Selection of gait parameters for modified Gillette Gait Index using Hellwig Correlation Based Filter method, random forest method, and correlation methods

• Autorzy: Syczewska Małgorzata , Kocel Krzysztof , Swiecicka Anna , Graff Krzysztof , Krawczyk Maciej , Wasiewicz Piotr , Kalinowska Małgorzata , Szczerbik Ewa

Identyfikatory

DOI

10.1016/j.bbe.2020.07.002

• Języki publikacji: EN

Abstrakty

EN

Objective gait analysis provide a large number of data, which are used for planning further treatment of the patient. Data from groups of patients are used for comparisons of different treatment methods, assessment of the severity of gait deviations, design of classification systems. The Gilette Gait Index (GGI) was designed to express the level of abnormality of the gait pattern of patients with cerebral palsy by one number: a measure of distance between the set of discrete gait parameters of a patient from a similar set of a healthy subject, based on 16 parameters. Gait pathology in other disorders is different, thus other variables may better describe their level of pathology. The aim was to see if modified GGI can be constructed based on other sets of gait variables. To decide which gait variables should be taken three different analytical methods were used: Hellwig Correlation Based Filter, random forest, and correlation methods. Gait data of 84 patients were retrospectively selected: 30 had spastic cerebral palsy, 24 scoliosis, 30 suffered the stroke. The results show, that in the final sets of the 16 parameters chosen by the analyses there are some parameters, which were not present in the original list of GGI. If the number of sixteen parameters is kept, there are more than one optimal set of parameters. In conclusion, the use of analytical methods enabled the choice of sets of 16 gait parameters which are specific for the medical problem, and the calculation of modified GGIs.

Słowa kluczowe

EN

gillette gait index; gait parameters; Hellwig method; random forest

PL

analiza chodu; metoda Hellwiga; las losowy

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 3
• Strony: 1267--1276
• Opis fizyczny: Bibliogr. 29 poz., tab.

Twórcy

autor

Syczewska Małgorzata

• Department Rehabilitation, The Children's Memorial Health Institute, Warsaw, Poland

autor

Kocel Krzysztof

• Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland

autor

Swiecicka Anna

• Department Rehabilitation, The Children's Memorial Health Institute, Warsaw, Poland

autor

Graff Krzysztof

• Department Rehabilitation, The Children's Memorial Health Institute, Warsaw, Poland; Faculty of Rehabilitation, Józef Pilsudski University of Physical Education in Warsaw, Poland

autor

Krawczyk Maciej

• 2nd Department Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland

autor

Wasiewicz Piotr

• Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland

autor

Kalinowska Małgorzata

• Department Rehabilitation, The Children's Memorial Health Institute, Warsaw, Poland

autor

Szczerbik Ewa

• Department Rehabilitation, The Children's Memorial Health Institute, Warsaw, Poland

Bibliografia

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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).