PIN generation using EEG : a stability study

In a previous study, it has been shown that brain activity, i.e.

electroencephalogram (EEG) signals, can be used to generate personal

identification number (PIN). The method was based on brain–computer

interface (BCI) technology using a P300-based BCI approach and showed that

a single-channel EEG was sufficient to generate PIN without any error for

three subjects. The advantage of this method is obviously its better fraud

resistance compared to conventional methods of PIN generation such as

entering the numbers using a keypad. Here, we investigate the stability of these

EEG signals when used with a neural network classifier, i.e. to investigate the

changes in the performance of the method over time. Our results, based on

recording conducted over a period of three months, indicate that a single

channel is no longer sufficient and a multiple electrode configuration is

necessary to maintain acceptable performances. Alternatively, a recording

session to retrain the neural network classifier can be conducted on shorter

intervals, though practically this might not be viable.