Oxygenation During Exercise: An Analytical Experiment
by Timothy Girgis (2614615G)
BIOL 2C Human Biology II
Mr. Nairn Scobie
University of Glasgow
Glasgow, Scotland
February 26, 2022
1. Introduction
In this experiment, one subject performed submaximal exercise while gas inspiration and expiration were measured, along with heart rate, in order to determine the relationship between heart rate (HR), work rate increment (W), and oxygen uptake (VO2).
2. Results
A 20-subject sample data sheet, obtained during a quite morning laboratory session, was provided by the University of Glasgow school of Medical, Veterinary, and Life Sciences (MVLS) laboratory team, which yielded the descriptive statistical measures in Table 1 below.
Table 1. Summary of median rate of perceived exertion (RPE) as well as the means and standard deviations (SD) of heart rates (HR), oxygen uptake (VO2),and R-values at different work rate increments for the 20-subject sample
There is a clear linear relationship between the work rate increment, HR, and VO2, as shown in Figure 1 below.
2 (ml/kg/min)
Figure 1 Scatterplot of original sample showing linearity between VO2 ml/kg/min (y-axis) and W (x-axis)
There is also a direct linear relationship between the aforementioned data points, and the Borg rate of perceived exertion, which supports the accuracy of subject self-reporting regardless of the fact that it is likely to vary from person to person. Notably, however, the sole subject of this particular experiment yielded data that, while still generally linear, was markedly less so than the sample means – while consistently reporting much higher RPEs, as given in Table 2 below.
Work Rate Increment (W)
Table 2. Heart rate (HR), oxygen uptake (VO2), R-value, and Borg rate of perceived exertion (RPE) at different work rate increments for a single subject sample. Data was obtained in the afternoon during a busy laboratory session, although resting work rate increment was taken after 3 minutes of quite breathing into the Douglas bag.
Unsurprisingly, given the relatively small sample size of just 20 subjects, the data obtained from the subject of this experiment had a slight flattening effect when appended to the sample data set, as shown in Table 3 below.
Work Rate Increment (W)
Table 3. Amended 21-subject sample summary of median RPE and means and standard deviations (SD) of heart HR, VO2, and R-values at different work rate increments.
4. Discussion
Although the amended sample still maintained a high degree of linearity between the work rate increment and HR, VO2, and R, there was a slight skewing of that relationship. Although there is some literature suggesting that the relationship between key values such as HR and VO2 are not necessarily perfectly linear at maximal exercise (Vella and Robergs, 2005), the sole subject in this experiment was only subject to submaximal exercise, and thus this is not likely responsible for the observed discrepancies. Differences in metabolic substrate utilization, such as whether fat or carbohydrates are being broken down for energy, are also well known to alter oxygen uptake, however in this case the discrepancies between the volume inspired and expired (VI and VE) do not appear significant enough to have such a distortive impact on the results.
More likely, differences in relative heart rate, other environmental factors (such as the time of day the data was gathered – the original data was gathered in a quite morning laboratory whereas the subject of this experiment was measured in a loud evening laboratory) and experimental error were the primary causes of the discrepancies observed. While data on the average age of the subjects in the provided sample is not available, it is noteworthy that agerelated differences in heart rate, particularly in the target and maximum heart rate, have been well described in medical literature (CDC, 2020). Moreover, in the case of this experiment, the subject only wore the nose clamps during the initial ‘at rest’ data readings, which likely distorted the results in two ways. First, discomfort likely contributed to the higher resting heart rate, which for this subject was 90 b/min – not outside of the 60-100 b/min average range (Shmerling, 2017), but certainly at the higher end. Indeed, while the original sample suffered from significant resting HR variation between the subjects themselves, it was even more skewed when the data from the subject of this experiment was included, as shown in Figure 2.
Original Data Set (N=20)
Amended Data Set (N=21)
Figure 2 Range of R-values for the original unamended 20-subject sample at rest (top box plot) and amended 21-subject sample (bottom box plot). Median, which falls on the Q1 line, is clearly skewed from the start, but becomes significantly more skewed after the data from this experiment was amended into the sample data set.
Second, the lack of clamping during the various work rate increments likely allowed a substantial amount of gas to escape rather than being exhaled into the Douglas bag. Regardless, it is clear that the there is a linear relationship between exercise intensity, heart rate, and oxygen uptake, at least as far as submaximal exercise is concerned.
References
CDC (2020). 'Target Heart Rate and Estimated Maximum Heart Rate.' Available at: https://www.cdc.gov/physicalactivity/basics/measuring/heartrate.htm (Accessed: 2 March 2022).
Shmerling, R. H. (2017) ‘How's your heart rate and why it matters?’ Harvard Health Available at: https://www.health.harvard.edu/heart-health/hows-your-heart-rate-andwhy-it-matters (Accessed: 2 March 2022).
Vella, C.A. and Robergs, R.A. (2005) ‘Non-linear relationships between central cardiovascular variables and VO2 during incremental cycling exercise in endurancetrained individuals.’ The Journal of Sports Medicine and Physical Fitness, 45(4), pp. 452–459.
Experiment Data and Gas Calculations
Subject body mass: 59.8 kg
Barometric Pressure: 760 mm Hg