Computational gait analysis using fuzzy logic for everyday clinical purposes - preliminary findings

• Autorzy: Mikołajewska, E. , Prokopowicz, P. , Mikołajewski, D.
• Języki publikacji: EN

Abstrakty

EN

Background: Proper, early, and exact identification of gait impairments and their causes is regarded as a prerequisite for specific therapy and a useful control tool to assess efficacy of rehabilitation. There is a need for simple tools allowing for quickly detecting general tendencies. Objective: The aim of this paper is to present the outcomes of traditional and fuzzy-based analysis of the outcomes of post-stroke gait reeducation using the NeuroDevelopmental Treatment-Bobath (NDT-Bobath) method. Materials and methods: The research was conducted among 40 adult people: 20 of them after ischemic stroke constituted the study group, and 20 healthy people constituted the reference group. Study group members were treated through 2 weeks (10 therapeutic sessions) using the NDT-Bobath method. Spatio-temporal gait parameters were assessed before and after therapy and compared using novel fuzzy-based assessment tool. Results: Achieved results of rehabilitation, observed as changes of gait parameters, were statistically relevant and reflected recovery. One-number outcomes from the proposed fuzzy-based estimator proved moderate to high consistency with the results of the traditional gait assessment. Conclusions: Observed statistically significant and favorable changes in the health status of patients, described by gait parameters, were reflected also in outcomes of fuzzy-based analysis. Proposed fuzzy-based measure increases possibility of the clinical gait assessment toward more objective clinical reasoning based on common use of the mHealth solutions.

Słowa kluczowe

EN

fuzzy-based analysis; gait; neurologic gait disorders; physical therapy modalities; rehabilitation

• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2017
• Tom: Vol. 13, no. 1
• Strony: 37--42
• Opis fizyczny: Bibliogr. 15 poz., rys.

Twórcy

autor

Mikołajewska, E.

• Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Department of Physiotherapy, Jagiellońska 13-15, 86-067 Bydgoszcz, Poland,
• Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Neurocognitive Laboratory, Wileńska 5, 87-100 Toruń, Poland

autor

Prokopowicz, P.

• Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University in Bydgoszcz, Kopernika 1, 85-064 Bydgoszcz, Poland

autor

Mikołajewski, D.

• Institute of Mechanics and Applied Computer Science, Kazimierz Wielki University in Bydgoszcz, Kopernika 1, 85-064 Bydgoszcz, Poland
• Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Neurocognitive Laboratory, Wileńska 5, 87-100 Toruń, Poland

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)

Identyfikatory

DOI

10.1515/bams-2016-0023