The electroencephalogram (EEG) is a non-invasive tool for monitoring the electrical activities of the brain for different applications from clinical and neurological research to brain-computer interface (BCI) platforms. EEG can be acquired by different types of electrodes like wet, dry contact, and capacitive electrodes. Although wet/gel electrodes are the gold standard for EEG recording in clinical applications and for short periods of tests, they are not a preferred option during continuous daily activities and for wearable gadgets. Shortcomings of gel electrodes and the critical role of prompt response after brain stroke, have inspired researchers to design dry electrodes and try to make them more compatible with wearable EEG measurement systems.

Dry EEG electrodes can record the signals through galvanic contact to the scalp skin or capacitively without a direct connection to the skin. The electrode-tissue impedance (ETI) in both types of dry EEG sensory systems is highly associated with the hair-air domain which can cause erroneous measurements due to unknown impedance characteristics of hair, the potential of having heavy motion artefacts in wearable measurement systems, and hair’s static electricity discharge through the system. These effects can potentially lead to long-term blockage and/or heavy baseline drifts in high-gain front-end dry EEG electrode circuits.

The main aim of this study is to evaluate and mitigate the effect of electrostatic noise on dry EEG electrodes. To achieve this, a simulation of an active band-pass filter employing an operational amplifier (op-amp) was conducted. This filter is designed to operate within the EEG frequency band, between 0.72 Hz and 72 Hz. Recognizing the weak nature of EEG signals on the scalp, a gain of 220 was selected.

In addition, a simplified lumped model representing the hair-air domain was integrated into the input stage. This model was applied to both contact and non-contact dry electrodes. To mimic electrostatic noise, the human-body model (HBM) based on the MIL-STD 833 standard was employed. This choice aimed to replicate real-world conditions, ensuring a comprehensive simulation.

After evaluating the designed amplifiers in normal working conditions, simulations were completed to observe the progression from mild disruption to complete signal loss as the injected charge increased. Furthermore, the relationship between the physical properties of the hair-air domain and the duration of the signal disruption was evaluated. Moreover, to validate the simulation outcomes, the printed circuit board (PCB) layout of the simulated circuits was manufactured and tested. The experiment results are aligned with the simulation results. The electrostatic noise was injected into the circuit using a manufactured electrostatic discharge (ESD) simulator that is capable of injecting charge with MIL-STD 833 standard characteristics.

Once the simulation results of destructive effects of the electrostatic noise were confirmed, compensation measures were devised and implemented on the PCBs to mitigate the impact of electrostatic charges. In dry contact electrodes, a discharge pathway was established to facilitate the dissipation of the charge. For dry non-contact electrodes, the compensation approach encompassed a detection/control unit capable of detecting saturation in the amplification stage, along with a Howland current pump, which, in combination, served to elevate the input baseline and expedite the return to normal operational conditions within a shorter timeframe. The effectiveness of these compensation strategies was subjected to testing and validation using the developed PCB layouts, and the ESD simulator.

Conclusively, a homogenous human head phantom made of gelatine and covered with genuine Remy human hair was used. This setup served to assess the electrodes’ capability to replicate human hair conditions. To introduce electrostatic charges, an IMCS 2600 ESD gun was employed. Subsequently, the dry contact EEG electrode, both with and without compensation techniques, was employed to capture signals and appraise the effectiveness of the designed dissipation path. During the experiments, the signal loss occurred on the contacted EEG electrodes without the compensation strategy, although the duration was comparatively shorter than observed in the PCB circuit experiments. The compensation strategy proved effective, eliminating signal loss entirely by providing a discharge path, as confirmed by the simulation results.

The results of this PhD research introduce a novel method to decrease the signal blockage duration in active dry EEG electrodes, rendering them more viable for integration into wearable biopotential measurement devices.