1 resultado para Complex biological systems
em Universidade Federal de Uberlândia
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Resumo:
Data variability analysis has been the focus of a number of studies seeking to capture differences of patterns generated by biological systems. Although several studies related to gait employ the analysis of variability in their observations, we noticed a lack of such information for subjects with unilateral coxarthrosis undergoing total hip arthroplasty (THA). To tackle this deficiency of information, we conducted a study of the gait on a treadmill with10 healthy subjects (30.7 ± 6.75 years old) from G1 and 24 subjects (65 ± 8.5 years old) with unilateral THA from G2. Thus, by means of two inertial measurement units (IMUs) positioned in the pelvis, we have developed a detection method of the step and stride for calculating these intervals and extract the signal characteristics. The variability analysis (coefficient of variation) was performed, taking into consideration the extracted features and the step and stride times. The average and the 95% confidence interval estimate for the average of the step and stride times to each group were in agreement with literature. The mean coefficient of variation for the step and stride times was calculated and compared among groups by the Kruskal-Wallis test with 95% confidence interval. Each component X, Y and Z of the two IMUs (accelerometer, magnetometer and gyroscope) corresponded to a variable. The resultants of each sensor, the linear velocity (accelerometers) and the instantaneous angular displacement (gyroscopes) completed the set of variables. The characteristics were extracted from the signals of these variables to check the variability in the G1 and G2 groups . There were significant differences (p <0.05) between G1 and G2 for the average of the step and stride times. The variability of the step and stride, as well as the variability of all other evaluated characteristics were higher for the group G2 (p <0.05). The method proposed in this study proved to be suitable for the measuring of variability of biomechanical parameters related to the extracted features. All the extracted features categorized the groups. The G2 group showed greater variability, so it is possible that the age and the pathological condition of the hip both contributed to this result.