A human-computer interface uses neuroelectric signals recorded from the user's scalp i.e. electroencephalograms (EEGs) to alter the program being run by the computer, for example to present less or more difficult material to the user, depending on the user's neurocognitive on-line workload score. Each user is tested with a standard battery of tasks, while wearing an EEG hat, to calibrate a neurocognitive workload function. The calibrated function is user-specific and is obtained by modifying a neural network pattern analyzer which has been previously trained to index neurocognitive workload using data from a group of subjects performing the same battery of tasks.
Neurocognitive adaptive computer interface method and system based on on-line measurement of the user's mental effort