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Original Research

Mechanical Load and Physiological Responses of Four Different Resistance Training Methods in Bench Press Exercise

Buitrago, Sebastian1; Wirtz, Nicolas1; Yue, Zengyuan1; Kleinöder, Heinz1; Mester, Joachim1,2

Author Information
Journal of Strength and Conditioning Research: April 2013 - Volume 27 - Issue 4 - p 1091-1100
doi: 10.1519/JSC.0b013e318260ec77
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Resistance training plays an important role in the conditioning program required for most sports. In the last 2 decades, such training has also become prominent and popular among the general population for health and fitness. In addition to the main purposes of resistance training, its effects on muscle hypertrophy, the enhancement of muscular functional capacities, and energy balance and body weight management have also been focuses in research and practical exercise recommendations (7,16,17,29,36,40).

Acute physiological and metabolic responses to resistance exercise are caused by mechanical stimuli. Such stimuli are determined by numerous parameters that would distinguish different resistance training methods (RTMs). Several studies have investigated the effects of varying loads (2,3,14,19,24,26,34,39), contraction velocity (3,10,15,26), exercise volume (11), and rest interval length (12,22,30,38) on physiological responses during and after resistance exercise. These factors determine the generated power and performed work, simultaneously determining the energy demands of exercise.

Numerous investigations have studied the effects of resistance training parameters on oxygen uptake (V[Combining Dot Above]O2), energy expenditure rate, lactate concentration (LA), and excess postexercise oxygen consumption (EPOC) (3–5,11,12,14,19,24,27–29,34,40). However, from a practical point of view, there is no investigation that has measured mechanical variables of a wide range of established RTM and the corresponding physiological and metabolic responses. Hence, there is a lack of knowledge about the mechanical properties of the various RTM and their impact on particular muscular capacities and energy metabolism. The aim of this study was to fill this void, measuring and analyzing lifting performances with 4 practically applied RTM in regard to their mechanical load, exercise volume and physiological and metabolic responses. The examined variables of mechanical load, exercise volume, and energy metabolism were hypothesized to be different between the 4 RTMs, revealing differences in the mechanical impact and in the energy demands. It was considered that mechanical variables would result from the interaction between external load and contraction velocity. This may lead to similar values of particular mechanical variables between the various RTMs.

The results may establish a more precise description and characterization of the mechanical load and the energy demands of the examined RTM, allowing a more accurate specification of their impact on muscular capacities. Consequently, the effectiveness of future exercise method recommendations may be improved upon and an optimum RTM can be selected according to the exercising person's training goals and needs.


Experimental Approach to the Problem

On 4 different days, 1 of 4 randomly chosen bench press exercise protocols had to be performed by each subject. The bench press protocols were designed according to 4 commonly applied RTMs in regard to the external load and contraction velocity. During exercise, mechanical variables were measured at the weight stack of the bench press machine. To guarantee consistency of mechanical parameters between the repetitions of each RTM, an innovative visual feedback system was applied for the first time allowing the subjects to keep predetermined contraction velocity accurately constant. The best position for the visual feedback system was directly in front of the exercising individual. This was best accomplished using a sitting bench press machine. The sitting bench press was also selected based on its easy handling, safety reasons and for its common use in resistance training. Spirometric measures were taken to evaluate aerobic metabolism. Blood samples were taken for lactate analysis as an indicator for activation of anaerobic metabolism.


Ten healthy and resistance trained male subjects (age: 27.3 ± 3.2 years; height: 181.4 ± 4.8 cm; body mass: 81.4 ± 10.1 kg) participated in the investigation. All the participants had several years of resistance training experience with each of them practicing competitive sports in varying disciplines. The participants were informed about content, aims, and risks of the investigation, and they signed an informed consent document before any testing. The study was performed in accordance with the declaration of Helsinki, and it was approved by the Ethics Committee of the German Sport University Cologne.


