Your files should be structured in a way such that you have one main folder that contains within in, a subfolder for each participant. The name of each participant folder should be their ID number. In each “participant” subfolder should be all zip files containing their data, using the naming convention that E4 Connect uses (starttime_serialnumber.zip).
This step is where you extract and filter EDA data. It will output raw data, filtered data (using user-specified high and low pass filters + a butterworth filter), and filtered + feature-scaled ([0,1]) data. It will also provide summary data at the participant and session level.
Inputs: (1) List of participant numbers and (2) location where ZIP folders are stored.
Outputs: (1) one RDS file per participant with all data, (2) summary file that gives participant-level meta-data.
This is the final step where everything gets put into one file.
E4_EDA_Process.part4.BinMatchedEDA(participant_list=c(1001),
rdslocation.MatchedEDA="~/extdata/output/matched_EDA/",
rdslocation.BinnedMatchedEDA="~/extdata/output/binned_matched_EDA/",
min.after = 20,min.before = 20)
Note: The values for “MinBeforeAfter” for “before” values will be negative, to use with things like growth curve modeling. If you positive integers, just multiple this column by -1.