Fit Recovery Trajectory to Longitudinal Activation Data

Fits parametric recovery curves (exponential, sigmoid, or linear) to longitudinal muscle activation data from an MSKLongitudinalTracker.

Usage

mskRecoveryTrajectoryFit(
  tracker,
  model = c("exponential", "sigmoid", "linear"),
  muscle_subset = NULL,
  partial_pool = FALSE
)

Arguments

tracker

An MSKLongitudinalTracker object.

model

Character, recovery curve model: "exponential" (default), "sigmoid", or "linear".

muscle_subset

Optional character vector of muscle names to fit (NULL = all muscles).

partial_pool

Logical; when TRUE and there is more than one muscle, an exponential fit is estimated by partial pooling across muscles via a population NLME (PhysioClinStats::recoveryTrajectoryLME, if installed), rather than one independent NLS per muscle. Defaults to FALSE (the independent-NLS behaviour), which is also the fallback if the NLME is unavailable or fails to converge.

Value

An S3 object of class "MSKRecoveryTrajectory" with:

fits

list per muscle with coefficients, residuals, R-squared, AIC

predicted

matrix of predicted values (muscles x timepoints)

model_type

character

recovery_rate

numeric vector (slope at midpoint for each muscle)

time_to_90pct

estimated time to 90 percent of asymptotic recovery

Examples

if (FALSE) { # \dontrun{
traj <- mskRecoveryTrajectoryFit(tracker, model = "exponential")
} # }