In the spring, the participants reported to the laboratory on 5 separate days over a 3-week period between 7:00 and 10:00 AM; each participant started at the same time. Dietary habits throughout the testing period were to be maintained, but the participants were asked to appear for the test after an overnight fast. Only water was allowed to be consumed ad libitum, and the participants were instructed not to perform any physical activity the morning before the tests.

On day 1, all the participants were subjected to pretesting anthropometrical measurements. Body mass and body composition were determined via bioelectrical impendence analysis (Tanita corp., Tokyo, Japan). Afterward, the subjects were seated and were connected to an open-circuit-spirometry system. V[Combining Dot Above]O2 and V[Combining Dot Above]CO2 were measured for 30 minutes, and the data collected during the last 10 minutes were used to calculate basal metabolic rate (BMR). After respiratory measurements, the subjects were seated on a bench press machine (gym80 International GmbH, Gelsenkirchen, Germany). Machine settings were adjusted individually, so that all the subjects had the same starting and end positions during pretesting and during the experiment. For the starting position, the seat height was adjusted so that the hand grip of the machine was at the height of the sternum. The angle between shoulder blade and upper arm was 180° and the inner elbow angle was 90°. Ending position was defined by complete extension of the elbow. The range of motion (ROM) was measured by a distance-time sensor that was placed vertically between the upper weight plate of the weight stack and the frame of the strength machine. The sensor was connected to a PC and a visual feedback system (Digimax GmbH, Hamm, Germany) that recorded and saved each subject's ROM, defined as the vertical displacement of the weight stack during the lifting action. Subsequently, 1-repetition maximum (1RM) was determined using the testing protocol suggested and described by the American College of Sports Medicine (1).

On each of the other 4 remaining experimental days, the participants chose randomly 1 of 4 different lifting protocols on a sitting bench press. The 4 lifting protocols differ in load (% 1RM) and temporal distribution of the contraction modes per repetition and they were designed in accordance to the following RTMs: strength endurance (SE)—55% 1RM, 4/1/4/1 (4-second concentric, 1-second isometric, 4-second eccentric, 1-second isometric); fast force endurance (FFE)—55% 1RM, explosive/1/1/1; hypertrophy training (HYP)—70% 1RM, 2/1/2/1; maximum strength (MAX)—85% 1RM, explosive/1/1/1. Table 1 shows the description and characteristics of the 4 protocols. These RTMs are commonly applied to achieve a specific training outcome according to their description. The decision was made to perform merely 1 set of each protocol to rule out the effect of the length of the rest interval on the physiological and metabolic responses to the exercise (30). Furthermore, neither the number of repetitions nor the duration of exercise was limited for any RTM, because it was an intention to determine maximum possible work and exercise time. There were always at least 48 hours between 2 testing days for each participant.

Table 1:
Performance characteristics of the 4 resistance training methods.*

After randomly choosing 1 of the 4 RTMs, the participants were seated in the same bench press machine at which pretesting measurements and the 1RM tests were conducted and were connected to the open spirometry system. Five minutes after starting the gas analysis, a blood sample from the right ear lobe was collected to determine blood lactate concentration (LA) at rest. A brief warm-up session of 15 repetitions at 30% of 1RM was performed. Thereafter, the visual feedback tracking system was activated and subjects performed 15 repetitions without any external load for the purpose of familiarization with the movement velocity of the randomly selected RTM. The feedback system calculated and projected a tracking trace that moved according to the subject's ROM and the set time for concentric, isometric, and eccentric action. While executing concentric and eccentric actions, a tracking point in the display (controlled by the distance-velocity sensor) moved up and down, respectively. By moving the tracking point at the adjusted speed, the subjects followed the particularly calculated trace. Using this permanent direct visual feedback, the subjects were able to keep mean movement velocity constant during the complete ROM and the complete exercise bout. Figure 1 shows the setup of the testing equipment.

