The goal is to identify neuro-physiological signatures at several levels of mental workload during the realisation of tasks, performed by all the subjects. In parallel, there will be a methodological work consisting to develop the classification algorithms, predictives of these levels of mental workload in real time, in purpose to implement a passive brain-machine interface in the best interest of operators that accomplish complex tasks. Mesures of electro-physiological activity will be recorded in order to approve states of charge in addition to behavioral performances.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
19
UniversityHospitalGrenoble
La Tronche, France
Electroencephalography (EEG)
With a EEG helmet. Classical Stemberg's task Stemberg's task with time pressure N-back task Mental arithmetic task 13 minutes MATB Multi-Attribute Task Battery : Divided attention task
Time frame: 10 minutes
Electrooculography (EOG)
Simultaneously to EEG : electrooculography (EOG) will be recorded With a EEG helmet. Classical Stemberg's task Stemberg's task with time pressure N-back task Mental arithmetic task 13 minutes MATB Multi-Attribute Task Battery : Divided attention task
Time frame: 10 minutes
Subjective and behavioral data
KSS scale to evaluate the patient's state of alertness Classical Stemberg's task Stemberg's task with time pressure N-back task Mental arithmetic task 13 minutes MATB Multi-Attribute Task Battery : Divided attention task
Time frame: 10 minutes
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