Article

Estimation of % V˙ O 2 reserve from heart rate during arm exercise and running

Zinman College for Physical Education and Sport Science, Wingate Institute, Netanya, Israel.
Arbeitsphysiologie (Impact Factor: 2.19). 01/2001; 83(6):545-50. DOI: 10.1007/s004210000308
Source: PubMed

ABSTRACT

The purpose of the present investigation was to examine the relationship between the percent heart rate reserve (%HRR) in arm exercise and the corresponding percent oxygen uptake (VO2) reserve, and to compare this relationship to that occurring in running. Fourteen male physical education students took part in the study. Each subject performed a maximal running exercise test and a maximal arm cycling test. The subjects also performed three submaximal exercise bouts (in both exercise modes) at 30%, 60% and 80% of their HRR. The subjects were monitored for their heart rate (HR) at rest, maximal HR (HRmax), HR at submaximal work loads. maximal VO2 (VO2max), VO2 at rest and VO2 at submaximal loads. For each subject, load and exercise mode, %HRR and %VO2 reserve were calculated (from HRmax and VO2max as measured during running and arm cycling) and the relationship between the two was evaluated. The main finding of the present investigation is that the prediction of %VO2 reserve in arm cycling from %HRR is grossly overestimated when calculated from HRmax and VO2max measured during running. The prediction is better but still overestimated when calculated from HRmax and VO2max measured during arm cycling. The findings indicate a better prediction of %VO2 reserve from %HRR for running than for arm exercise. These findings should be taken into consideration when prescribing the target HR for arm training.

