Og. Okogbaa et al., ON THE INVESTIGATION OF THE NEUROPHYSIOLOGICAL CORRELATES OF KNOWLEDGE WORKER MENTAL FATIGUE USING THE EEG SIGNAL, Applied Ergonomics, 25(6), 1994, pp. 355-365
Technological trends and advances in automation have underscored the i
mportance of task performance of certain jobs requiring mental functio
ns such as information processing and decision analyses. Most experts
agree that such work environments produce increased mental activities,
with profound implications for mental fatigue and stress. Consequentl
y, productivity measurement and improvement for white collar or 'knowl
edge worker' occupations remains a major challenge and concern. This i
nvestigation defines an experimental approach that examines the neurop
hysiological correlates of white collar worker mental fatigue using th
e EEG signal. A 6 h laboratory experiment was conducted to simulate wo
rk output. The methods of assessing fatigue employed were mental tests
and physiological measurements. The experiment involved reading of st
andardized texts, finding solutions to arithmetic-logical problems and
a combination of both task types. Two primary performance measures we
re obtained, work output and brain waves. Fast Fourier transform and c
orrelation analyses are used to quantify the relationship between cert
ain brain waves and mental fatigue. This research is a major step towa
rds the development of a model that explores the relationship between
mental fatigue and factors associated with output performance, optimal
recuperation periods and related variables. Such a model would be use
ful in human reliability prediction based on task parameters and worke
r profiles.