What eye blink can tell us
There are a lot of activities to gain data from the brain. In 2015 a group of students in Berkeley was exposed to a series of stimuli and at the same time measured their EEG. The data sets has been anonymizised and published, but no definite results could be drawn from the data.
The EEG raw signal is permanently fluctuating and the information is grouped in so called bands, giving the intensity of the presence of certain frequencies in the signal. The mindwave mobile headsets are deriving so called eSense values with a rate of one set per second. In the same time, there are 512 raw values, which can be transmitted to a receiver, which is normally a PC with blue tooth.
A reasonable candidate for deriving useful information is the eye blink signal, which is manifested in the raw signal by a positive peak with 60 ms width, followed by a negative tail of about 90 ms. This event is in the common measuring regime of recording each second sometimes distributed over two data sets, making the evaluation hard.
The student Laurin K. had the idea, not to record the data in a fixed time frame, but making a second of history always available and gliding this interval over the time, while looking for such events.
One can visualize this algorithm by a ring of 512 values in which center a canon rotates with a rate of one revolution per second. The canon fires at a rate of 512 Hz replacing in each instant the eldest value by the newest. So the ring always contains a recent history of 512 values, triggered by the event of eye blink. So it can never happen, that the event is distributed over more than one data set and it is fixed in position, making analysis much easier.
First trials showed the pronounced features, which eye blink show in dependence, what has been seen in the moment and how relaxed the client is. It turns out, that it could be easier to drain information from the eye blink curve than from other features of the EEG signal.
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Christian Rempel in Zeuthen, den 19.11.2017