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Overview

This R package offers a fast, standardized and reproducible workflow for data from cardiopulmonary exercise testing. It offers tools for data import, processing, summary and visualization.

Background

Measuring gas exchange during physical exercise is a common procedure in sports science and medicine. It allows to assess the functional limit of the cardiovascular system, evaluate the success of training interventions, and diagnose cardio-respiratory diseases. The measuring devices of cardiopulmonary exercise testing — so-called metabolic carts — output their data in different formats. Moreover, measured breath-by-breath data is noisy and requires post-processing. This package standardizes the import and processing of raw data from different metabolic carts.

Installation

Install spiro from CRAN:

Install the current development version of spiro from GitHub:

if (!require(remotes)) install.packages("remotes")
remotes::install_github("ropensci/spiro")

Usage

Main functions:

  • Use spiro() to automatically import and process raw data from cardiopulmonary exercise testing.
  • Use spiro_summary() for a summary of cardiopulmonary parameters (e.g., relative oxygen uptake, respiratory quotient, heart rate, …) for each load step.
  • Use spiro_max() to calculate maximum parameter values (e.g., VO2max).
  • Use spiro_plot() to visualize the data as a modifiable Wassermann 9-Panel Plot.

Further functionality:

  • Add external heart rate data from a .tcx file.
  • Automated guessing or manual setting of exercise protocols.
  • Different data filtering strategies for VO2max determination (moving time averages, moving breath averages, Butterworth filters)

Metabolic Carts

The following metabolic carts are currently supported by spiro:

  • Cortex
  • Cosmed
  • Vyntus
  • ZAN

Support for further metabolic carts is planned for future releases.

Example

library(spiro)

# get data path for example
file <- spiro_example("zan_gxt")

# import and process the raw data
gxt_data <- spiro(file)

# summary of parameters by load step
spiro_summary(gxt_data)
#> for pre-measures, interval was set to length of measures (60 seconds)
#>    step_number duration load     VO2    VCO2     VE HR PetO2 PetCO2 VO2_rel
#> 1            0       60  0.0  500.19  411.74  13.03 NA    NA     NA    7.58
#> 2            1      300  2.0 1860.92 1585.75  39.87 NA    NA     NA   28.20
#> 3            2      300  2.4 2097.82 1805.27  44.63 NA    NA     NA   31.79
#> 4            3      300  2.8 2413.01 2122.17  52.63 NA    NA     NA   36.56
#> 5            4      300  3.2 2710.68 2319.93  57.19 NA    NA     NA   41.07
#> 6            5      300  3.6 3048.75 2684.87  67.45 NA    NA     NA   46.19
#> 7            6      300  4.0 3404.02 3026.70  75.91 NA    NA     NA   51.58
#> 8            7      300  4.4 3724.37 3383.64  88.36 NA    NA     NA   56.43
#> 9            8      300  4.8 4223.82 3993.55 106.44 NA    NA     NA   64.00
#> 10           9      300  5.2 4573.91 4488.36 127.54 NA    NA     NA   69.30
#>        RE  RER  CHO   FO
#> 1      NA 0.82 0.27 0.15
#> 2  234.97 0.85 1.27 0.46
#> 3  220.73 0.86 1.51 0.49
#> 4  217.62 0.88 1.95 0.48
#> 5  213.91 0.86 1.89 0.65
#> 6  213.86 0.88 2.47 0.60
#> 7  214.90 0.89 2.90 0.62
#> 8  213.75 0.91 3.50 0.56
#> 9  222.21 0.95 4.68 0.37
#> 10 222.12 0.98 5.82 0.12

# maximum values
spiro_max(gxt_data)
#>       VO2    VCO2     VE VO2_rel  RER HR
#> 1 4732.28 4640.75 129.62    71.7 0.99 NA

# Wassermann 9-Panel Plot
spiro_plot(gxt_data)

Citation

citation("spiro")
#> 
#> To cite spiro in publications use:
#> 
#>   Simon Nolte (2022). spiro: Manage Data from Cardiopulmonary Exercise
#>   Testing. R package version 0.1.1. DOI: 10.5281/zenodo.1040727.
#>   https://docs.ropensci.org/spiro
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {spiro: Manage Data from Cardiopulmonary Exercise Testing},
#>     author = {Simon Nolte},
#>     year = {2022},
#>     url = {https://docs.ropensci.org/spiro/},
#>     doi = {10.5281/zenodo.5816170},
#>     note = {R package version 0.1.1},
#>   }

The whippr package offers a different approach to working with data from cardiopulmonary exercise testing. It additionally offers functions for analyzing VO2 kinetics.

Acknowledgment

The following persons contributed to this package by providing raw data files: Daniel Appelhans, Sebastian Mühlenhoff, Yannick Schwarz, Adrian Swoboda, Andreas Wagner.

Contributing

If you consider contributing to this package, read the CONTRIBUTING.md. Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.