Gait patterns of hemiplegia patients have many potential applications such as assistance in diagnosis or clinical decision-making. Many techniques were developed to classify gait patterns in past years; however, these methods have some limitations. The main goal of the study was to present the performance evaluation results of the new biclustering algorithm called KMB. The second objective was to compare clustering and biclustering methods. The study was performed based on the gait patterns of 41 hemiplegia patients over 12 months post-stroke, at the age of 48.6 ± 19.6 years. Spatial–temporal gait parameters and joint moments were measured using motion capture system and force plates. Clustering and biclustering algorithms were applied for data consisting of joint moments of lower limbs. The obtained results of this study based on joint moments, clustering, and biclustering can be applied to evaluate patient condition and treatment effectiveness. We suggest that the biclustering algorithm compared to clustering algorithms better characterizes the specific traits and abnormalities of the joint moments, especially in case of hemiplegia patients.
Celem pracy była analiza chodu osób z porażeniem połowiczym po udarze mózgu. Dokonano porównania wybranych parametrów lokomocji osób z porażeniem do chodu osób zdrowych, a także kończyny po stronie porażonej i nieporażonej. Analizie poddano 10 osób, w tym 4 kobiety i 6 mężczyzn. Wyniki badań przedstawiono na tle rezultatów chodu z naturalną prędkością młodych, zdrowych osób, stanowiących grupę porównawczą.
EN
The aim of this paper was to analyse the gait of people after stroke with hemiplegia and make comparision with the health people’s walk. Gait parameters obtained for paralyzed limb were compared with those obtainted for health one. Ten people after strokes with hemiplegia, including 4 women and 6 men, were taken into consederation. The results were presented on the background of the walk of the young, health people who were the reference group.
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