The aim of the research was to determine the energy changes during the gait cycle for a group of healthy children and a group of patients with cerebral palsy, and to compare the value of energy expenditure (EE) with the determined values of the Gillette Gait Index (GGI) and the Gait Deviation Index (GDI). Methods: The study group consisted of 56 children with regular gait and 56 patients with diagnosed cerebral palsy (CP). The gait kinematics was determined by BTS Smart System. Based on the identified position of the body mass, the following parameters were determined: the potential energy, kinetic energy, and total energy. The values were standardized to 100% of the gait cycle. The values of the Gillette Gait Index (GGI) and the Gait Deviation Index (GDI) were calculated using the authors’ own software. Results: Values of potential, kinematic and mechanical energy changes and mean values of total energy (energy expenditure – EE) were calculated for a reference group and for patients with CP. The obtained results were standardized in relation to the body mass and stride length. Furthermore, the values of the Gillette Gait Index (GGI) and the Gait Deviation Index (GDI) were calculated. Statistical analysis of the obtained results was performed. The Spearman rank correlation coefficient was defined between the calculated GGI and GDI values and energy expenditure EE. Conclusions: Values of energy expenditure changes can be used as an objective comparative tool for gait results concerning children with various neurological and orthopaedic dysfunctions.
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Autorzy prezentują wyniki badań nad analizą nieprawidłowości w sposobie poruszania się na podstawie danych chodu uzyskanych za pomocą techniki motion capture. Badaniu poddano 3 grupy pacjentów: ze zwyrodnieniami stawu biodrowego, kręgosłupa i po udarze mózgu oraz grupę osób zdrowych. Sekwencje chodu nagrywano w dwóch sesjach – przed i po trzytygodniowym okresie rehabilitacji. Jako wskaźników nieprawidłowości użyto indeksów chodu.
EN
The authors present results of the research aiming at analysis of gait abnormalities based on the gait motion capture data. Three groups of patients suffering from the following affections: osteoarthritis of the hip, osteoarthritis of the spine and stroke underwent the recording process twice – before and after three-week rehabilitation. Healthy volunteers were also recorded. Gait indices were used as indicators of abnormality.
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