Abstract
This paper presents a new and simple gait analysis system, from a depth camera placed in front of a subject walking on a treadmill, capable of detecting a healthy gait from an impaired one. Our system relies on the fact that a normal or healthy walk typically exhibits a smooth motion (depth) signal, at each pixel with less high-frequency spectral energy content than an impaired or abnormal walk. Thus, the estimation of a map showing the location and the amplitude of the high-frequency spectral energy (HFSE), for each subject, allows clinicians to visually quantify and localize the different impaired body parts of the patient and to quickly detect a possible disease. Even if the HFSE maps obtained are clearly intuitive for a rapid clinical diagnosis, the proposed system makes an automatic classification between normal gaits and those who are not with success rates ranging from 88.23 % to 92.15 %.
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References
Motion capture systems from vicon. http://www.vicon.com/
Alexander, L.D., Black, S.E., Patterson, K.K., Gao, F., Danells, C.J., Mcllroy, W.E.: Association between gait asymmetry and brain lesion location in stroke patients. Stroke 40(2), 537–544 (2009)
Auvinet, E., Multon, F., Meunier, J.: Lower limb movement asymmetry measurement with a depth camera. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 6793–6796, August 2012
Carse, B., Meadows, B., Bowers, R., Rowe, P.: Affordable clinical gait analysis: an assessment of the marker tracking accuracy of a new low-cost optical 3d motion analysis system. Physiotherapy 99(4), 347–351 (2013). http://www.science direct.com/science/article/pii/S0031940613000266
Clark, R.A., Bower, K.J., Mentiplay, B.F., Paterson, K., Pua, Y.H.: Concurrent validity of the microsoft kinect for assessment of spatiotemporal gait variables. J. Biomech. 46(15), 2722–2725 (2013)
Gabel, M., Gilad-Bachrach, R., Renshaw, E., Schuster, A.: Full body gait analysis with kinect. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1964–1967. IEEE (2012)
Hamill, J., Bates, B., Knutzen, K.: Ground reaction force symmetry during walking and running. Res. Q. Exerc. Sport 55(3), 289–293 (1984)
Hansard, M., Lee, S., Choi, O., Horaud, R.: Time-of-Flight Cameras. Springer, Heidelberg (2013)
Lazaros, N., Sirakoulis, G.C., Gasteratos, A.: Review of stereo vision algorithms: from software to hardware. Int. J. Optomechatronics 2(4), 435–462 (2008)
Leu, A., Ristic-Durrant, D., Graser, A.: A robust markerless vision-based human gait analysis system. In: 2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI), pp. 415–420 (May 2011)
Loizeau, J., Allard, P., Duhaime, M., Landjerit, B.: Bilateral gait patterns in subjects fitted with a total hip prosthesis. Arch. Phys. Med. Rehab. 76(6), 552–557 (1995)
Moevus, A., Mignotte, M., de Guise, J., Meunier, J.: Evaluating perceptual maps of asymmetries for gait symmetry quantification and pathology detection. In: 36th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, Illinois, USA, August 2014
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, É.: Scikit-learn: machine learning in python. J. Mach. Learn. Res. 12, 2825–2830 (2011)
Potdevin, F., Gillet, C., Barbier, F., Coello, Y., Moretto, P.: The study of asymmetry in able-bodied gait with the concept of propulsion and brake. In: 9th Symposium on 3D Analysis of Human Movement, Valenciennes, France (2006)
Rougier, C., Auvinet, E., Meunier, J., Mignotte, M., de Guise, J.A.: Depth energy image for gait symmetry quantification. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 5136–5139. IEEE (2011)
Salvi, J., Pages, J., Batlle, J.: Pattern codification strategies in structured light systems. Pattern Recogn. 37(4), 827–849 (2004)
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Ndayikengurukiye, D., Mignotte, M. (2016). High-Frequency Spectral Energy Map Estimation Based Gait Analysis System Using a Depth Camera for Pathology Detection. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_5
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DOI: https://doi.org/10.1007/978-3-319-41501-7_5
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