Document Type : Original article
Authors
1
Department of Motor Behavior, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
2
Department of Motor Control, Faculty of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran.
3
Department of Knowledge and Cognitive Intelligence, Imam Hossein University, Tehran, Iran.
4
Department of Sport Management, Faculty of Physical Education and Sport Sciences, Central Branch of Islamic Azad University, Tehran, Iran.
10.32598/SJRM.13.5.1
Abstract
Background and Aims Due to the lack of mechanoreceptors in people with anterior cruciate ligament rupture (ACLR), sensory and motor neuroplasticity occurs, which causes abnormal and asymmetric motor control patterns in the lower limbs. Perturbation-based training can improve motor asymmetry and functional deficits in people with ACLR. In this study, we used a mechanical perturbation training to assess its effect on the cortico-muscular performance during walking in athletes with ACLR.
Methods Thirty athletes with unilateral ACLR were randomly assigned to two groups of perturbation-based and standard training. The training program of the two groups was done in three sessions every other day per week for one month. The surface electromyography and relative power analysis of alpha and beta waves in quantitative electroencephalography were performed during a walking task.
Results The perturbation-based training group showed a significantly higher muscle activity in both healthy and affected knees after increase in the similarity index (P=0.08, Cohen’s d=0.81), while there was no significant difference in the standard training group (P=0.39, Cohen’s d= 0.39). In cortical activity tests, the perturbation-based training group showed excellent symmetry in the relative power of alpha wave compared to the standard training group (P=0.94, Cohen’s d =0.02) and a good symmetry in the relative power of beta wave (P=0.24, Cohen’s d=0.26).
Conclusion The perturbation-based training is a more appropriate training for athletes with ACLR, probably due to having real-world challenges.
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