Constructs a compensation-weighted subgraph from compensation detection results, identifying compensation chains and hub muscles.
Arguments
- compensation_result
An
"MSKCompensation"object.- hg
An MSKHypergraph object (NULL loads default).
- emg_mapping
Optional pre-computed data.frame from
emgToMSKMapping().
Value
A list with:
- adjacency
Weighted compensation adjacency matrix
- chains
List of compensation chains
- hub_muscles
Muscles in multiple compensation chains
- community_involvement
MSK communities affected by compensation
Examples
C <- matrix(c(1,1,0,0,0, 0,1,1,0,0, 0,0,1,1,0, 0,0,0,1,1, 1,0,0,0,1, 0,1,0,1,0),
nrow = 6, byrow = TRUE,
dimnames = list(paste0("bone", 1:6),
c("Biceps Brachii", "Deltoid", "Trapezius",
"Triceps Brachii", "Brachialis")))
hg <- MSKHypergraph(C)
set.seed(1); emg_base <- matrix(abs(rnorm(300 * 4)), 300, 4)
set.seed(2); emg <- matrix(abs(rnorm(300 * 4)), 300, 4)
colnames(emg) <- colnames(emg_base) <-
c("Biceps Brachii", "Deltoid", "Trapezius", "Triceps Brachii")
result <- mskDetectCompensation(emg, emg_base, "Biceps Brachii", hg = hg)
net <- mskCompensationNetwork(result, hg = hg)
net
#> $adjacency
#> <0 x 0 matrix>
#>
#> $chains
#> list()
#>
#> $hub_muscles
#> character(0)
#>
#> $community_involvement
#> integer(0)
#>