I got a commercial-grade EEG headband and am trying to look at the data it outputs. The headband quantifies raw EEG signal from a single forehead dry sensor into a range of EEG bands (alpha, beta, etc). The issue that I'm running into is that the values of the EEG bands jump rather significantly from one data point to the next (0.05 second reading intervals). Additionally, there are eye-related artifacts.
I would like to apply some sort of algorithm or statistical analysis to see how the EEG bands behave over some time interval. I'm hoping to see if some EEG band statistically rises or is suppressed over 5-15min time period. Seeing instantaneous jumps in individual readings does not convey this information.
For example, I know that for Actigraphic studies, there are sleep scoring algorithms, like one by Cole that looks at the previous 4 minutes, the current minute and 2 minutes in the future to score a minute of actigraphy data:
SleepScoreConstant* (550*4minAgo + 378*3minAgo + 413*2minAgo + 699*1minAgo +1736*CurrentMinute + 287*1minAhead + 309*2minAhead)
Are there some similar algorithms for EEG band analysis?
Alternatively, it would help if you can suggest the realistic time window over which EEG bands may be statistically analyzed in awake subjects: is it 20 seconds? 5 minutes? 90 minutes?