Full-text preview

Available from: danpat.net
  • Source
    • "), BR (Pulkkinen et al., 2004; Firstbeat Technologies Ltd., 2007), physical fitness (Skinner and Jankowski, 1974; Londeree and Ames, 1976; Rotstein and Meckel, 2000), which may be partly determined by HR rest (Davis and Convertino, 1975; Panton et al., 1996), body weight, and BMI (Greenberg et al., 1995; Health Reviser, 2010; Hoeger and Hoeger, 2012). However, the results in the literature are contradictory on whether age has a significant (Panton et al., 1996) or negligible (Hellerstein, 1973; Franklin et al., 1980) impact on work rate assessment. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In a new approach based on adaptive neuro-fuzzy inference systems (ANFIS), field heart rate (HR) measurements were used to classify work rate into four categories: very light, light, moderate, and heavy. Inter-participant variability (physiological and physical differences) was considered. Twenty-eight participants performed Meyer and Flenghi's step-test and a maximal treadmill test, during which heart rate and oxygen consumption ( ) were measured. Results indicated that heart rate monitoring (HR, HRmax, and HRrest) and body weight are significant variables for classifying work rate. The ANFIS classifier showed superior sensitivity, specificity, and accuracy compared to current practice using established work rate categories based on percent heart rate reserve (%HRR). The ANFIS classifier showed an overall 29.6% difference in classification accuracy and a good balance between sensitivity (90.7%) and specificity (95.2%) on average. With its ease of implementation and variable measurement, the ANFIS classifier shows potential for widespread use by practitioners for work rate assessment.
    Full-text · Article · May 2016 · Applied ergonomics
    • "Negative rates-ofchange values indicate glucose decaying more rapidly during exercise than in the corresponding resting period; or conversely, increasing more slowly during the recovery stage. CI confidence interval, REST resting control period, RoC rate of change, RoC E glycemia RoC during exercise, RoC R glycemia RoC at recovery, wrt with respect to[37], we imputed an intensity of 20 % VO 2max as corresponding to the range 90–110 beats per minute[40]. Figure 8adepicts a moderate dependency of RoC E with respect to physical activity intensity, with regression slope -0.0200 mmol/L h -1 per unit of %VO 2max , although not statistically significant (p = 0.69). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The acute impact of different types of physical activity on glycemic control in type 1 diabetes has not been well quantified. Our objective was to estimate the rate of change (RoC) in glucose concentration induced acutely during the performance of structured exercise and at recovery in subjects with type 1 diabetes. We searched for original articles in the PubMed, MEDLINE, Scopus, and Cochrane databases. Search terms included type 1 diabetes, blood glucose, physical activity, and exercise. Eligible studies (randomized controlled trials and non-randomized experiments) encompassed controlled physical activity sessions (continuous moderate [CONT], intermittent high intensity [IHE], resistance [RESIST], and/or a resting reference [REST]) and reported excursions in glucose concentration during exercise and after its cessation. Data were extracted by graph digitization to compute two RoC measures from population profiles: RoCE during exercise and RoCR in recovery. Ten eligible studies were found from 540 publications. Meta-analyses of exercise modalities versus rest yielded the following: RoCE -4.43 mmol/L h(-1) (p < 0.00001, 95 % confidence interval [CI] -6.06 to -2.79) and RoCR +0.70 mmol/L h(-1) (p = 0.46, 95 % CI -1.14 to +2.54) for CONT vs. REST; RoCE -5.25 mmol/L·h(-1) (p < 0.00001, 95 % CI -7.02 to -3.48) and RoCR +0.72 mmol/L h(-1) (p = 0.71, 95 % CI -3.10 to +4.54) for IHE vs. REST; RoCE -2.61 mmol/L h(-1) (p = 0.30, 95 % CI -7.55 to +2.34) and RoCR -0.02 mmol/L h(-1) (p = 1.00, 95 % CI -7.58 to +7.53) for RESIST vs. Novel RoC magnitudes RoCE, RoCR reflected rapid decays of glycemia during CONT exercise and gradual recoveries immediately afterwards. RESIST showed more constrained decays, whereas discrepancies were found for IHE.
    No preview · Article · Jan 2015 · Sports Medicine
  • Source
    • "While research has demonstrated that HR is a valid tool to prescribe exercise intensity for lower-body exercise, very few studies have investigated the HR-V ˙ O 2 relationship for upperbody exercise. In fact, to the best of our knowledge, only one previous study has investigated the relationship between %HRR and %V ˙ O 2R during upper-body exercise (Rotstein and Meckel, 2000). Their results showed that predictions of %V ˙ O 2R from %HRR obtained during seated arm-cycling exercise were overestimated. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Previous studies have demonstrated that during lower-body exercise the percentage of heart rate reserve (%HRR) is equivalent to the percentage of the oxygen consumption reserve (%V˙O(2R)) but not to a percentage of the peak oxygen consumption (%V˙O(2peak)). The current study examined these relationships in trained surfboard riders (surfers) during upper-body exercise. Thirteen well-trained competitive surfers performed a stepwise, incremental, prone arm-paddling exercise test to exhaustion. For each subject, data obtained at the end of each stage (i.e., HR and V˙O(2) values) were expressed as a percentage of HRR, V˙O(2peak), and V˙O(2R) respectively and used to determine the individual %HRR-%V˙O(2peak) and %HRR-%V˙O(2R) relationships. Mean slope and intercept were calculated and compared with the line of identity (slope=1, intercept=0). The %HRR versus %V˙O(2R) regression mean slope (0.88±0.06) and intercept (20.82±4.57) were significantly different (p<0.05) from 1 and 0, respectively. Similarly, the regression of %HRR versus %V˙O(2peak) resulted in a line that differed in the slope (p<0.05) but not in the intercept (p=0.94) from the line of identity. Predicted values of %HRR were significantly higher (p<0.05) from indicated values of %V˙O(2R) for all the intensities ranging from 35% to 95% V˙O(2R). Unlike results found for lower-body exercise, a given %HRR during prone upper-body exercise was not equivalent to its corresponding %V˙O(2R). Thus, to ensure more targeted exercise intensity during arm-paddling exercise, individual HR-V˙O(2) equations should be used.
    Full-text · Article · Nov 2010 · Journal of PHYSIOLOGICAL ANTHROPOLOGY
Show more