The Evaluation of Shoulder Muscle Fatigue in Volleyball Players Łukasz Oleksy 1,2 , Wojciech Czarny 3 , Wojciech Bajorek 3 , Paweł Król 3 , Anna Mika 1* and Renata Kielnar 4 1 Department of Clinical Rehabilitation, University of Physical Education in Krakow, Poland 2 Oleksy Physiotherapy Clinic, Poland 3 Department of Physical Education, University of Rzeszów, Poland 4 Institute of Physiotherapy, Faculty of Medicine, University of Rzeszów, Poland * Corresponding author: Anna Mika, Department of Clinical Rehabilitation, University of Physical Education in Krakow, Al. Jana Pawla II 78, 31-571 Krakow, Poland, Tel: (4812)6831134; Fax. (4812) 6831300; E-mail: anna.mika@awf.krakow.pl Received date: March 08, 2018; Accepted date: April 10, 2018; Published date: April 17, 2018 Copyright: © 2018 Oleksy L, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract Objective: To identify the difference in infraspinatus, posterior deltoid, and teres minor muscle fatigability between the dominant and non-dominant side in elite volleyball players and to examine the differences between three sEMG signal processing methods used in assessment of shoulder muscle imbalance due to fatigue in volleyball players. Methods: In 18 male volleyball players (21-26 years; 186.6 ± 8.4 cm; 85.7 ± 9.8 kg) with no previous shoulder injury the bioelectrical activity of the right and left infraspinatus, posterior deltoid, and teres minor muscles was measured during 60 seconds of isometric contraction in prone position with the shoulder in external rotation. Fatigue related changes as mean frequency shift were calculated from the RAW sEMG signal using 3 processing methods: FFT (Fast Fourier Transform), STFT (Short Time Fourier Transform) and CWT (Morlet Continues Wavelet Transform). Results: There were no statistically significant differences (p>0.05) in the values of the mean frequency slope, intercept and difference between dominant and non-dominant sides in all the evaluated muscles. There were no significant differences between FFT and STFT sEMG signal processing methods in mean frequency slope, intercept values and difference. The sEMG signal processing using CWT showed the significantly higher values of mean frequency slope for infraspinatus and teres minor muscles. Significantly lower values of mean frequency intercept were observed for the infraspinatus, posterior deltoid and the teres minor muscles. There were no significant differences observed in mean frequency difference for all the evaluated muscles. Conclusions: In elite volleyball players without previous shoulder injury, the fatigue indices in muscles of the shoulder region were similar on both the dominant and non-dominant sides. Therefore, we have hypothesized that asymmetric shoulder loading during volleyball training should not be considered as an obvious factor increasing the risk of shoulder injury. Muscle fatigue indices measured by sEMG may be a sensitive and objective method of evaluation, but may reach different values depending on the used signal processing method. Consequently, the clinical interpretation and any comparison between different measurements, without knowledge of how those values were calculated, may be misleading and be the reason for misdiagnosis. Keywords: Volleyball; Muscle fatigue; sEMG; Shoulder injury Introduction Overhead sports such as volleyball are closely related to shoulder pain and strain injuries of the shoulder region [1,2]. Te specifcs of this discipline require the transfer of high energy through the shoulder in large ranges of motion and with high precision [1]. It was reported that repetitive movements during sport activities may lead to cumulative tissue loading, muscle fatigue and strain injuries [3,4]. It was demonstrated that during repetitive movements muscle fatigue may be accompanied by changes in movement patterns and by changes in joint proprioception [4,5]. Te alterations in proprioception due to fatigue are very important especially in sport activities where optimal movement patterns and appropriate motor control are required [5]. It was reported that changes in movement patterns due to muscle fatigue may contribute to acute or overuse injuries and to many musculoskeletal disorders, particularly in the shoulder region [3,6,7]. Tis process is especially devastating when including the postural and stabilizing muscles of the shoulder complex, specifcally, the rotator cuf muscles [7,8]. Studies have shown that altered position and motion of the scapula are considered as potential risk factors for shoulder pain and shoulder injury [2,4,8]. It was reported that scapular dyskinesis is observed in a 43% of overhead athletes and is infuenced by acute and chronic fatigue [1]. It has been reported that fatigue during exercise is accompanied by changes in electromyographic muscle activity [9-11]. Tis leads to an increase in signal amplitude and to a higher fatigue index [11,12]. Te sEMG signal analysis in muscle fatigue assessment usually includes changes in average sEMG amplitude and changes in sEMG spectral frequency [11-13]. Muscle fatigue is usually evaluated by sEMG signal spectral frequency analysis. But signal processing methods may be diferent even if the fnal parameters are the same J o u r n a l of N o v e l P h y s i o t h e r a p i e s ISSN: 2165-7025 Journal of Novel Physiotherapies Oleksy et al., J Nov Physiother 2018, 8:2 DOI: 10.4172/2165-7025.1000388 Research Article Open Access J Nov Physiother, an open access journal ISSN:2165-7025 Volume 8 • Issue 2 • 1000388