Figure 1:
Experimental equipment set: 1) Sitting bench press machine, 2) Visual feedback system, and 3) Spirometric device.

Before starting exercise, the subjects were instructed to exhale and inhale deeply during the concentric phase and eccentric phase, respectively. Thus, unintentional vasalva maneuvers and inadequate breathing were to be avoided, hence minimizing respiratory artifacts and guaranteeing accuracy of the gas analysis. During the SE, the participants were instructed to conduct 1 complete breathing cycle (exhalation and inhalation) during concentric action and during eccentric action, respectively, because of the long time of 4 seconds of each phase.

Ten minutes after beginning the spirometric measurement, the participants started to exercise. They were asked to maintain the effort until they failed to follow the tracking trace of the visual feedback system, because this would indicate that the participants were not able to sustain the given velocity and accordingly keep power constant. When exhaustion was evident, exercise was stopped and postexercise time started. Immediately after exercise, the HR was recorded, and capillary blood sample was taken. For a period of 30 minutes postexercise, the HR recording and blood sampling were repeated at intervals of 2 minutes. Spirometric measurements were also finished 30 minutes postexercise. Figure 2 shows the scheduled experimental protocol for 1 trial.

Figure 2:
Experimental protocol.

Measurements and Calculations

Mechanical force was measured by a dynamometer (Digimax GmbH, Hamm, Germany) placed between weight stack and pull cable of the strength machine. Time and distance were measured by the same sensor of the visual feedback system. Force, distance, and time were recorded at a rate of 100 Hz. Mean concentric power (P) and total concentric work (W) were calculated by a specific measuring system (Mechatronic GmbH, Hamm, Germany) and Extime was recorded.

Respiratory gas exchange measures were assessed via an open air spirometry system in breath-by-breath mode (ZAN 680 CPX, ZAN GmbH, Oberthulba, Germany) throughout the testing, using standard algorithms with dynamic account for the time delay between the gas consumption and volume signal. The respiratory gas exchange instrumentation was calibrated according to the manufacturer's guidelines with calibration gas. Mean V[Combining Dot Above]O2 and volume of consumed O2 were calculated during exercise and for the 30 minutes postexercise. The EPOC was determined by subtracting BMR averaged over 30 minutes from consumed O2 postexercise. Blood samples were analyzed for LA with an enzymatic–amperometric analyzer (Ebio plus, Eppendorf AG, Hamburg, Germany). The highest LA was defined as postexercise maximum lactate concentration (LAmax).

Statistical Analyses

Data were summarized as group means and SDs. All data were analyzed by using repeated measures analysis of variance comparing differences between the 4 RTMs for each variable. The alpha level for significance was set to be p ≤ 0.05 to identify significant differences. When significance was found, Greenhouse-Geisser–-Huynh-Feldt adjustment was performed to reduce the probability of making type 1 error. When the significance was further confirmed by the Greenhouse-Geisser–Huynh-Feldt adjustment, post hoc comparisons were made between the different RTMs by the use of Tukey honestly significant difference Test. The Statistica software package for Windows version 7.1 (StatSoft Inc., Tulsa, OK, USA) was used for all statistical analyses.


The comparison of the measured variables among the 4 RTMs is shown in Figures 3–8, respectively. Figure 3 shows the comparison of P where the results for FFE and MAX (292.0 ± 82.1 and 260.5 ± 93.5 W) were significantly higher (p < 0.01) compared with SE and HYP (39.7 ± 8.2 and 89.7 ± 13.0 W). No significant differences were detected between FFE and MAX and between SE and HYP. Figure 4 shows the comparison between W performed where the results for FFE (5,142.2 ± 1,348.6 J) were significantly higher (p < 0.01) than for SE, HYP, and MAX (1,725.6 ± 734.9, 2,239.0 ± 835.3, and 2,599.2 ± 1,317.3 J, respectively). The W was also lower for SE than for MAX (p < 0.05). No significant differences were observed between SE and HYP, and between HYP and MAX.

