Visualização Postural Bidimensional utilizando Sensor de Profundidade de Baixo Custo
Abstract
Postural assessment is the main method for evaluating, diagnosing, and treating postural deviations caused by several reasons, whether natural or irregular posture. In this paper, we used the Kinect sensor and Unity to collect data and perform a postural reading of standing up individuals in their natural position and observe possible deviations through angular measurements of predefined joints. In the results, the proposed method was compared with the manual evaluation technique that uses a symmetrograph. We show that the method can be used to evaluate postures as an alternative to the symmetrograph.
References
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de Gusm˜ão Lafayette, T. B., Teixeira, J. M. X. N., and Da Gama, A. E. F. (2019). Hybrid solution for motion capture with kinect v2 to different biotypes recognition. In XXVI Brazilian Congress on Biomedical Engineering, pages 249–259. Springer.
de Matos, O. (2011). Avaliação postural e prescrição de exercícios corretivos. Phorte Editora LTDA.
dos Santos, J. B. (2018). Descrição do método de avaliação postural de portland state university. Fisioterapia Brasil, 6(5):392–395.
Hoy, D. (2014). The global burden of low back pain: estimates from the global burden of disease 2010 study. Ann Rheum Dis. doi, 10.
Iunes, D., Bevilaqua-Grossi, D., Oliveira, A., Castro, F., and Salgado, H. (2009). Análise comparativa entre avaliação postural visual e por fotogrametria computadorizada. Revista Brasileira de Fisioterapia, 13(4):308–315.
Rumen, F. (2013). Kinect with ms-sdk. https://rfilkov.com/2013/12/16/kinect-with-ms-sdk/.
Shum, H. P. H., Ho, E. S. L., Jiang, Y., and Takagi, S. (2013). Real-time posture reconstruction for microsoft kinect. IEEE Transactions on Cybernetics, 43(5):1357–1369.
Xu, Z., Zhang, Y., Fu, C., Liu, L., Chen, C., Xu, W., and Guo, S. (2020). Back shape measurement and three-dimensional reconstruction of spinal shape using one kinect sensor. In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pages 1–5. IEEE.
Published
2020-09-10
How to Cite
DA SILVA, Danilo.
Visualização Postural Bidimensional utilizando Sensor de Profundidade de Baixo Custo. In: REGIONAL SCHOOL ON COMPUTING OF CEARÁ, MARANHÃO, AND PIAUÍ (ERCEMAPI), 8. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 149-156.
DOI: https://doi.org/10.5753/ercemapi.2020.11479.
