2015
DOI: 10.1177/2325967114566796
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Surface Electromyography of the Forearm Musculature During the Windmill Softball Pitch

Abstract: Background:Previous studies investigating the windmill softball pitch have focused primarily on shoulder musculature and function, collecting limited data on elbow and forearm musculature. Little information is available in the literature regarding the forearm. This study documents forearm muscle electromyographic (EMG) activity that has not been previously published.Purpose:Elbow and upper extremity overuse injuries are on the rise in fast-pitch softball pitchers. This study attempts to describe forearm muscl… Show more

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Cited by 17 publications
(19 citation statements)
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“…The most common approach to the analysis of sEMG signals is the assessment of the maximum or mean amplitude of the envelope, with or without normalisation to the maximum voluntary contraction [ 71 – 74 , 76 87 , 89 95 , 97 – 106 ]. The analysis of timing is also common in sport science, with usual approaches ranging from the detection of the onset and offset of sEMG activity and global and local maxima detection to examination of the entire time course using statistical parametric mapping [ 72 – 74 , 76 79 , 81 , 83 , 89 93 , 96 , 100 , 102 ]. Other advanced approaches include the analysis of the signal's frequency content, especially for fatigue estimation [ 79 , 106 ], classification of sEMG patterns through k -means clustering or support vector machines [ 82 , 88 ], and nonlinear analysis of the signals using the Lyapunov exponents [ 102 ].…”
Section: Resultsmentioning
confidence: 99%
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“…The most common approach to the analysis of sEMG signals is the assessment of the maximum or mean amplitude of the envelope, with or without normalisation to the maximum voluntary contraction [ 71 – 74 , 76 87 , 89 95 , 97 – 106 ]. The analysis of timing is also common in sport science, with usual approaches ranging from the detection of the onset and offset of sEMG activity and global and local maxima detection to examination of the entire time course using statistical parametric mapping [ 72 – 74 , 76 79 , 81 , 83 , 89 93 , 96 , 100 , 102 ]. Other advanced approaches include the analysis of the signal's frequency content, especially for fatigue estimation [ 79 , 106 ], classification of sEMG patterns through k -means clustering or support vector machines [ 82 , 88 ], and nonlinear analysis of the signals using the Lyapunov exponents [ 102 ].…”
Section: Resultsmentioning
confidence: 99%
“…The majority of the studies included the recordings of less than nine muscles [ 72 , 73 , 77 85 , 87 , 91 95 , 98 – 106 , 158 ], while only a few considered a number between nine and 16 [ 74 , 76 , 86 , 88 , 90 , 96 ] or bigger than 16 [ 71 , 97 ]. Most of the studies considered muscles of the lower limb [ 71 73 , 77 , 78 , 81 , 83 85 , 89 , 90 , 92 , 93 , 95 , 96 , 98 , 104 , 106 , 115 ], with the remaining focussing on the trunk and/or upper limb [ 74 , 76 , 80 , 82 , 87 , 94 , 100 , 102 , 103 , 106 ] or both the upper and lower body [ 79 , 86 , 88 , 91 , 97 , 99 , 101 ]. Bilateral recordings (involving the left and right hand side of the same muscles) were less common [ 71 , 74 , 77 , 82 , 86 , 88 , 90 , 97 , 98 , 101 ] than ipsilateral [ 72 , 7...…”
Section: Resultsmentioning
confidence: 99%
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“…The three primary softball pitches are the fastball, the rise ball, and the drop pitch. Each of these pitches requires slightly different planes of motion, patterns of muscular activation, and neuromuscular control to be executed effectively, especially in the upper extremity …”
Section: Introductionmentioning
confidence: 99%