Figure 3:
Differences in P between the 4 resistance training methods (RTMs). **p < 0.01. Data presented are the mean ± SD.
Figure 4:
Differences in W between the 4 resistance training methods (RTMs). *p < 0.05, **p < 0.01. Data presented are the mean ± SD.
Figure 5:
Differences in EXTIME between the 4 resistance training methods (RTMs). **p < 0.01. Data presented are the mean ± SD.
Figure 6:
Differences in V[Combining Dot Above]O2 between the 4 resistance training methods (RTMs). **p < 0.01. Data presented are the mean ± SD.
Figure 7:
Differences in O2 consumed between the 4 resistance training methods (RTMs). *p < 0.05, **p < 0.01. Data presented are the mean ± SD.
Figure 8:
Differences in LAmax between the 4 resistance training methods (RTMs). *p < 0.05. Data presented are the mean ± SD.

Figure 5 shows the comparison of EXTIME where the result for SE (104.9 ± 23.7 seconds) was significantly higher (p < 0.01) than for all other RTMs. The result for MAX (29.2 ± 7.8 seconds) was significantly lower (p < 0.01) than for all other RTMs. There was no difference in EXTIME between FFE and HYP (64.8 ± 13.0 and 62.9 ± 8.2 seconds, respectively). Figure 6 shows the comparison of mean V[Combining Dot Above]O2 during exercise where the result for FFEs (923.6 ± 170.6 ml·min−1) was significantly higher than for all other RTMs (p < 0.01). No differences were observed among the other RTMs.

Figure 7 shows the comparison of the volume of consumed O2 during exercise where the result for MAX (240.5 ± 92.9 ml) was significantly lower than the other RTM (p < 0.05 to HYP, and p < 0.01 to SE and FFE). Furthermore, the result was significantly higher for SE than at HYP (849.8 ± 441.6 vs. 529.1 ± 181.2 ml, p < 0.05). No significant differences were observed between FFE (729.9 ± 219.6 ml) and SE or HYP. Figure 8 shows the comparison of LAmax, where the result after FFE was significantly higher than after MAX (5.1 ± 1.3 vs. 4.1 ± 1.5 mmol·L−1, p < 0.05). No further significant differences were detected neither for SE (4.7 ± 1.0 mmol·L−1) nor for HYP (4.9 ± 1.0 mmol·L−1). No significant differences in EPOC were detected among the 4 RTMs.


To the authors' knowledge, this is the first investigation applying online dynamometric measurement of mechanical variables during resistance exercise in a nonisokinetic machine. This method enables an accurate analysis of the mechanical load of resistance exercise. Also, a novelty is the use of the visual feedback that allows the tracking and the control of movement velocity over the total ROM more accurately when compared with other systems used in previous investigations. The combination of both systems allows a precise description of the mechanical impact of the examined exercise protocols. In addition to the respiratory and metabolic data, this approach provides new, more profound information about the mechanophysiological characteristics regarding the exercise stimuli underlying the different RTMs.

The results show that more power is generated for RTM with maximum possible velocity than those with restricted velocity. Furthermore, as the highest P was achieved during FFE, the present results are in agreement with those of other studies revealing that the maximum power for upper body exercise is generated at external loads between 30 and 60% of 1RM (21,33). This supports the suggestions that low load—explosive exercise should be used for power development and corresponding adaptations (20) although the broad range of 30–60% is not adequate for precise planning of load. Conversely, the lack of significant difference in P between FFE and MAX also supports the controversial opinion suggesting high load training (>80% 1RM) to generate optimal power production (20).

