Towards closed-loop transcranial electrical stimulation: a comparison of methods for real time tES-EEG artefact removal using a phantom head model

Flexible 3D-Printed EEG Electrodes

For electroencephalography (EEG) in haired regions of the head, finger-based electrodes have been proposed in order to part the hair and make a direct contact with the scalp. Previous work has demonstrated 3D-printed fingered electrodes to allow personalisation and different configurations of electrodes to be used for different people or for different parts of the head. This paper presents flexible 3D-printed EEG electrodes for the first time. A flexible 3D printing element is now used, with three different base mechanical structures giving differently-shaped electrodes. To obtain improved sensing performance, the silver coatings used previously have been replaced with a silver/silver-chloride coating. This results in reduced electrode contact impedance and reduced contact noise. Detailed electro-mechanical testing is presented to demonstrate the performance of the operation of the new electrodes, particularly with regards to changes in conductivity under compression, together with on-person tests to demonstrate the recording of EEG signals.

Removal of Gross Artifacts of Transcranial Alternating Current Stimulation in Simultaneous EEG Monitoring

Transcranial electrical stimulation is a widely used non-invasive brain stimulation approach. To date, EEG has been used to evaluate the effect of transcranial Direct Current Stimulation (tDCS) and transcranial Alternating Current Stimulation (tACS), but most studies have been limited to exploring changes in EEG before and after stimulation due to the presence of stimulation artifacts in the EEG data. This paper presents two different algorithms for removing the gross tACS artifact from simultaneous EEG recordings. These give different trade-offs in removal performance, in the amount of data required, and in their suitability for closed loop systems. Superposition of Moving Averages and Adaptive Filtering techniques are investigated, with significant emphasis on verification. We present head phantom testing results for controlled analysis, together with on-person EEG recordings in the time domain, frequency domain, and Event Related Potential (ERP) domain. The results show that EEG during tACS can be recovered free of large scale stimulation artifacts. Previous studies have not quantified the performance of the tACS artifact removal procedures, instead focusing on the removal of second order artifacts such as respiration related oscillations. We focus on the unresolved challenge of removing the first order stimulation artifact, presented with a new multi-stage validation strategy.

Wearable EEG and beyond

The electroencephalogram (EEG) is a widely used non-invasive method for monitoring the brain. It is based upon placing conductive electrodes on the scalp which measure the small electrical potentials that arise outside of the head due to neuronal action within the brain. Historically this has been a large and bulky technology, restricted to the monitoring of subjects in a lab or clinic while they are stationary. Over the last decade much research effort has been put into the creation of "wearable EEG" which overcomes these limitations and allows the long term non-invasive recording of brain signals while people are out of the lab and moving about. This paper reviews the recent progress in this field, with particular emphasis on the electrodes used to make connections to the head and the physical EEG hardware. The emergence of conformal "tattoo" type EEG electrodes is highlighted as a key next step for giving very small and socially discrete units. In addition, new recommendations for the performance validation of novel electrode technologies are given, with standards in this area seen as the current main bottleneck to the wider take up of wearable EEG. The paper concludes by considering the next steps in the creation of next generation wearable EEG units, showing that a wide range of research avenues are present.