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People identification based on dynamic determinants of human gait

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper a way of people identification, based on ground reaction forces during gait, is presented. The authors established that each individual has an unique gait pattern that can be described by quantitative parameters, calculated using measurements coming from the force plates. Fifteen volunteers took part in this study. Each person walked barefoot at least 100 times through 10-m-long walkway with the force plates built in. Determinants were calculated based on vertical and anterior-posterior components of the ground reaction force. The obtained parameters were used as an input matrix of the artificial neural network designed for identification of each person. Effectiveness of the recognition was assessed as root mean square error between expected and obtained output values. It was proved, that human identification based on presented determinants of the gait and artificial neural network is possible at a high level.
Rocznik
Tom
Strony
1--6
Opis fizyczny
Bibliogr. 11 poz., 1 wykr.
Twórcy
autor
  • Institute of Applied Mechanics, Faculty of Mechanical Engineering and Management, Poznan University of Technology, Jana Pawła II 24, 60-965 Poznań, Poland, tomasz.walczak@put.poznan.pl
  • Institute of Applied Mechanics, Faculty of Mechanical Engineering and Management, Poznan University of Technology, Jana Pawła II 24, 60-965 Poznań, Poland, jakub.grabski@put.poznan.pl
autor
  • Institute of Applied Mechanics, Faculty of Mechanical Engineering and Management, Poznan University of Technology, Jana Pawła II 24, 60-965 Poznań, Poland
Bibliografia
  • 1. C. J. Payton, E. M. Bartlett (eds.), Biomechanical evaluation of movement in sport and exercise, Routledge: Taylor & Francis Group, London and New York 2008.
  • 2. C. Rzymkowski, Selected aspects of the experimental methods of impact biomechanics, Vibrations in Physical Systems, 27 (2016) 25 - 34.
  • 3. I. Lubowiecka, Dynamics of mechanical model of implant-tissue system in ventral hernia repair, Vibrations in Physical Systems, 25 (2012) 261 - 266.
  • 4. P. Rahimian, J. K. Kearney, Optimal camera placement for motion capture systems, IEEE Transactions on Visualization and Computer Graphics, 23 (2017) 1209 - 1221.
  • 5. R. Merletti, P. Parker (eds.), Electromyography. Physiology, engineering and noninvasive applications, IEEE Press, New Jersey 2004.
  • 6. J. K. Grabski, S. Kazimierczuk, T. Walczak, Analysis of the electromyographic signal during rehabilitation exercises of the knee joint, Vibrations in Physical Systems, 26 (2014) 79 - 86.
  • 7. M. Grygorowicz, M. Michałowska, T. Walczak, A. Owen, J. K. Grabski, A. Pyda, T. Piontek, T. Kotwicki, Discussion about different cut-off values of conventional harmstring-to-quadriceps ratio used in hamstring injury prediction among, professional male football players, PLoS ONE, 12(2) e0188974.
  • 8. T. Walczak, J. K. Grabski, M. Grajewska, M. Michałowska, The recognition of human by the dynamic determinants of the gait with use of ANN, In: Springer Proceedings in Mathematics and Statistics, Dynamical Systems: Modelling, J. Awrejcewicz (ed.), Springer, Cham, 181 (2016) 375 - 385.
  • 9. V. T. Iman, H. J. Ralston, F. Todd, J. C. Lieberman, Human walking, Baltimore: Williams & Wilkins 1981.
  • 10. J. K. Grabski, T. Walczak, M. Michałowska, M. Cieślak, Gender recognition using artificial neural networks and data coming from force plates, In: Innovations in Biomedical Engineering. IBE 2017. Advances in Intelligent Systems and Computing, M. Gzik et al. (eds.), Springer, Cham, 623 (2018) 53 - 60.
  • 11. T. Walczak, J. K. Grabski, M. Grajewska, M. Michałowska, Application of artificial neural networks in man’s gait recognition, In: Advances in Mechanics: Theoretical, Computational and Interdisciplinary Issues. Proceedings of the 3rd Polish Congress of Mechanics (PCM) and 21st International Conference on Computer Methods in Mechanics (CMM), M. Kleiber et al. (eds.), CRC Press, Taylor & Francis Group, London 2016, 591 - 594.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0701e048-3a7e-43eb-a666-e3e9b8ef182a
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