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Multivariate linear regression analysis to evaluate multiple-set performance in active and inactive individuals

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DataCite Commons2020-08-27 更新2024-07-27 收录
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Abstract Aim: To determine how EMG, anthropometric, and psychological factors, and physical activity levels affect isokinetic peak torque performance (IPT) of multiple set exercise sessions. Methods: 20 participants (27±7 years old), classified as active (A=10) and inactive (I=10), performed 10x10:40secs of maximal unilateral knee flexions and extensions at 120o.s-1. The IPT, EMG, glucose, LDH, and lactate concentrations and perceptions of pain, effort, recovery. Results: Active volunteers showed higher muscularity (52±5 vs 47±4 cm; p<0.05), PTI (262±4 vs 185±4 Nm; p<0.05), relative lower drop in performance (14±2 vs 27±3% ; p<0.05), major MDF (83±1 vs 76±1 Hz; p<0.05), lower log -Fins5 (-12.9±0.3 vs -12.7 ± 0.3 Hz; p<0.05), smaller subjective perception of effort (14.8±0.3 vs 17.0±0.3) and higher subjective perception of recovery (14.2±0.2 vs 12.3±0.3). There was a significant interaction between relative fatigue and the number of sets (F=6.18; p<0.001). Stepwise multiple regressions revealed that subjective perception of recovery best explained the fatigue level generated in the active volunteers [fatigue level= 85.084-5255(SPR)] while for body mass was the best determinant for the inactive group [fatigue level = -21.560 +1.828(BMI)]. Conclusion: Data from the present analysis suggest that physically active individuals show higher torque development and a smaller fatigability index when compared to inactive individuals. Among the fatigue models studied, it is possible that alterations in biochemical components, psychophysiological and EMG are not sensitive to the direct influence of the fatigue dynamics protocol, both in active or inactive individuals.
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SciELO journals
创建时间:
2019-05-08
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