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The electroencephalography (EEG) sensor has become a prominent sensor in the study of brain activity. Its applications extend from research studies to medical applications. This review paper explores various types of EEG sensors and their applications. This paper is for an audience that comprises engineers, scientists and clinicians who are interested in learning more about the EEG sensors, the various types, their applications and which EEG sensor would suit a specific task. The paper also lists the details of each of the sensors currently available in the market, their technical specs, battery life, and where they have been used and what their limitations are.

Introduction We investigated the between‐subject variability of EEG (electroencephalography) electrode placement from a simultaneously recorded EEG‐fMRI (functional magnetic resonance imaging) dataset. Methods Neuro‐navigation software was used to localize electrode positions, made possible by the gel artifacts present in the structural magnetic resonance images. To assess variation in the brain regions directly underneath electrodes we used MNI coordinates, their associated Brodmann areas, and labels from the Harvard‐Oxford Cortical Atlas. We outline this relatively simple pipeline with accompanying analysis code. Results In a sample of 20 participants, the mean standard deviation of electrode placement was 3.94 mm in x, 5.55 mm in y, and 7.17 mm in z, with the largest variation in parietal and occipital electrodes. In addition, the brain regions covered by electrode pairs were not always consistent; for example, the mean location of electrode PO7 was mapped to BA18 (secondary visual cortex), whereas PO8 was closer to BA19 (visual association cortex). Further, electrode C1 was mapped to BA4 (primary motor cortex), whereas C2 was closer to BA6 (premotor cortex). Conclusions Overall, the results emphasize the variation in electrode positioning that can be found even in a fixed cap. This may be particularly important to consider when using EEG positioning systems to inform non‐invasive neurostimulation. We examined the variability of EEG (electroencephalography) electrode positions and their underlying brain regions by visualizing gel artifacts that arise on structural brain images in simultaneous EEG‐fMRI (functional magnetic resonance imaging). We observed that the scalp and cortical locations of parietal and occipital electrodes had the greatest between‐subject variability. We provide insight into the brain regions that lie underneath fixed cap electrodes in MNI space, with the notable finding that brain regions covered by electrode pairs are not always homologous.

Despite the progress in the development of innovative EEG acquisition systems, their use in dynamic applications is still limited by motion artifacts compromising the interpretation of the collected signals. Therefore, extensive research on the genesis of motion artifacts in EEG recordings is still needed to optimize existing technologies, shedding light on possible solutions to overcome the current limitations. We identified three potential sources of motion artifacts occurring at three different levels of a traditional biopotential acquisition chain: the skin-electrode interface, the connecting cables between the detection and the acquisition systems, and the electrode-amplifier system. The identified sources of motion artifacts were modelled starting from experimental observations carried out on EEG signals. Consequently, we designed customized EEG electrode systems aiming at experimentally disentangling the possible causes of motion artifacts. Both analytical and experimental observations indicated two main residual sites responsible for motion artifacts: the connecting cables between the electrodes and the amplifier and the sudden changes in electrode-skin impedance due to electrode movements. We concluded that further advancements in EEG technology should focus on the transduction stage of the biopotentials amplification chain, such as the electrode technology and its interfacing with the acquisition system.

Currently, the electroencephalogram (EEG) cap is limited to a finite number of sizes based on head circumference, lacking the mechanical flexibility to accommodate the full range of skull dimensions. This reliance on head circumference data alone often results in a poor fit between the EEG cap and the user’s head shape. To address these limitations, we have developed a four-dimensional (4D) adjustable EEG cap. This cap features an adjustable mechanism that covers the entire cranial area in four dimensions, allowing it to fit the head shapes of nearly all adults. The system is compatible with 64 channels or lower electrode counts. We conducted a study with numerous volunteers to compare the performance characteristics of the 4D caps with the commercial (COML) caps in terms of contact pressure, preparation time, wearing impedance, and performance in brain–computer interface (BCI) applications. The 4D cap demonstrated the ability to adapt to various head shapes more quickly, reduce impedance during testing, and enhance measurement accuracy, signal-to-noise ratio (SNR), and comfort. These improvements suggest its potential for broader application in both laboratory settings and daily life.

