Instrumentation & Measurement Magazine 24-4 - 87

navigators were, in general, more mobile inside the bridge in
order to access different displays and control panels, while pilots
spent most of their time standing near the steering wheel
region.
We monitored 12 participants, who were all male students
from the second year of the navigation course in NTNU Ålesund
and were aged between 20 and 24 years. The minimum
requirements for the participants were knowledge about navigation
rules and maritime communication and how to operate
the bridge layout present in the simulators. The exercise duration
depended on the task itself and varied between 0h36min
and 1h22min (1h06min ± 00h11min).
The reported KSS levels for each participant of the second
experiment is presented in Fig. 4. There was a wide range of
initial and final KSS levels reported by the participants. Additionally,
some participants did not report any increase in the
KSS level. This heterogeneous response for the participants'
self-assessment demonstrates the impact of both individual
differences and the performed task in the MF assessment.
The results presented in Fig. 5 show that for most subjects
there was a significant increase in the MF4
state and for some
subjects it shows high levels of MF5 state towards the end of the
task. While for some participants the tendency for both self-assessment
and the algorithm assessment was quite similar, for
others they diverged significantly. For Subject 2.2, for example,
the self-assessment points towards a constant tiredness level
while the MF score points toward a significant increase in the
MF level in the beginning of the experiment, leading to a constant
MF level towards the end.
In general, the proposed MF score was capable of detecting
trends in the increase of MF. The cases where these trends
were not very well captured are mostly related to higher levels
of MF5
tiplier kMF5
state
would reduce the total MF score for cases with very high MF5
levels. With additional experimental data, it would be possible
to fine-tune the model's parameters and obtain a better MF assessment
response.
Conclusion
Assessing MF in maritime operators can greatly reduce accident
risk due to human failure. The assessment system needs
to have low intrusiveness and be subject- and task independent.
For such a system, we propose the use of an EEG sensor
to collect information about the brain activity of maritime operators.
This data is used to derive a power spectral density
ratio that can track increases in operators' MF levels. To evaluate
the performance of the proposed system, we performed
experiments combining multi-subject and multi-task analysis.
The proposed algorithm can be applied in real time and
requires a very simple hardware setup and little computational
effort.
In general, the algorithm was capable of capturing the MF
development trend, taking as reference the reported KSS levels
from each participant. The algorithm performance was considered
satisfactory, as it captured different degrees of variation
June 2021
, such as for Subjects 2.1 and 2.11. Reducing the MF mulor
increasing the upper limit defining the MF4
of the KSS levels, including situations with no significant increase
in the reported KSS. A next step in this research would
include the investigation of the applicability of the proposed
algorithm in a closed loop system. In this scenario, the effectiveness
of a risk feedback for mitigating MF development and
reducing accident risk would be assessed.
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IEEE Instrumentation & Measurement Magazine
87
Int. IEEE
https://www.emotiv.com/epoc/

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