Electrode Contact Impedance and Biopotential Signal Quality

Electroencephalography (EEG) is the recording of potential fluctuations originating from electrical activity of brain. It is used in diagnosis of neurological disorders, monitoring the depth of anaesthesia and evaluation of sleep. A possible application is long-term continous monitoring of intensive care unit (ICU) patients, with the aim to detect epileptic seizure activity. Currently this is not practised due to poor usability of the available equipment. This thesis is part of a project which aims to develop a novel solution which solves the usability problem. Adding to that, the solution contains an algorithm for automatic online epileptic seizure detection, which enables immediate treatment of patients once epileptic seizures occur. This leads to an increased patient outcome at ICUs. An important factor contributing to poor usability of current EEG equipment is the electrode contact. To ensure good signal quality, skin under the electrodes needs to be prepared by abrasion for example. This is time-consuming especially when multiple electrodes are used. Adding to that, skin preparation damages skin which is undesired especially in long-term applications, as the the presence of electrode and electrolytic gel causes irritation and possibly an infection risk. The quality of the electrode contact is quantified by its electrical impedance. In this thesis the relationship of electrode contact impedance to total electrode contact noise and motion artifact magnitude are studied. These both are factors contributing to biopotential signal quality. Sintered silver-silverchloride electrodes are used in the work. Contact impedance is defined as the magnitude of the impedance vector at 20 Hz. Contact noise is studied by measuring impedance-noise data pairs (n=122) at two body sites of volunteer subjects using two different electrode gels. A univariate analysis of variance is implemented on the data pairs. Motion artifact magnitude is studied with impedanceartifact magnitude data pairs (n=33) while producing a horizontal motion to the electrode. The behavior of the seizure detection algorithm is also studied by adding different amounts of noise to EEG signals, and assessing how its behavior changes. The results show that electrode contact impedance can be used as a rough predictor of total contact noise. With contact impedance in the range of 20 k or less, the contact noise is expected to settle at RMS values less than 5 μV at a 30 Hz bandwidth. It was also found the that the type of electrolytic gel can have a significant effect on total contact noise. Motion artifact magnitude was found to decrease with decreasing contact impedance. With larger contact impedance values, the variations of motion artifact magnitudes were larger. The behavior of the seizure detection algorithm was found to change significantly with a small amount of noise added to EEG signals. By comparing that amount of noise to the measured contact noise data, it can be seen that it is well within the measured values