Generate a summary of the signal data to view weak and saturated channels

This function will generate a summary of the signal data to view weak and saturated channels. The output contains the optode, the status of the min and max signal values, the status of the mean signal value, and whether there are any NA values in the signal data. It is meant as a quick way to check the quality of the signal data. Can be used in conjunction with visual inspection to determine low quality channels.

Usage

signal_summary(nirsData, min = 1000, max = 4000)

Arguments

nirsData

(DATAFRAME) NIRS data that has been imported using the import_nirs function.

min

The lower value for the signal data to be considered "weak". Default is 1000.

max

The upper value for the signal data to be considered "saturated". Default is 4000.

Value

A dataframe with the signal summary.

See also

import_nirs

Examples

if (FALSE) { # \dontrun{
# To generate a signal summary from a single NIRS file
nirsData <- import_nirs("path/to/nir/file.nir")
signalSummary <- signal_summary(nirsData)

 # To generate a signal summary from multiple NIRS files

 ##  name path to files (ending in "/")
 mypath <- paste0(system.file("extdata", package = "cobifnirs"),"/")

 ## List all files in the folder that end in ".nir"
 nirsFiles <- list.files(mypath, pattern = ".nir", full.names = FALSE)

 ## Import all of the nirs files
 nirsData <- lapply(nirsFiles, import_nirs, folder = myPath)

## Generate a signal summary for each of the nirs files
signalSummary <- lapply(nirsData, signal_summary)

## Combine the signal summaries into a single dataframe (recommend you name each of the dataframes in the list first)


## add a column to each dataframe in the list to identify the participant - in this example, pids is a vector of participant ids

signalSummary <- mapply(`[<-`, signalSummary, 'npid', value = pids, SIMPLIFY = FALSE)

## combine the dataframes into a single dataframe

signalSummary <- do.call(rbind, signalSummary)

} # }