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The Implementation of a Kinect-Based Postural Assessment System

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Inclusive Smart Cities and Digital Health (ICOST 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9677))

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Abstract

In some hospitals, rehabilitation professionals usually adopt the visual assessment incorporated with some posture charts to assess whether a patient has good postures while he or she is standing still or stretching some joints. While the advantages of the visual assessment are its simplicity and no need of expensive equipment, its disadvantages are imprecise, subjective, inefficient, etc. In this paper, we report the implement of a Kinect-based postural assessment system which is able to perform postural assessment and create an analysis report with 62 measurements including 22 angles, 35 distances, and 5 postural rotations. Based on the proposed Kinect-based postural assessment system, rehabilitation specialists are then able to objectively assess the treatment effect after each individual course of treatment.Some experiments were designed to measure the accuracy of the proposed system to verify whether it has the potential of being adopted at hospitals.

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References

  1. Missaoui, B., Portero, P., Bendaya, S., Hanktie, O., Thoumie, P.: Posture and equilibrium in orthopedic and rheumatologic diseases. Neurophysiologies Clin./Clin. Neurophysiol. 38(6), 447–457 (2008)

    Article  Google Scholar 

  2. Do, J.L., Rosário, P.: Biomechanical assessment of human posture: a literature review. J. Bodywork Mov. Ther. 18(3), 368–373 (2014)

    Article  Google Scholar 

  3. Normand, M.C., Descarreaux, M., Harrison, D.D., Harrison, D.E., Perron, D.L., Ferrantelli, J.R., Janik, T.J.: Three dimensional evaluation of posture in standing with the PosturePrint in an intra- and inter-examiner reliability study. Chiropractic Osteopathy 15, 15 (2007)

    Article  Google Scholar 

  4. Souza, J.A., Pasinato, F., Basso, D., Corrêa, E.C.R., da Silva, A.M.T.: Biophotogrametry: reliability of measurements obtained with an posture assessment software (SAPO). Revista Brasileira de Cineantropometria E Desempenho Humano 13(4), 299–305 (2011)

    Article  Google Scholar 

  5. Nixon, M.E., Howard, A.M., Chen, Y.P.: Quantitative evaluation of the Microsoft Kinect for use in an upper extremity virtual rehabilitation environment. In: 2013 International Conference. Virtual Rehabilitation (ICVR), pp. 222–228 (2013)

    Google Scholar 

  6. 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 

  7. Clark, R.A., Vernon, S., Mentiplay, B.F., Miller, K.J., McGinley, J.L., Pua, Y.H., Paterson, K., Bower, K.J.: Instrumenting gait assessment using the kinect in people living with stroke: reliability and association with balance tests. J. NeuroEngineering Rehabil. 12(15) (2015). doi:10.1186/s12984-015-0006-8

    Google Scholar 

  8. Cippitelli, E., Gasparrini, S., Spinsante, S., Gambi, E.: Kinect as a tool for gait analysis: validation of a real-time joint extraction algorithm working in side view. Sensors 15, 1417–1434 (2015)

    Article  Google Scholar 

  9. Schmitz, A., Ye, M., Boggess, G., Shapiro, R., Yang, R., Noehren, B.: The measurement of in vivo joint angles during a squat using a single camera markerless motion capture system as compared to a marker based system. Gait Posture 41, 694–698 (2015)

    Article  Google Scholar 

  10. Huang, J.D.: Kinerehab: a kinect-based system for physical rehabilitation — a pilot study for young adults with motor disabilities. In: The 13th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 319–320 (2011)

    Google Scholar 

  11. Clark, R., Pua, Y.H., Fortin, K., Ritchie, C., Webster, K.E., Denehy, L., Bryant, A.L.: Validity of the Microsoft Kinect for assessment of postural control. Gait Posture 36, 372–377 (2012)

    Article  Google Scholar 

  12. Metcalf, C.D., Robinson, R., Malpass, A.J., Bogle, T.P., Dell, T.A., Harris, C., Demain, S.H.: Markerless motion capture and measurement of hand kinematics: validation and application to home-based upper limb rehabilitation. IEEE Trans. Biomed. Eng. 60, 2184–2192 (2013)

    Article  Google Scholar 

  13. Clark, R.A., Pua, Y.H., Bryant, A.L., Hunt, M.A.: Validity of the Microsoft Kinect for providing lateral trunk lean feedback during gait retraining. Gait Posture 38, 1064–1066 (2013)

    Article  Google Scholar 

  14. Mentiplay, B.F., Clark, R.A., Mullins, A., Bryant, A.L., Bartold, S., Paterson, K.: Reliability and validity of the Microsoft Kinect for evaluating static foot posture. J. Foot Ankle Res. 6(14) (2013). doi:10.1186/1757-1146-6-14

  15. Su, M.C., Jhang, J.J., Hsieh, Y.Z., Yeh, S.C., Lin, S.C., Lee, S.F., Tseng, K.P.: Depth-sensor-based monitoring of therapeutic exercises. Sensors 15(10), 25628–25647 (2015)

    Article  Google Scholar 

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Acknowledgements

This paper was partly supported by Ministry of Science and Technology, Taiwan, R.O.C., under NSC 104-2221-E-008-074-MY2 and NCU-LSH Joint Research Foundation 102-LSH-105-A-004.

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Correspondence to Mu-Chun Su .

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Su, MC., Lin, SH., Lee, SF., Huang, YS., Chen, HR. (2016). The Implementation of a Kinect-Based Postural Assessment System. In: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_45

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  • DOI: https://doi.org/10.1007/978-3-319-39601-9_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39600-2

  • Online ISBN: 978-3-319-39601-9

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