, T.: Evaluation of the Kinect™ sensor for 3-D kinematic measurement in the workplace. Appl. Ergon. 43, 645–646 (2012)

    Article  Google Scholar 

  12. Schwarz, L.A., Mkhitaryan, A., Mateus, D., Navab, N.: Human skeleton tracking from depth data using geodesic distances and optical flow. Image Vis. Compt. 30(3), 217–226 (2012)

    Article  Google Scholar 

  13. Huber, M.E., Seitz, A.L., Leeser, M., Sternad, D.: Validity and reliability of kinect for measuring shoulder joint angles. In: Northeast Bioengineering Conference (NEBEC). Boston, MA, pp. 1–2. IEEE (2014)

    Google Scholar 

  14. Johoson, B.: Hand position on steering wheel during driving. Traffic Inj. Prev. 12(2), 187–190 (2011)

    Article  Google Scholar 

  15. Edmondston, S.J, Henne, S.E., Loh, W., Østvold, E.: Influence of cranio-cervical posture on three-dimensional motion of the cervical spine. Manual Ther. 10, 44–51 (2005)

    Article  Google Scholar 

  16. Grimmer-Somers, K., Milanese, S., Louw, Q.: Measurement of cervical posture in the sagittal plane. J. Manip. Physiol. Ther. 9, 509–517 (2008)

    Article  Google Scholar 

  17. Kyung, G., Nussbaum, M.A.: Specifying comfortable driving postures for ergonomic design and evaluation of the driver workspace using digital human models. Ergonomics 52(8), 941–943 (2014)

    Google Scholar 

  18. Galna, B., Barry, G., Jackson, D., Mhiripiri, D., Olivier, P., Rochester, L.: Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson’s disease. Gait Posture. 39, 1062–1068 (2014)

    Article  Google Scholar 

  19. Schmidt, S., Seiberl, W., Schwirtz, A.: Influence of different shoulder-elbow configurations on steering precision and steering velocity in automotive context. Appl. Ergon. 46, 176–183 (2015)

    Article  Google Scholar 

  20. Xu, X., McGorry, R.W.: The validity of the first and second generation Microsoft Kinect™ for identifying joint center locations during static postures. Appl. Ergon. 49, 47–54 (2015)

    Article  Google Scholar 

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Acknowledgements

This research is supported by Special funds for the basic R&D undertakings by welfare research institutions (522016Y-4680), National Key R&D Program of China (2017) YFF0206602, General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China (201510042). The authors also appreciate the support from the State Scholarship Fund from China Scholarship Council (201208110144), the National Natural Science Foundation of China (51005016), and Fundamental Research Funds for the Central Universities, China (FRF-TP-14-026A2).

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Correspondence to Jianwei Niu .

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Zhao, Y., Wang, Y., Niu, J., Ran, L., Liu, T. (2019). Using Kinect to Capture the Joint Angles of Static Driving Posture. In: Goonetilleke, R., Karwowski, W. (eds) Advances in Physical Ergonomics & Human Factors. AHFE 2018. Advances in Intelligent Systems and Computing, vol 789. Springer, Cham. https://doi.org/10.1007/978-3-319-94484-5_31

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  • DOI: https://doi.org/10.1007/978-3-319-94484-5_31

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  • Online ISBN: 978-3-319-94484-5

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