According to the American College of Sports Medicine (ACSM) [1] and the American Heart Association (AHA), strength training is beneficial to one’s health [2]. It has several advantages, including increased strength and beneficial changes in body composition [1]. According to the ACSM, gaining health and fitness benefits from resistance training requires at least one set of eight to twelve repetitions of each of eight to ten exercises involving the major muscle groups [3] on two or more days per week [4].

Previous research has explored the acute metabolic demands during strength exercise. Variables such as the muscle mass [5], exercise speed ^[6][7][8][6,7,8], number of sets ^[9][10][9,10], number of repetitions ^[11][12][11,12], workload ^[13][14][13,14], training volume [15], and rest intervals ^[11][16][17][11,16,17] resulted in substantially greater increases in oxygen consumption (VO₂) and energy expenditure (EE). Currently, oxygen consumption is commonly measured through indirect calorimetry, which has a stated accuracy of −2% to 4% [16]. However, acute physiological responses to skeletal muscle activation during moderate-strength exercises have not been thoroughly investigated.

Surface electromyography (EMG; sEMG), one of the most common methods of measuring muscle activation, is an electrophysiological recording technique for detecting the electric potential across muscle fiber membranes [17]. One recent researchtudy reported a relation between VO₂ and muscle activity for squats and heel raises with 80% of one repetition maximum (1RM) in healthy male participants and observed an increase in oxygen uptake after 6 weeks of resistance exercises [18]. Another researchtudy investigated the mean correlation between the surface EMG amplitude and oxygen uptake for lower extremity muscles as 0.69~0.87 during treadmill walking in young males [19].

To the best of our knowledge, no single researchstudy has found that oxygen consumption (VO₂) is related to the sEMG of the various upper limb and lower limb muscles during strength exercises at 60% of 1RM. It is an unexplored field of research to find which muscle sEMG has a significant association in computing oxygen consumption in healthy populations. By determining this kind of relationship, we can better explainingin which muscle activation can more or less predict VO₂. Some muscles are highly active during the shoulder press, deadlift, and squat, but we also observed other muscles which are not highly active during these strength workouts.

2. VO₂ Models of Three Training Sessions (Group Models)

VO₂ was predicted by the GEE model over the course of three training sessions but did not reach the level of significance. For the untrained group, right biceps femoris (RBFsEMG_rms) [p = 0.330; 95% CI = −0.532~1.586] predicted VO₂, and for the trained group, left middle deltoid (LMDsEMG_rms) [p = 0.058; 95% CI = −0.010~0.607] predicted VO₂ without attaining the level of significance. QIC values for the group models were 368 and 867 for the untrained and trained groups, respectively (Table 13).

3. Oxygen Consumption (VO₂) and Surface Electromyography (sEMG)

When utilizing GEE modeling to predict VO₂ for three strength training exercises, including the shoulder press, deadlift, and squat with dumbbells in young participants. For the group models, the right biceps femoris predicted model for VO₂ in the untrained group, while the left middle deltoid in the trained group without attaining the level of significance (Table 13). For the exercise models, the right and left middle deltoid, right and left biceps femoris, and left rectus femoris for the shoulder press, right and left lumbar erector spinae, and right biceps femoris for the deadlift and the right and left lumbar erector spinae, biceps femoris, and left middle deltoid for the squat significantly predicted the GEE models (Table 24a–c). No single previous researchtudy predicted VO2 by sEMG of individual muscles during moderate-intensity strength exercises. Because there is not a lot of studies on GEE modeling during strength training exercises, it is difficult to compare our computed models with previously available research. One researchstudy reported the association between VO₂ and sEMG RMS during cycling exercise and reported global sEMG measured from vastus lateralis muscle as a good predictor of energy expenditure in trained cyclists ^[20][32]. In some previous studies, one researchtudy reported the relation between VO₂ and sEMG responses of the anterior tibialis (TA), gastrocnemius medial (MG), gastrocnemius lateral (LG), and soleus muscles during different speeds of treadmill walking in young, healthy males; correlations between VO₂ and sEMG were 0.69~0.87 for those muscles [19]. Another researchtudy conducted on young males reported the effect of 6 weeks of strength training exercises and whole-body vibration on changes in normalized VO₂ and sEMG; they monitored the rectus femoris muscle during squats and lateral gastrocnemius during heel raises [18]. The main goal of the present research was to calculate GEE models for VO₂ in two categories (1) group and (2) exercise types. For the group models, none of the groups significantly predicted VO₂ from sEMG RMS of individual muscles, but for exercise type models, the shoulder press exercise showed significant relations of the right and left middle deltoid, right and left biceps femoris, and left rectus femoris with VO₂ for the untrained group [QIC = 102, * p = 0.000], while in the trained group, only the left rectus femoris [QIC = 82, * p = 0.000] were significantly correlated with the VO₂. Lower QIC and significant p-values for the trained group [QIC = 82 vs. 102 and * p = 0.000 vs. * 0.000] are suggestive of a better GEE model than that for the untrained group (Table 24a). For the deadlift and squat exercises, the untrained group models were more predictive than those of the trained group [QIC = 172 vs. 320 and * p = 0.000 vs. * 0.026] and [QIC = 76 vs. 348 and * p = 0.000 vs. * 0.001] (Table 24b,c) ^[21][22][29,31]. The reason why the correlations between the two groups differed lies in the fact that the untrained group participants had no previous experience of strength training, and their 60% 1RM was lower, so their muscle activation occurred differently than that in the trained group. Another factor that may have affected the results was the gender because the untrained group consisted mostly of female participants and trained group males. Table 24. Generalized estimating equations for oxygen consumption (VO₂; mL/min/kg) estimation for three training sessions (n = 11). (a) Shoulder Press. (b) Deadlift. (c) Squat.

