MENTAL EFFORT (BETA)
Mental Effort is included in a Beta form. The Mental Effort Algorithm is not a formal inclusion of the Developer Tools 2.5 release but can still be tested in your application design. Questions or feedback? Email: support@neurosky.com
For the most up to date versions of this algorithm and the corresponding documentation, please refer to http://developer.neurosky.com and any specific new algorithm preview packages.
When applied to single-channel EEG data collected from forehead area, the Mental Effort algorithm measures the amount of workload exerted by subject's brain while performing a task (how hard the subject’s brain is working while performing the task). The Mental Effort algorithm works well with both motor (e.g. drawing) and mental (e.g. reciting) tasks. The algorithm can be used for monitoring a subject's Mental Effort curve and changes in realtime (to see how their Mental Effort Index changes as they're performing the task), or it can be used for studying their Mental Effort levels on a task across separate sessions or days.
The Mental Effort algorithm must be applied to at least 1 minute of EEG data. A Mental Effort Index will be output by the algorithm after the first 60s, and then every N seconds after that (N is the predefined output rate; default: 10s).
A typical way to use the Mental Effort algorithm is for an application to prompt a subject to be relaxing, with their eyes open, doing nothing, for the first 60s while taking the initial measurement. The first Mental Effort Index value (reported after the first 60s) is kept by the application as a baseline, against which subsequent Mental Effort Index values (by default received every 10s) can be compared to determine relative percent changes (e.g. after relaxing for the first minute, the user starts doing a specific task. Their Mental Effort Index decreases by -20% in the first 10s of the task compared to the first minute baseline, and then goes down further to -35% in the next 10s of the task compared to the first minute baseline, indicating their brain is doing less and less work in the first 20s. After 40s, their Mental Effort Index goes back up to -5% from the first minute baseline, which may indicate their brain is starting to do more work again at that point.)
Alternatively, another possible baseline measurement could be, instead of relaxing and doing nothing during the first 60s, to rather have the subject start doing the task right away and regard the initial part of the task as the baseline. You would then interpret the percentage changes accordingly, knowing that the baseline is based on the initial 60s engaging in the task.
For presenting, studying, and interpreting the data, each reported Mental Effort Index (MEI) value can be compared for percent changes either (1) against the baseline value, or (2) against the MEI value immediately preceding it.
The Mental Effort Index is a floating point number with arbitrary units. This means the MEI numbers have no meaning on their own, and take on meaning only when comparing percentage changes between two or more values.
An example on how to use the algorithm could be found in the sample application – “HelloEEG”.
A few example tasks that the algorithm can to: arithmetic calculation (“Math 24” available in http://www.24theory.com/, and “Addition Aliens Attack” available in )
To use the Mental Effort algorithm 3) in the NeuroSky SDK/API library, it must first be enabled: