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Effect of kinesiotaping following training inducing ankle stabilisers fatigue on balance and weight bearing ankle dorsiflexion range of motion in male football players

Puszczałowska-Lizis Ewa, Szymański Dominik, Krawiec Klaudia, Lizis Sabina

Acta of Bioengineering and Biomechanics

2025

Vol. 27, no. 1

25--32

This study investigated whether kinesiotaping applied to the ankle joint after exercise causing fatigue of the muscles stabilising this joint has an effect on the ability to maintain static balance, dynamic balance and weight-bearing ankle dorsiflexion range of motion in male football players without ankle pain and instability. Methods: The study included 50 men aged 18–30 years, practising football, assigned to the study group (subjected to kinesiotaping for the ankle joint) or the control group (without kinesiotaping). Exam 1st was performed prior to a 20- minute physical exercise causing fatigue of the muscles stabilising the ankle joint. Kinesiotaping was then applied in the study group. Exam 2nd was performed after exercise. Research tools were the Flamingo Balance Test (FBT), the Y-Balance Test (YBT) and Ankle Lunge Test (ALT). The data were analyzed based on Student’s t-test for independent variables, Mann–Whitney U-test, Student’s t-test for dependent variables, Wilcoxon test. Results: In the case of FBT, the values of the differences in 1st and 2nd examination results did not yield statistically significant results (p > 0.05), and for YBT and ALT, the values for the differences between 1st and 2nd examination in the study group were greater than in the control group (p < 0.05). Conclusions: Kinesiotaping applied to the ankle joint after exercise causing fatigue of the muscles stabilising this joint has a beneficial effect on the ability to maintain dynamic balance and weight-bearing ankle dorsiflexion range of motion, whereas it does not significantly improve static balance in male football players without ankle pain and instability.

Application of Basic Machine-Learning Classifiers for Automatic Anomaly Detection in Shewhart Control Charts

Woźniak Aleksander, Krawiec Klaudia, Książek Roger

Decision Making in Manufacturing and Services

2024

Vol. 18

83--98

In today’s dynamic technological environment, innovation plays a crucial role – especially for manufacturing enterprises that constantly strive to improve the quality of their products. This article examines the quality-management issue in a company producing car rims. It was identified that real-time quality control can sometimes be unreliable due to controller fatigue, leading to erroneous data interpretation or delayed responses to deviations in the production process. The study aimed to investigate the possibility of eliminating or significantly reducing these errors by employing a tool that is based on artificial intelligence. The article covers the preparation of training data, the training of classifiers, and the evaluation of their effectiveness in analyzing control charts in real time. The adopted hypothesis assumes that machine-learning classifiers can be effective methods of support for quality controllers. The research began with collecting measurement data from the machine and dividing it into training and test sets. The obtained results were evaluated using standard quality measures for machine-learning models. The results showed that the use of artificial intelligence can bring significant benefits in improving quality supervision in the production process of car rims.