(a)
Exercise	Group	Model	Parameter	Estimate (ß)	SE	95% CI (Lower~Upper)	p
Shoulder press	UTr	Model 1 (QIC 102)	Intercept	3.489	1.009	1.512~5.466	0.001
			LBF	sEMG-rms	−23.844	2.104	−27.967~−19.721	0.000 *
			RMD	sEMG-rms	0.942	0.204	0.543~1.341	0.000 *
			RBF	sEMG-rms	17.088	3.673	9.890~24.286	0.000 *
			LMD	sEMG-rms	−0.737	0.143	−1.016~−0.457	0.000 *
			LRF	sEMG-rms	−1.050	0.304	−1.646~−0.454	0.001 *
	Tr	Model 2 (QIC 82)	Intercept	5.727	0.271	5.195~6.259	0.000
			LRF	sEMG-rms	7.685	1.814	4.131~11.240	0.000 *
(b)
Exercise	Group	Model	Parameter	Estimate (ß)	SE	95% CI (Lower~Upper)	p
Deadlift	UTr	Model 3 (QIC 172)	Intercept	11.701	1.065	9.613~13.789	0.000
			RLES	sEMG-rms	9.366	1.425	6.573~12.159	0.000 *
			LLES	sEMG-rms	−10.428	2.030	−14.407~−6.448	0.000 *
			RBF	sEMG-rms	−2.086	0.459	−2.985~−1.186	0.000 *
	Tr	Model 4 (QIC 320)	Intercept	9.314	1.339	6.689~11.939	0.000
			LLES	sEMG-rms	3.362	1.506	0.411~6.313	0.026 *
(c)
Exercise	Group	Model	Parameter	Estimate (ß)	SE	95% CI (Lower~Upper)	p
Squat	UTr	Model 5 (QIC 76)	Intercept	10.328	0.875	8.612~12.043	0.000
			LBF	sEMG-rms	−11.262	0.538	−12.318~−10.207	0.000 *
			RLES	sEMG-rms	−3.318	0.514	−4.325~−2.312	0.000 *
			LLES	sEMG-rms	6.891	1.420	4.108~9.675	0.000 *
			LMD	sEMG-rms	0.653	0.126

UTr, untrained (n = 5); Tr, trained (n = 6). * Shows a significant difference p < 0.050. SE, standard error; 95% CI, confidence interval; QIC, quasi-likelihood under an independence model criterion; Root mean square surface electromyography (sEMG) of RMDsEMG-rms, right middle deltoid; LMDsEMG-rms, left middle deltoid; RLESsEMG-rms, right lumbar erector spinae; LLESsEMG-rms, left lumbar erector spinae; RBFsEMG-rms, right biceps femoris; LBFsEMG-rms, left biceps femoris; RRFsEMG-rms, right rectus femoris; LRFsEMG-rms, left rectus femoris. Pre vs. post static muscle strength is shown in Table 36. Some of the muscles’ strength increased after six training sessions, but out of the eight muscles, not a single one reached a significant level, because 2-week trainings are not enough to increase muscle strength as adaptation in strength would require about 12 or more weeks of consecutive trainings. The changes in the VO₂ and sEMG_rms after six trainings reported higher VO₂ values in both groups, particularly during the squat and deadlift exercises, which may have been due to the greater training loads of these exercises. Meanwhile, the sEMG_rms amplitude was higher for the bilateral middle deltoid during the shoulder press, because it is the major muscle group that is active during that exercise. In the deadlift, the right and left middle deltoid, lumbar erector spinae, and biceps femoris were more active than the rectus femoris, and only the bilateral deltoid and rectus femoris were active during squatting. Two-way repeated measures ANOVA for manual muscle strength (MMT) ( = 11).

Parameters	Untrained (n = 5)	Trained (n = 6)	p-Value
			Within Subject Pre vs. Post	Between Groups
0.406~0.901
0.000 *
RBF
sEMG-rms
1.758
0.391
0.992~2.524
0.000 *
Tr
Model 6
(QIC 348)
Intercept
10.781	0.758	9.295~12.266	0.000
LLES	sEMG-rms	0.494	0.155	0.191~0.797	0.001 *

Right Middle Deltoid	85.08 ± 22.01	156.28 ± 20.09	0.926	0.041 *
Left Middle Deltoid	85.49 ± 17.82	136.28 ± 16.27	0.951	0.065
Right Lumbar Erector Spinae	130.35 ± 23.14	212.27 ± 21.12	0.016 *	0.028 *
Left Lumbar Erector Spinae	134.93 ± 18.87	207.78 ± 17.23	0.017 *	0.019 *
Right Rectus Femoris	281.61 ± 34.25	426.36 ± 31.27	0.170	0.012 *
Left Rectus Femoris	283.40 ± 34.01	408.43 ± 31.04	0.085	0.024 *
Right Biceps Femoris	208.81 ± 19.06	249.48 ± 17.40	0.569	0.149
Left Biceps Femoris	181.45 ± 22.73	256.76 ± 20.75	0.950	0.037 *