Project: EOGee – Hardware Noise Analysis

Having previously improved the drift performance of EOGlass, I decided to look a little into the sources of noise. It’s pretty clear that there is a lot of noise on the signal.

Noise on the signal

It’s actually pretty tricky to know exactly what is noise, given that I don’t really know exactly what my eyes were supposed to be doing and, even if I did, the eyes often make micro-saccades that the conscious brain isn’t aware of. If I zoom into a section that looks like I was keeping my eye relatively still, the noise turns out to be about 60 ADC counts peak-to-peak. This is equivalent to approximately 21863nVpkpk, when referred to the input (ie before amplification) (12-bit ADC, 3.3V range, gain of 2211).

I wanted to know how much of this noise was coming from the hardware, and how much was coming from the user. For this I decided to analyse the noise contributions from each stage of the signal chain. Texas Instruments have a good application note on noise analysis.

Continue reading “Project: EOGee – Hardware Noise Analysis”

Project: EOGee – EOGlass Drift Reduction

In a previous article I showed how the bias current of the AD8226 amplifier was causing a 20nV current to flow through the electrodes resulting in a large voltage offset due to the impedance mismatch between the left and right electrodes. This resulted in a large drift in the signal due to changes in impedance between the user and electrodes as they moved or sweated, which often saturated the ADC. I built a test board and showed how this could be reduced by a factor of about 1000x by using the AD8220 which has a bias current of less than 10pA.

Continue reading “Project: EOGee – EOGlass Drift Reduction”