Conventional gel electrodes are widely used for biopotential measurements, despite important drawbacks such as skin irritation, long set-up time and uncomfortable removal. Recently introduced dry electrodes with rigid metal pins overcome most of these problems; however, their rigidity causes discomfort and pain. This paper presents dry electrodes offering high user comfort, since they are fabricated from EPDM rubber containing various additives for optimum conductivity, flexibility and ease of fabrication. The electrode impedance is measured on phantoms and human skin. After optimization of the polymer composition, the skin-electrode impedance is only ~10 times larger than that of gel electrodes. Therefore, these electrodes are directly capable of recording strong biopotential signals such as ECG while for low-amplitude signals such as EEG, the electrodes need to be coupled with an active circuit. EEG recordings using active polymer electrodes connected to a clinical EEG system show very promising results: alpha waves can be clearly observed when subjects close their eyes, and correlation and coherence analyses reveal high similarity between dry and gel electrode signals. Moreover, all subjects reported that our polymer electrodes did not cause discomfort. Hence, the polymer-based dry electrodes are promising alternatives to either rigid dry electrodes or conventional gel electrodes.

Wearable EEG solutions allow portability and realtime measurements in uncontrolled conditions. However, for accurate interpretation of the EEG data, it is essential to determine artefact-contaminated data in EEG measurements so that the output is reliable and reproducible. In this paper, two data quality indicator approaches are proposed. The first approach, a pragmatic model, is based on statistical features and data-driven thresholding. The second approach is based on the same set of statistical features, but uses a regression model to predict data quality. The results were validated against EEG data recorded during uncontrolled laboratory and free-living conditions, manually annotated by experts. Both approaches show high accuracy in detecting artefactual data. Training of the two approaches on free-living conditions data showed better generalization when tested on different types of databases, i.e. uncontrolled laboratory and free-living. Although the accuracy in determining artefact-contaminated data is highest when using a window size of 8 seconds, the accuracy drop is minor when using shorter window size, facilitating realtime applications. Data quality indicators using relatively simple statistical features can distinguish with at least 80% accuracy between good and bad data. The two models perform equally across different databases. Complexity of both models allows for implementation in real-time, which is demonstrated using wearable EEG headset system available at IMEC.

Assessing the human affective state using electroencephalography (EEG) have shown good potential but failed to demonstrate reliable performance in real-life applications. Especially if one applies a setup that might impact affective processing and relies on generalized models of affect. Additionally, using subjective assessment of ones affect as ground truth has often been disputed. To shed the light on the former challenge we explored the use of a convenient EEG system with 20 participants to capture their reaction to affective movie clips in a naturalistic setting. Employing state-of-the-art machine learning approach demonstrated that the highest performance is reached when combining linear features, namely symmetry features and single-channel features, with nonlinear ones derived by a multiscale entropy approach. Nevertheless, the best performance, reflected in the highest F1-score achieved in a binary classification task for valence was 0.71 and for arousal 0.62. The performance was 10–20% better compared to using ratings provided by 13 independent raters. We argue that affective self-assessment might be underrated and it is crucial to account for personal differences in both perception and physiological response to affective cues.

Transforming the field of portable noninvasive brain monitoring from cumbersome, inconvenient, and obtrusive sensing systems into new ergonomic, user-friendly solutions requires solid evidence from practice. Multi-modal sensing of brain signals digitized at the sensor level, minimization of noise using active sensors and shielding, and flexible and reconfigurable dry electrodes are essential components of such solutions. Usefulness of these basic ingredients has been demonstrated in several research publications, however deficiencies and prospects of novel brain sensing systems and their components over traditional gel-based systems and their clinical relevance have rarely been discussed. Here, we present the state-of-the-art and illustrate some of the latest developments in imec's wearable brain sensing systems and identify latest research trends and needs. Special emphasis is given to recent technological developments that enable multi-modal wearable brain sensing by combining EEG with functional near infrared spectroscopy and electrical impedance tomography.

Soft, comfortable polymer-based dry electrodes are fabricated. Impedance and biopotential measurements are carried out to compare the performance of conventional gel electrodes with our dry electrodes. The impedance of our dry electrodes is reduced by adding more conductive additives to the polymer material. To further lower the impedance, two skin pretreatment techniques are evaluated regarding their influence on skin impedance. However, these techniques are found to have only temporary beneficial effects. Finally biopotential measurements (both ECG and EEG) are performed using our soft polymer electrodes. The ECG signal acquired with both gel and our polymer electrodes demonstrates high degree of similarity. Therefore, heart beat detection is straightforward. To enable monitoring of EEG signals with smaller amplitudes, our dry electrodes need to be combined with pre-amplifiers. Initial EEG tests show that the alpha waves are clearly identifiable with the dry electrodes when subjects close their eyes. Based on the results, combining with sophisticated signal acquisition electronics, the dry electrodes provide a high user comfort solution for high quality biopotential measurements, even on very hairy skin.

Today conventional gel electrodes are widely used for biopotential measurements (EEG, ECG,..) despite their important drawbacks, such as signal degradation due to gel drying, skin irritation and the time-consuming set-up. Dry electrodes overcome most of these problems, however, the rigidity of the existing metal and Ag/AgCl dry electrodes causes discomfort and pain. In this paper, flexible polymer-based dry electrodes with high user comfort are presented. They are fabricated from EPDM rubber with various additives for optimization of conductivity, flexibility and fabrication yield. The impedance of these electrodes is measured for various signal frequencies on phantoms to test reproducibility, and on human skin to evaluate the electrode-skin impedance variation between subjects. All the subjects reported that our polymer electrodes were not causing discomfort. The polymer electrodes with optimum composition show ~10 times larger normalized impedance than gel electrodes. Tests showed that skin-electrode impedance reduced significantly by skin hydration, but this effect is only temporally. The 10-fold higher impedance of our polymer electrodes allows for an easy recording of strong biopotential signals such as ECG. For weaker signals, like EEG, the electrodes need to be coupled with an active circuit to compensate for their higher impedance. EEG recordings using active dry electrodes combined with a clinical EEG recording system are promising: visual interpretation of the signals revealed clear alpha-waves when subjects close their eyes, and correlation and coherence analyses reveal high similarity between dry and gel electrode signals. Based on the obtained results, the polymer-based dry electrodes are promising alternatives for the rigid dry electrodes in development and the conventional gel electrodes.