| eegdata {eegkitdata} | R Documentation |
EEG Data from Alcoholic and Control Subjects
Description
Contains 64-channel electroencephalography (EEG) data from 10 alcoholic and 10 control subjects participating in a visual event-related potential (ERP) experiment. Data frame contains 5 trials (replications) from each subject. Data were recorded at 256 Hz for 1 second following the presentation of the visual stimulus.
Usage
data(eegdata)
Format
A data frame with 1638400 observations and the following 7 variables:
- subject
-
Subject identification numbers (factor).
- group
-
Subject group: "a" for alcoholic and "c" for control (factor).
- condition
-
Experimental condition: "S1" (factor).
- trial
-
Trial number for each replication (integer).
- channel
-
Channel from which data was recorded (factor).
- time
-
Time point at which data was recorded: 0,1,...,255 (integer).
- voltage
-
Recorded EEG voltage in microvolts (numeric).
Details
Created from UCI MLR EEG training data using geteegdata with option nt=5.
Author(s)
Nathaniel E. Helwig <helwig@umn.edu>
Source
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
Begleiter, H. Neurodynamics Laboratory. State University of New York Health Center at Brooklyn.
Ingber, L. (1997). Statistical mechanics of neocortical interactions: Canonical momenta indicatros of electroencephalography. Physical Review E, 55, 4578-4593.
Ingber, L. (1998). Statistical mechanics of neocortical interactions: Training and testing canonical momenta indicators of EEG. Mathematical Computer Modelling, 27, 33-64.
Examples
# see examples for eegtime, eegspace, eegica, and eegsmooth (in package eegkit)
# example code to create eegdata (not run):
# #(1)# download and untar SMNI_CMI_TRAIN.tar.gz file from UCI:
# # http://archive.ics.uci.edu/ml/machine-learning-databases/eeg-mld/
# #(2)# eegdata=geteegdata(indir="/Users/Nate/Downloads/SMNI_CMI_TRAIN/",nt=5)