It performs the whole process of the VO2max data analysis, which includes:
data standardization and normalization according to incremental protocol (incremental_normalize()
),
'bad breaths' detection (detect_outliers()
),
mean response time calculation (incremental_mrt()
) (currently ignored),
and maximal values calculation (VO2, PO, HR, RER) (perform_max()
).
vo2_max( .data, vo2_column = "VO2", vo2_relative_column = NULL, heart_rate_column = NULL, rer_column = NULL, detect_outliers = TRUE, average_method = c("bin", "rolling"), average_length = 30, mrt, plot = TRUE, verbose = TRUE, ... )
.data | Data retrieved from |
---|---|
vo2_column | The name (quoted) of the column containing the absolute oxygen uptake (VO2) data. Default to |
vo2_relative_column | The name (quoted) of the column containing the relative to body weight oxygen uptake (VO2) data. Default to |
heart_rate_column | The name (quoted) of the column containing the heart rate (HR) data. Default to |
rer_column | The name (quoted) of the column containing the respiratory exchange ratio (RER) data. Default to |
detect_outliers | A boolean indicating whether to detect outliers. Default to |
average_method | The average method to be used for VO2max calculation. One of |
average_length | The length, in seconds, of the average to be used. For example, if |
mrt | A boolean indicating whether to calculate the mean response time. To be implemented soon <- currently ignored. |
plot | A boolean indicating whether to produce a plot with the summary results. Default to |
verbose | A boolean indicating whether messages should be printed in the console. Default to |
... | Additional arguments passed onto |
a tibble containing one row and the following columns:
The absolute VO2max.
The relative VO2max.
The peak power output.
The maximal heart rate.
The maximal RER.
The plot, if plot = TRUE
.
TODO
## get file path from example data path_example <- system.file("ramp_cosmed.xlsx", package = "whippr") ## read data from ramp test df <- read_data(path = path_example, metabolic_cart = "cosmed") ## normalize incremental test data ramp_normalized <- df %>% incremental_normalize( .data = ., incremental_type = "ramp", has_baseline = TRUE, baseline_length = 240, work_rate_magic = TRUE, baseline_intensity = 20, ramp_increase = 25 ) ## detect outliers data_ramp_outliers <- detect_outliers( .data = ramp_normalized, test_type = "incremental", vo2_column = "VO2", cleaning_level = 0.95, method_incremental = "linear", verbose = TRUE )#>#> ● 2 outlier(s) found in baseline#> ● 15 outlier(s) found in ramp## analyze VO2max perform_max( .data = data_ramp_outliers, vo2_column = "VO2", vo2_relative_column = "VO2/Kg", heart_rate_column = "HR", rer_column = "R", average_method = "bin", average_length = 30, plot = TRUE, verbose = FALSE )#> # A tibble: 1 x 6 #> VO2max_absolute VO2max_relative POpeak HRmax RERmax plot #> <dbl> <dbl> <int> <dbl> <dbl> <list> #> 1 3524. 46.0 303 193 1.13 <gg>