Prediction of Maximal or Peak Oxygen Uptake from Ratings of Perceived Exertion

Abstract

Maximal or peak oxygen uptake (V˙O2 max and V˙O2 peak , respectively) are commonly measured during graded exercise tests (GXTs) to assess cardiorespiratory fitness (CRF), to prescribe exercise intensity and/or to evaluate the effects of training. However, direct measurement of CRF requires a GXT to volitional exhaustion, which may not always be well accepted by athletes or which should be avoided in some clinical populations. Consequently, numerous studies have proposed various sub-maximal exercise tests to predict V˙O2 max or V˙O2 peak . Because of the strong link between ratings of perceived exertion (RPE) and oxygen uptake (V˙O2), it has been proposed that the individual relationship between RPE and V˙O2 (RPE:V˙O2) can be used to predict V˙O2 max (or V˙O2 peak) from data measured during submaximal exercise tests. To predict V˙O2 max or V˙O2 peak from these linear regressions, two procedures may be identified: an estimation procedure or a production procedure. The estimation procedure is a passive process in which the individual is typically asked to rate how hard an exercise bout feels according to the RPE scale during each stage of a submaximal GXT. The production procedure is an active process in which the individual is asked to self-regulate and maintain an exercise intensity corresponding to a prescribed RPE. This procedure is referred to as a perceptually regulated exercise test (PRET). Recently, prediction of V˙O2max or V˙O2 peak from RPE:V˙O2 measured during both GXT and PRET has received growing interest. A number of studies have tested the validity, reliability and sensitivity of predicted V˙O2 max or V˙O2 peak from RPE:V˙O2 extrapolated to the theoretical V˙O2 max at RPE20 (or RPE19). This review summarizes studies that have used this predictive method during submaximal estimation or production procedures in various populations (i.e., sedentary individuals, athletes and pathological populations). The accuracy of the methods is discussed according to the RPE:V˙O2 range used to plot the linear regression (e.g., RPE9–13 versus RPE9–15 versus RPE9–17 during PRET), as well as the perceptual endpoint used for the extrapolation (i.e., RPE19 and RPE20). The V˙O2 max or V˙O2 peak predictions from RPE:V˙O2 are also compared with heart rate-related predictive methods. This review suggests that V˙O2 max (or V˙O2 peak ) may be predicted from RPE:V˙O2 extrapolated to the theoretical V˙O2 max (or V˙O2 peak) at RPE20 (or RPE19). However, it is generally preferable to (1) extrapolate RPE:V ˙ O 2 to RPE19 (rather than RPE20); (2) use wider RPE ranges (e.g. RPE ≤ 17 or RPE9–17) in order to increase the accuracy of the predictions; and (3) use RPE ≤ 15 or RPE9–15 in order to reduce the risk of cardiovascular complications in clinical populations.

Monitoring Training Loads: The Past, the Present, and the Future

“…Given that the HR response can be disrupted, and has technological requirements, it may be that using RPE during standard warm-up activities is an even more simple approach, as it has already been shown to be a useful strategy for predicting VO 2 max. 43 Just as sRPE has been shown to be a useful method for tracking the intensity of exercise, the process of systematically asking the athlete "how do you feel" holds the potential for monitoring the response to training. Steven Seiler has related the "hair in the cereal" story of observing athlete behavior at the breakfast table.…”

Are first ventilatory threshold and 6-minute walk test heart rate interchangeable? A pilot study in healthy elderlies and cardiac patients

“…Thus, in the meta-analysis by Chen et al among healthy subjects [36], RPE was found to be significantly correlated with several physiological parameters usually considered in the determination of the first VT such as VO 2 (r = 0.63), ventilation (r = 0.61) and blood lactate levels (r = 0.57). A more recent review performed by Coquart et al [37] concluded that the individual relationship between RPE and VO 2 (RPE/VO 2 ) can be used to predict VO 2 max (or VO 2 peak) from data measured during submaximal exercise tests.…”

Predicting time to exhaustion during high-intensity exercise using rating of perceived exertion

“…Besides being highly correlated with physiological variables (i.e. blood lactate, heart rate, oxygen uptake) [2][3][4], RPE has shown to be a useful tool to prescribe exercise intensity in the estimation-production paradigm [4,5]. Furthermore, linear regression of submaximal RPE values vs exercise intensity (e.g., 9-17 RPE of 15-point Borg Scale) can be used to accurately predict maximal oxygen uptake (VO 2 max) [4,5], preventing the need of maximal efforts.…”

“…Hence, one can expect that exercise duration until exhaustion be predicted by submaximal RPE values [8,10,11]. However, in incremental exercise the accuracy of the prediction of VO 2 max can be better when extrapolating the submaximal RPE (RPE ≤ 17) to RPE19 in comparison to RPE20 [5,12]. It may be suggested that the predictions are better when RPE = 19 is used, since previous researches have already shown that an RPE = 19 is more commonly reported as the feeling of exhaustion/maximal functional capacity [9,13].…”

“…Despite some evidence of VO 2 max prediction from submaximal RPE regression analysis [4,5] and the scalar linear relationship between RPE and time to exhaustion [11]; to our knowledge, there are no studies testing whether time to exhaustion (Tlim) could be accurately estimated by submaximal RPE linear regression during high intensity constant-load exercise bouts and if it is better to extrapolate to RPE19 (Tlim19) or RPE20 to predict Tlim (Tlim20). Tlim prediction with submaximal parameters is an important tool to monitor the physical fitness of different populations and the effectiveness of physical exercise training without inducing exhaustion in an individual.…”