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Computational gait analysis for post-stroke rehabilitation purposes using fuzzy numbers, fractal dimension and neural networks

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Języki publikacji
EN
Abstrakty
EN
Computational gait analysis constitutes a useful tool for quantitative assessment of gait disturbances, improving functional diagnosis, assessment of treatment planning, and monitoring of disease progress. There is little research on use of computational gait analysis in neurorehabilitation of post-stroke survivors, but current evidence on its clinical application supports a favorable cost-benefit ratio. The research was conducted among 50 adult people: 25 of them after ischemic stroke constituted the study group, and 25 healthy volunteers constituted the reference group. Study group members were treated for 2 weeks (10 neurorehabilitation sessions). Spatio-temporal gait parameters were assessed before and after therapy and compared using a novel fuzzy-based assessment tool, fractal dimension measurement and gait classification based on artificial neural networks. Measured results of rehabilitation (changes of gait parameters) were statistically relevant and reflected recovery. There is good evidence to extend its use to patients with various gait diseases undergoing neurorehabilitation. However, methodology for properly conducting and interpreting the proposed assessment and analysis procedures, providing validity and reliability of their results remains a key issue. More objective clinical reasoning, based on proposed novel tools, requires further research.
Rocznik
Strony
191--198
Opis fizyczny
Bibliogr. 34 poz. rys., tab.
Twórcy
  • Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University, Kopernika 1, 85-074 Bydgoszcz, Poland
  • Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University, Kopernika 1, 85-074 Bydgoszcz, Poland
  • Neurocognitive Laboratory, Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Poland
autor
  • Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University, Kopernika 1, 85-074 Bydgoszcz, Poland
  • Department of Physiotherapy, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Poland
Bibliografia
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  • [4] P. Prokopowicz, E. Mikołajewska, D. Mikołajewski, and P. Kotlarz, “Analysis of temporospatial gait parameters”, In P. Prokopowicz, J. Czerniak, D. Mikołajewski, Ł. Apiecionek and D. Ślezak (eds.), Theory and Applications of Ordered Fuzzy Numbers: A Tribute to Professor Witold Kosiński, 289‒302. Springer International Publishing, Cham (2017).
  • [5] P. Prokopowicz, D. Mikołajewski, E. Mikołajewska, and P. Kotlarz, “Fuzzy system as an assessment tool for analysis of the health-related quality of life for the people after stroke”, In L. Rutkowski, M. Korytkowski, R. Scherer, R. Tadeusiewicz, L.A. Zadeh and J. M. Zurada (eds.), Artificial Intelligence and Soft Computing, 710–721. Springer International Publishing, Cham (2017).
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  • [7] E. Mikołajewska, “Metoda NDT-Bobath w neurorehabilitacji osób dorosłych”, Wydawnictwo Lekarskie PZWL (2012).
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  • [16] E. Mikołajewska, “Normalized gait parameters in NDT-bobath post-stroke gait rehabilitation”, Open Medicine 7(2) (2012).
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  • [18] E. Mikołajewska, “Associations between results of post-stroke NDT-Bobath rehabilitation in gait parameters, ADL and hand functions”, Adv Clin Exp Med 22(5), 731–738 (2013).
  • [19] E. Mikołajewska, “NDT-bobath method in post-stroke rehabilitation in adults aged 42–55 years – preliminary findings”, Polish Annals of Medicine 22(2), 98–104 (2015).
  • [20] M. Kılınç, F. Avcu, O. Onursal, E. Ayvat, C.S. Demirci, and S.A. Yildirim, “The effects of bobath-based trunk exercises on trunk control, functional capacity, balance, and gait: a pilot randomized controlled trial”, Topics in Stroke Rehabilitation 23(1), 50–58 (2016).
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Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-03b65456-07e3-4fc0-bc42-38d2fab4a8c5
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