摘要

Oxygen consumption (VO2) during strength training can be predicted through surface electromyography (sEMG) of local muscles. This research aimed to determine relations between VO2 and sEMG of upper and lower body muscles to predict VO2 from sEMG during moderate-intensity strength training exercises. Of the 12 participants recruited, 11 were divided into two groups: untrained (n = 5; with no training experience) and trained (n = 6; with 2 months of training experience). On different days, each individual completed six training sessions. Each participant performed training sessions consisting of three types of dumbbell exercises: shoulder press, deadlift, and squat, while wearing a mask for indirect calorimetric measurements of VO2 using the Cortex Metalyzer 3B. sEMG measurements of the bilateral middle deltoid, lumbar erector spinae, quadriceps (rectus femoris), and hamstring (biceps femoris) muscles were recorded. The VO2 was predicted from sEMG root mean square (RMS) values of the investigated muscles during the exercise period using generalized estimating equation (GEE) modeling. The predicted models for the three types of exercises for the untrained vs. trained groups were shoulder press [QIC = 102, * p = 0.000 vs. QIC = 82, * p = 0.000], deadlift [QIC = 172, * p = 0.000 vs. QIC = 320, * p = 0.026], and squat [QIC = 76, * p = 0.000 vs. QIC = 348, * p = 0.001], respectively. It was observed that untrained vs. trained groups predicted GEE models [quasi-likelihood under an independence model criterion (QIC) = 368, p = 0.330 vs. QIC = 837, p = 0.058], respectively. The study obtained significant VO2 prediction models during shoulder press, deadlift, and squat exercises using the right and left middle deltoid, right and left lumbar erector spinae, left rectus femoris, and right and left biceps femoris sEMG RMS for the untrained and trained groups during moderate-intensity strength training exercises.

原文英語
文章編號2233
期刊International journal of environmental research and public health
19
發行號4
DOIs
出版狀態已發佈 - 2月 16 2022

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