report.txt

ADJUST
Automatic EEG artifacts Detector with Joint Use of Spatial and Temporal features

Andrea Mognon and Marco Buiatti (2009-2014)

Analyzed dataset: co3c0000402-0.set
Analysis date: 25-Sep-2020
Analysis carried out on the 30 Independent Components

> HEM - Horizontal movements

Classification based on features:
SED - Spatial eye difference (threshold=-0.240521)
MEV - Maximum epoch variance (threshold=3.666613)

ICs with Horizontal eye movements:
30

>> VEM - Vertical movements

Classification based on features:
SAD - Spatial average difference (threshold=0.038124)
MEV - Maximum epoch variance (threshold=3.666613)

ICs with Vertical eye movements:
3

>>> EB - Blinks

Classification based on features:
SAD (threshold=0.038124)
TK - Temporal kurtosis (threshold=0.078357)

ICs with Blinks:
4   8  13

>>>> GD - Discontinuities
Classification based on features:
GDSF - Generic Discontinuities Spatial Feature (threshold=0.604107)
MEV - Maximum epoch variance (threshold=3.666613)

ICs with Generic Discontinuities:
23  30

Artifacted ICs (total):
3   4   8  13  23  30