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

Approximate entropy as an indicator of non-linearity in self paced voluntary finger movement EEG

This study investigates the indications of non-linear dynamic structures in electroencephalogram signals. The iterative amplitude adjusted surrogate data method along with seven non-linear test statistics namely the third order autocorrelation, asymmetry due to time reversal, delay vector variance method, correlation dimension, largest Lyapunov exponent, non-linear prediction error and approximate entropy has been used for analysing the EEG data obtained during self paced voluntary finger-movement. The results have demonstrated that there are clear indications of non-linearity in the EEG signals. However the rejection of the null hypothesis of non-linearity rate varied based on different parameter settings demonstrating significance of embedding dimension and time lag parameters for capturing underlying non-linear dynamics in the signals. Across non-linear test statistics, the highest degree of non-linearity was indicated by approximate entropy (APEN) feature regardless of the parameter settings

Flow Visualisation Studies On Wall Mounted Pitot Type Intake With Splitter Plate

Flow Visualisation Studies Employing Schlieren/Shadowgraph Technique And -Simple Oil Flow Technique Were Carried Out On A Simple Pitot Type Of 1-Btake With Splitter Plate Mounted On Base Plate In The NAL 0 .3m Tunnel . Between The Splitter Plate And The Base Plate, A Heat Exchanger Duct With Wedge Diverters Was Also Simulated . From These Studies, The Effect Of Closure Of The Intake Duct And The Heat Exchanger Duct On The Flow Behaviour Was Qualitatively Determined . It Was Found That Flow Constraint In The Heat Exchanger Duct And Diverter Passages Had Considerable Effect On The Flow Through The Intake