elpatron (version 0.0.4)

Wbalance: Calculate W' balance

Description

This function provides an efficient implementation of Dr. Skiba's W' balance algorithm (Skiba et al., 2012).

Usage

Wbalance(time.s, power.W, CP, Wprime.kJ = NULL, data = NULL, smooth = FALSE)

Arguments

time.s, power.W

numeric vectors of similar length describing elapsed time and corresponding power output recordings.

CP, Wprime.kJ

numerics (scalar) describing the two parameters of the basic critical power model, given in units of watts and kilojoules, respectively.

data

optional; a data.frame in which to find time.s and power.W arguments. If provided (i.e. not NULL), time.s and power.W arguments should be bare, unquoted column names.

smooth

logical; should power data be averaged into sections of sub- and supra-CP power output?

Value

A numeric vector of W' expended/balance values.

Details

If the Wprime.kJ argument is supplied, W' balance per se is returned; that is, the output starts at "Wprime.kJ" and will decline with periods of supra-CP power output. This approach, while most familiar, relies on a valid estimate of total W' in order that W' balance is not seen to go < 0. This requirement can be circumvented by simply returning W' expended; that is, the ongoing work expended above CP. W' expended will be returned if the Wprime.kJ argument is left as NULL (default).

References

Skiba PF, Chidnok W, Vanhatalo A, Jones AM. Modeling the Expenditure and Reconstitution of Work Capacity above Critical Power. Medicine & Science in Sports & Exercise 44: 1526–1532, 2012.

Skiba PF, Jackman S, Clarke D, Vanhatalo A, Jones AM. Effect of Work and Recovery Durations on W' Reconstitution during Intermittent Exercise. Medicine & Science in Sports & Exercise 46: 1433–1440, 2014.

Skiba PF, Fulford J, Clarke DC, Vanhatalo A, Jones AM. Intramuscular determinants of the ability to recover work capacity above critical power. European Journal of Applied Physiology ( November 26, 2014). doi: 10.1007/s00421-014-3050-3.

Examples

library(dplyr, warn.conflicts = FALSE)
data(chaingang)

chaingang <- mutate(chaingang,
                    Wbal = Wbalance(time.s, power.W, CP = 325))

# For an estimate of W'
max(chaingang$Wbal)

# This is probably being inflated by passing raw power data
# to the function. A solution:
chaingang <- mutate(chaingang,
                    power.W = roll_mean(power.W, 25, ema = TRUE),
                    Wbal = Wbalance(time.s, power.W, CP = 325))

max(chaingang$Wbal)  # 19.4 is more realistic.

plot(Wbal ~ time.s, type = "l", col = "red", data = chaingang)

# This representation is probably unintuitive to most.
# Hence, some modified approaches:

# Reverse the y axis...
ylim <- extendrange(chaingang$Wbal) %>% rev
plot(Wbal ~ time.s, type = "l", col = "red", ylim = ylim, data = chaingang)
title("Flipped y axis")

# Subtract an estimate of W'
Wprime <- max(chaingang$Wbal)
plot(Wprime - Wbal ~ time.s, type = "l", col = "red", data = chaingang)
title("W' subtracted")