EEG dynamic noise floor measurement with stochastic flash A/D converter

The noise floor is the measure of the signal at the output of a measurement system, produced by internal and external noise sources. The dynamic noise floor quantifies the effects of non-uniform noise. The main objective is to quantify accurately the noise floor in an EEG system, as the measurement error of the biopotential signals is in the microvolts voltage range. Signals measured by an EEG range down to 0.01 Hz, so measurements require long time and produce large quantities of data that needs to be measured with high accuracy. This paper presents a novel idea for the noise floor quantification using stochastic method of measurement over a long time interval. The accuracy of the method is independent of the input noise type, and it depends only on duration of the measurement interval and the flash A/D converter accuracy. The method is based around the 4-bit Stochastic Flash ADC with fast processing time of recorded data and high precision. A mathematical model of the stochastic measurement results is given. When the length of the measurement interval is 100 s, the relative measurement error falls below 0.004%. Long time of measurement and high precision allow this method to be integrated into the mixed-mode system on a chip, as a part of self-calibration process in a wearable wireless medical monitoring device, such as an EEG. The prototype with the integrated EEG chip is described and its noise floor is measured using the 4-bit Stochastic Flash ADC. In conclusion, the measurement results are analyzed and compared to the product datasheet figures, showing the significance of the presented measurement method which does not depend on the type of measured noise.