Generally, the volume of resistance exercise, for research or training purposes, is predefined by the number of sets and repetitions following common and fundamental suggestions in exercise prescription (23). Also, in several studies comparing the physiological responses of resistance exercise protocols with different loads, number of sets and repetitions were chosen to achieve an equal amount of work between protocols (22,24,28,31,34,39). In contrast, in the present investigation, the number of repetitions was not limited to ascertain the maximum amount of work and exercise time that can be achieved with each of the 4 RTMs. The present results show that the highest amount of W was performed during FFE compared with that during the other RTMs. Considering that energy is related to the ability to perform work, it can be consequently concluded that FFE elicits the highest energy cost compared with the other RTMs. However, despite this relation, it is not possible to quantify the energy expenditure based on mechanical work. Additionally, it does not yield any information about the contribution of aerobic and anaerobic metabolism to total energy supply.

The power produced is a main criterion in determining the intensity of an exercise. Generally, it is considered that with increasing intensity, that is, power, the maximum amount of performable work decreases, and vice versa. The present findings demonstrate that this relationship is not valid in resistance exercise as highest P and W among the 5 RTMs were achieved with FFE. In contrast to W, longest EXTIME was recorded during SE. These results are similar to those of Gentil et al. (10) and Koegh et al. (21) who also reported significantly higher EXTIME during super slow resistance exercise compared with other RTMs. However, time for concentric and eccentric phase was set at 60 and 5 seconds, respectively. The present data indicate that SE, for example, the combination of low load and low movement velocity, enables a high EXTIME. An increase of load or velocity causes a reduction of EXTIME as shown by FFE and HYP. Consequently, the lowest EXTIME was reached at MAX, where the highest load had to be lifted explosively. In the present investigation, EXTIME is equal to the time under tension until failure. This variable has been identified and described as a mechanobiological descriptor of resistance exercise stimuli affecting muscle-unit recruitment dynamics (35). Thus, different times under tension imply different metabolic changes inducing different metabolic and structural adaptations of the muscle fiber. In this study, the longest EXTIME was elicited by the SE method. Accordingly, muscular capability of the oxidative metabolism was more pronouncedly challenged than in the other RTM, suggesting that SE is appropriate to improve muscular aerobic capacity.

In comparison to maximum strength or power training, muscle hypertrophy training is characterized by a lower external load, a lower lifting velocity and a higher exercise training volume due to a higher number of repetitions and sets. In respect to exercise volume as determined by performed work, there is no difference between HYP and MAX. In contrast, EXTIME is significantly higher at HYP suggesting that not mechanical work but longer exercise duration and the elicited physiological and metabolic responses are the signals for an amplified muscle hypertrophy.

The present findings show that the RTM with the lowest load and highest movement velocity elicits the highest response in mean V[Combining Dot Above]O2 among all 4 examined RTMs. With regard to load, this result confirms those of Mazzetti et al. (26) reporting higher V[Combining Dot Above]O2 during resistance exercise with 60% 1RM than with 80% 1RM. The fact that SE elicits a significantly lower V[Combining Dot Above]O2 than FFE despite the equal external load indicates that the movement velocity also affects the V[Combining Dot Above]O2 response. Hunter et al. (15) also reported significantly lower mean V[Combining Dot Above]O2 during a super slow method than during traditional training, whereas external load was also different (25 vs. 60% 1RM). Mazzetti et al. (26) also presented a significantly lower V[Combining Dot Above]O2 during exercise of slower contraction velocity. Furthermore, these antipodal effects of load and velocity on V[Combining Dot Above]O2 response explain the similar values in mean V[Combining Dot Above]O2 between SE, HYP, and MAX.

Despite similar P between FFE and MAX, V[Combining Dot Above]O2 is significantly lower during MAX. A possible explanation is that despite the encouragement to inhale and exhale accentually, some vasalva maneuvers occurred unintentionally especially while lifting heavier weights at HYP and MAX leading to a reduction of venous blood flow to the heart and of stroke volume (25). Also, during heavy-resistance exercise, peripheral arterial vessels of working muscles are compressed, which causes a reduction in muscle perfusion and impairment in gas exchange (9,13). Both mechanisms will impede the enhancement of V[Combining Dot Above]O2 to a level that reflects the actual energy needs of the correspondent power output.

