Using a Low-Cost Electroencephalogram (EEG) Directly as Random Number Generator
Bhanupong Petchlert, Hiroshi Hasegawa · 2014
In this paper, we propose a new encoding method for converting an electroencephalogram (EEG) signal into binary sequences which use for supplying the random numbers. We focus on low-cost EEG signal since it can be used in real applications that require true random number generator, such as gaming, gambling, and some complex model simulations. Our encoding method uses fluctuations that lie in EEG data due to noise in biometric measurements by keeping the least significant digits of real EEG sample value and then convert this value into a binary sequence. The generated binary sequences have pass most of all statistical test suite of NIST with success rate of 99.47 percent.