MEAreplace: Substitute values from MEA data

In rMEA: Synchrony in Motion Energy Analysis (MEA) Time-Series

Substitute values from MEA data

Description

This function allows to substitute MEA data from a list of time epochs. This is useful to mark and remove artefacts, or to substitute extreme values.

Usage

MEAreplace(mea, epochs, replacement, filterLabel = "replaced")

Arguments

mea	an object of class MEA or a list of MEA objects (see function readMEA)
epochs	a data.frame containing a list of epochs that must be changed (see Details)
replacement	the value used to mark artefacts. Use 'NA' to remove artefacts and '0' to apply thresholds. Other values are allowed but should not be used without a good reason.
filterLabel	can be used to update the filter attribute, to keep track of the data transformations.

Details

the artefacts data.frame must contain a "start" and "end" columns, with the boundaries of the epochs that must be marked as artefacts. The start and end values can be either integers (denoting seconds), or string values in the format hh:mm:ss, or mm:ss. Furthermore the data.frame must contain a uid column containing strings in the format "group_id_session", OR three columns group, id, session presenting the information separately. Data identifiers must match those of the mea object.

The data.frame can be either hand crafted, for instance by importing a csv file (see read.table), or generated through the packages own artefact detection tools such as CCFartefacts

Value

returns the same MEA or MEAlist object, with all artefactual data substituted.

Examples

#' ## read the first 4 minutes of the normal sample
## (intake interviews of patients that carried on therapy)
path_normal <- system.file("extdata/normal", package = "rMEA")
mea_normal <- readMEA(path_normal, sampRate = 25, s1Col = 1, s2Col = 2,
                      s1Name = "Patient", s2Name = "Therapist",
                      idOrder = c("id","session"), idSep="_", skip=1, nrow = 6000)
mea_normal <- MEAccf(mea_normal, lagSec = 5, winSec = 30, incSec = 10, ABS = FALSE)

## find potential artefacts
artefacts = CCFartefacts(mea_normal, threshold = 0.2, delta=1)

##replace values
mea_replaced <- MEAreplace(mea_normal, epochs = artefacts,
                           replace = NA, filterLabel = "artefacts deletion")

#visualize results on first case
plot(mea_normal$all_200_1)
plot(mea_replaced$all_200_1)

rMEA documentation built on March 18, 2022, 5:41 p.m.