V[Combining Dot Above]O2 response for HYP and MAX could be explained further by the size principle of motor recruitment (35). This predicts that the activation of larger motor units and type 2 muscle fibers is amplified with increasing force demands, whereas at low force, primarily type 1 fibers will be active. Thus, the slower V[Combining Dot Above]O2 -kinetics of type 2 fibers (compared with type 1 fibers) and the reduced EXTIME result in a lower mean V[Combining Dot Above]O2 and V[Combining Dot Above]O2peak while exercising with increasing external load. Hence, it can be concluded that in contrast to aerobic exercise, differences in aerobic energy supply during resistance exercise are not reflected by V[Combining Dot Above]O2 while exercising with higher loads. The differences in P and V[Combining Dot Above]O2 -response between SE and FFE result from the different contraction velocity, which also implies different muscle fiber recruitment patterns. An additional activation of type 2 fibers at FFE and a decreasing efficiency of type 1 fibers at higher contraction velocities has been shown to elevate V[Combining Dot Above]O2 (8).

With increasing load during resistance exercise, energy needs are covered by increased activation of anaerobic metabolism. Consequently, in this case, the volume of consumed O2—the indicator of energy supplied by aerobic metabolic pathway—during exercise does not reflect the amount of work performed. The results of this study confirm those presented by Kalb and Hunter (18) and by Ratamess et al. (30). They reported that consumed O2 augmented significantly with decreased external load. Additionally, EXTIME was found to be increased with decreasing loads in these studies. This indicates that EXTIME also has ramifications on consumed O2. Hunter et al. (15) found opposite results comparing super slow resistance exercise (10-second concentric − 5-second eccentric) at 25% 1RM with traditional resistance exercise protocol at 65% 1RM. Consumed O2 was significantly higher during traditional resistance exercise with the higher load, but in contrast to the findings of Kalb and Hunter (18), Ratamess et al. (30), and the present investigation, exercise time of both protocols was matched. The limited exercise time of the super slow–low load exercise could have impeded the augmentation of consumed O2. This conclusion would be in agreement with the statement of Ratamess et al. (30) that total energy expenditure is affected by protocol duration. Consequently, it can be assumed that the significant differences in consumed O2 between SE, HYP, and MAX result from the significantly longer EXTIME of SE. The significantly longer EXTIME of SE could also have been the cause for the similar values of consumed O2 between SE and FFE despite the higher V[Combining Dot Above]O2 during FFE.

In this study, no differences in EPOC were detected among all 4 RTMs. These results are in agreement with those of Ratamess et al. (30) and of Olds and Abernethy (28). The EPOC reflects the level of energy supplied by anaerobic metabolism in previous exercise. Its magnitude is affected by exercise intensity and exercise volume where the effect of intensity seems to be more strenuous (6). These findings are confirmed by the results of Thornton and Potteiger (34). They have shown that resistance exercise of higher load but equal work elicits a higher EPOC response. Hunter et al. (15) also reported a higher EPOC after traditional exercise of higher load and work compared with a super slow protocol of lower load and less work but equal exercise time. Considering that RTM in this study were not matched for work and duration, the underlying metabolism of the performed work and exercise time are responsible for the similar EPOC values. During resistance exercise, the glycolytic rate is supposed to be enhanced when external load is increased. In contrast, when external load is reduced the contribution of glycolytic rate to energy supply decreases. However, due to the longer EXTIME of lower load exercise the oxygen deficit could be as high as during higher load exercise with shorter EXTIME. This could explain the similar values in EPOC throughout the examined RTM.

