Are incremental exercise relationships between rating of perceived exertion and oxygen uptake or heart rate reserve valid during steady-state exercises?

Background: Rating of perceived exertion (RPE) is considered a valid method for prescribing prolonged aerobic steady-state exercise (SSE) intensity due to its association with physiological indicators of exercise intensity, such as oxygen uptake (V̇O2) or heart rate (HR). However, these associations between psychological and physiological indicators of exercise intensity were found during graded exercise tests (GXT) but are currently used to prescribe SSE intensity even though the transferability and validity of the relationships found during GXT to SSE were not investigated. The present study aims to verify whether (a) RPE-HR or RPE-V̇O2 relations found during GXTs are valid during SSEs, and (b) the duration and intensity of SSE affect these relations. Methods: Eight healthy and physically active males (age 22.6 ± 1.2 years) were enrolled. On the first visit, pre-exercise (during 20 min standing) and maximal (during a GXT) HR and V̇O2 values were measured. Then, on separate days, participants performed 4 SSEs on the treadmill by running at 60% and 80% of the HR reserve (HRR) for 15 and 45 min (random order). Individual linear regressions between GXTs' RPE (dependent variable) and HRR and V̇O2 reserve (V̇O2R) values (computed as the difference between maximal and pre-exercise values) were used to predict the RPE associated with %HRR (RPEHRR) and %V̇O2R (RPEV̇O2R) during the SSEs. For each relation (RPE-%HRR and RPE-%V̇O2R), a three-way factorial repeated measures ANOVA (α = 0.05) was used to assess if RPE (dependent variable) was affected by exercise modality (i.e., RPE recorded during SSE [RPESSE] or GXT-predicted), duration (i.e., 15 or 45 min), and intensity (i.e., 60% or 80% of HRR). Results: The differences between RPESSE and GXT-predicted RPE, which were assessed by evaluating the effect of modality and its interactions with SSE intensity and duration, showed no significant differences between RPESSE and RPEHRR. However, when RPESSE was compared with RPEV̇O2R, although modality or its interactions with intensity were not significant, there was a significant (p = 0.020) interaction effect of modality and duration yielding a dissociation between changes of RPESSE and RPEV̇O2R over time. Indeed, RPESSE did not change significantly (p = 0.054) from SSE of 15 min (12.1 ± 2.0) to SSE of 45 min (13.5 ± 2.1), with a mean change of 1.4 ± 1.8, whereas RPEV̇O2R decreased significantly (p = 0.022) from SSE of 15 min (13.7 ± 3.2) to SSE of 45 min (12.4 ± 2.8), with a mean change of -1.3 ± 1.5. Conclusion: The transferability of the individual relationships between RPE and physiological parameters found during GXT to SSE should not be assumed as shown by the results of this study. Therefore, future studies modelling how the exercise prescription method used (e.g., RPE, HR, or V̇O2) and SSE characteristics (e.g., exercise intensity, duration, or modality) affect the relationships between RPE and physiological parameters are warranted.

Barbell load distribution and lifting velocity affect bench press exercise volume and perceived exertion.

OBJECTIVE: The intensity of barbell bench press exercise is generally prescribed as the load to be lifted for a specific number of repetitions; however, other factors (e.g., execution velocity) can affect bench press exercise intensity. Moreover, no study assessed whether load distribution (i.e., the distance between the disc stacks on the two sides of the barbell) affects exercise intensity. The present study aims to assess how different combinations of load, velocity, and barbell load distribution affect the number of repetitions to failure (REPfailure), and rating of perceived exertion (RPEfatigue) and number of repetitions (REPfatigue) at fatigue onset. METHODS: Ten males (age 23.3±1.8 years) performed bench press exercises to exhaustion using random combinations of three loads (50%, 65%, and 80% of 1 repetition maximum), three execution velocities (50%, 70%, and 90% of maximal concentric velocity), and two load distributions (narrow and wide). Three separate three-way repeated-measures ANOVAs were performed to assess the effect of load, velocity, and load distribution on REPfailure, RPEfatigue, and REPfatigue expressed as a percentage of REPfailure. RESULTS: REPfailure was affected by load (p<0.001), velocity (p<0.001), and distribution (p = 0.005). The interactions between load and velocity (p<0.001) and load and distribution (p = 0.004) showed a significant effect on REPfailure, whereas the interaction between velocity and distribution was not significant (p = 0.360). Overall, more REPfailure were performed using lower loads, higher velocities, and a wider distribution. RPEfatigue and REPfatigue were affected by load (p<0.001 and p = 0.007, respectively) and velocity (p<0.001 and p<0.001, respectively), and not by distribution (p = 0.510 and p = 0.571, respectively) or the two-way interaction effects. Overall, using higher loads yielded higher RPEfatigue but lower REPfatigue, while RPEfatigue and REPfatigue were higher when slower velocities were used. CONCLUSION: The current investigation shows that not only load but also velocity and barbell load distribution may influence bench press training volume and perceived exertion.