| Summary: | Emotions play a key role in non-verbal
communication, accompany everyone in daily life, and are
essential in understanding human behavior. Emotion
recognition can be elicited from text, speech, facial
expression as well as from body gesture. This study aims
to assess the use of bio signal analysis from
electroencephalogram (EEG) to measure emotional
response of a human subject while learning. This
study focused on recognition of inner emotions since
humans can control their facial expressions or vocal
intonation. A noninvasive brain-computer interfaces (BCI)
that read brain signals is used to detect brain waves and
transmit them to a computer for further data processing
and analysis. Different dataset from the subjects were
collected where all the subjects underwent two different
when they underwent two different learning sessions with
two trials each. The subjects level of concentration and
meditation were captured during the sessions in order to
study their academic emotional response level. Results
show that the trend of the time recorded for each subject
while completing each task were decreased . This suggests that
it is possible to obtain faster and more accurate brain
wave control with experience and practices. Implication
from the study is for modeling users in intelligent tutoring
systems.
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