Interpret EMG Network with Knowledge-Graph Metadata — emgInterpretNetworkKG • PhysioEMG

Adds metadata/KG context to high-weight network edges. This function does not require a specific backend and works with user-provided tables exported from PhysioAnnotationHub/physioKG workflows.

Usage

emgInterpretNetworkKG(
  network,
  node_metadata = NULL,
  kg_edges = NULL,
  threshold = NULL,
  top_n = 20L,
  window = NULL
)

Arguments

network: A square matrix (channels x channels) or 3D array (window x channels x channels).
node_metadata: Optional data.frame containing at least channel. Additional columns (e.g. kg_node, muscle_name, muscle_group) are carried into the edge table.
kg_edges: Optional data.frame of KG links. Expected columns are node_a, node_b, and optional relation.
threshold: Optional edge threshold. Default is 75th percentile of upper-triangle weights.
top_n: Maximum number of edges returned after thresholding.
window: Optional window index when network is a 3D array. If NULL, uses the mean across windows.

Value

A list with:

edge_table: Ranked edge table with optional metadata/KG annotations.
threshold: Applied threshold value.
network_matrix: Matrix used for interpretation.
summary: List of summary statistics.
kg_relation_summary: Relation counts from matched KG links, or NULL.