In this investigation, significant difference in postexercise blood LAmax was only detected between FFE and MAX despite the differences in external load, EXTIME, P, and W among all examined RTMs. These results confirm those of other studies reporting higher blood or plasma LA after exercise protocols at lower loads (14,19,22,26). They are also consistent with others finding no significant difference in blood LA after resistance exercise of different external loads (10,21,22,32). Koegh et al. (21) reported no significant difference in postexercise LAmax between 1 set with a 6RM load (comparable with MAX of this study) and a super slow protocol (5 seconds for concentric and eccentric actions, 55% 1RM) using bench press exercise. Gentil et al. (10) also found no significant difference in LAmax after 1 super slow repetition (30-second concentric and eccentric) and 1 set with a 10RM load (comparable with HYP of this study) of leg extension exercise. In contrast to the present findings, Koegh et al. (21) measured significantly lower postexercise LAmax after 6 repetitions of maximal power training (30% 1RM, explosive) and the 6RM protocol. Using heavier loads enhances the recruitment of glycolytic type 2 muscle fibers (37), causing an increased contribution of anaerobic metabolism to energy needs. In contrast to this mechanism, this investigation and several studies previously mentioned did not find higher LAmax after resistance exercise protocols of higher load and power. The use of heavy loads is accompanied by a reduced exercise time and performed work. If the number of repetitions or the exercise time is not restricted, longer exercise time and a higher amount of work can be achieved by exercising with lower loads. The LA is the difference between lactate influx into the bloodstream, and its reuptake by muscles and other organs and tissues. Blood lactate accumulation increases as long as lactate influx is higher than its efflux, leading to an augmented blood LA. Hence, despite a lower lactate production rate, SE and FFE could yield a similar or higher blood LAmax compared with HYP and MAX because of the longer time the exercise could be sustained and lactate could accumulate. This assumption is supported by the results of Lagally et al. (24) and Thornton and Potteiger (34). In contrast, they reported higher LA after a protocol of higher load and higher power but equal work. Hunter et al. (15) presented similar results, but in their study, total work was also higher for the high load protocol, whereas duration of exercise was matched. Their results indicate that higher blood lactate accumulation—because of higher glycolytic activity—could not be reached with lower load exercise when work and exercise time were limited.

Practical Applications

The results achieved enable the characterization of the mechanical impact and the energy demands of the 4 RTMs. Based on these data, the selection of an adequate RTM to improve particular muscular capacities can be made more accurately. It has to be considered that the benefits of the RTMs described in this work are only valid if the RTMs are performed until exhaustion, for example, with no restriction of time and repetitions. Because the highest concentric power was produced for the RTMs executed with highest possible velocity MAX and FFE should be applied for the development of muscular power. Because the highest work volume was performed at FFE, the highest amount of energy expenditure may be achieved by exercising FFE. Furthermore, FFE can be characterized as the training method eliciting the highest energy turnover covered by oxidative pathways. Because of the additional recruitment of the glycolytic muscle fibers, FFE seems to be also appropriate for improving anaerobic endurance capacities. The high exercise time and the resulting high volume of consumed O2 affirm SE to be also an adequate method to train muscular aerobic endurance. If resistance exercise is used to obtain the maximum possible energy expenditure, it is advisable to use FFE or SE until exhaustion. Concerning the enhancement of energy expenditure and weight management, an elevated and longer lasting EPOC has been described as 1 benefit of resistance exercise compared with aerobic endurance exercise. Consequently, if the metabolic rate after exercise is considered as a criterion for exercise selection, all 4 investigated RTMs can be equally recommended. For beginners of resistance training or in rehabilitation training after injury, SE might be a more appropriate training method to initiate the development of basic muscular capacities because of the slow and controlled movement and its low mechanical impact. Because the high load at HYP and MAX work and exercise time are too low to induce a high energy expenditure compared with SE and FFE. However, HYP and MAX do benefit energy metabolism. An increase in muscle mass as a result of training with submaximum loads enhances BMR supporting energy balance.


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resistance exercise; mechanical work; mechanical power; energy metabolism

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