Electroencephalography (EEG) data recorded during simultaneous EEG-fMRI experiments are contaminated by large gradient artifacts (GA). The amplitude of the GA depends on the area of the wire loops formed by the EEG leads, as well as on the rate of switching of the magnetic field gradients, which are essential for MR imaging. Average artifact subtraction (AAS), the most commonly used method for GA correction, relies on the EEG amplifier having a large enough dynamic range to characterize the artifact voltages. Low-pass filtering (250 Hz cut-off) is generally used to attenuate the high-frequency voltage fluctuations of the GA, but even with this precaution channel saturation can occur, particularly during acquisition of high spatial resolution MRI data. Previous work has shown that the ribbon cable, used to connect the EEG cap and amplifier, makes a significant contribution to the GA, since the cable geometry produces large effective wire-loop areas. However, by appropriately connecting the wires of the ribbon cable to the EEG cap it should be possible to minimize the overall range and root mean square (RMS) amplitude of the GA by producing partial cancelation of the cap and cable contributions. Here by modifying the connections of the EEG cap to a 1 m ribbon cable we were able to reduce the range of the GA for a high-resolution coronal echo planar Imaging (EPI) acquisition by a factor of ∼ 1.6 and by a factor of ∼ 1.15 for a standard axial EPI acquisition. These changes could potentially be translated into a reduction in the required dynamic range, an increase in the EEG bandwidth or an increase in the achievable image resolution without saturation, all of which could be beneficially exploited in EEG-fMRI studies. The re-wiring could also prevent the system from saturating when small subject movements occur using the standard recording bandwidth.

Emotions are fundamental to human life and can impact elderly healthcare encounters between caregiver and patient. Detecting emotions by monitoring the physical signals with wearable smart devices offers new promises for care support. While there are multiple studies on wearable devices, few of these pertain to soft electroencephalogram (EEG) caps designed for long-time wear by elderly people. In this study, a 4-channel textile cap was designed with dry electrodes held by an ultra-soft gel holder, while fashion and ergonomic design features were introduced to enhance wearability and comfort. The dry-electrode textile cap performed highly for monitoring EEG signals; closely matching the wet electrodes equipment. All participants reported positive feedback stating that the textile cap was softer, lighter, and more comfortable than other devices. A cumulative contribution rate of 72.199% for two factors (materials properties factor and design pattern factor) was achieved using the principal factor method (PFA), which are influencing the usability of the wearable devices. An average emotion classification accuracy of 81.32% was obtained from 5 healthy elderly subjects. It was thus concluded that the proposed method provides a stable monitoring and comfortable user experience for users, and can be used to detect emotions for elderly people with good results in the future.

The curtain of technical limitations impeding rat multichannel non-invasive electroencephalography (EEG) has risen. Given the importance of this preclinical model, development and validation of EEG source imaging (ESI) is essential. We investigate the validity of well-known human ESI methodologies in rats which individual tissue geometries have been approximated by those extracted from an MRI template, leading also to imprecision in electrode localizations. With the half and fifth sensitivity volumes we determine both the theoretical minimum electrode separation for non-redundant scalp EEG measurements and the electrode sensitivity resolution, which vary over the scalp because of the head geometry. According to our results, electrodes should be at least ~3 to 3.5 mm apart for an optimal configuration. The sensitivity resolution is generally worse for electrodes at the boundaries of the scalp measured region, though, by analogy with human montages, concentrates the sensitivity enough to localize sources. Cramér–Rao lower bounds of source localization errors indicate it is theoretically possible to achieve ESI accuracy at the level of anatomical structures, such as the stimulus-specific somatosensory areas, using the template. More validation for this approximation is provided through the comparison between the template and the individual lead field matrices, for several rats. Finally, using well-accepted inverse methods, we demonstrate that somatosensory ESI is not only expected but also allows exploring unknown phenomena related to global sensory integration. Inheriting the advantages and pitfalls of human ESI, rat ESI will boost the understanding of brain pathophysiological mechanisms and the evaluation of ESI methodologies, new pharmacological treatments and ESI-based biomarkers.

Abstract Attention deficit hyperactivity disorder (ADHD) is commonly associated with sleep problems, possibly due to shared pathophysiology. Microstructural sleep electroencephalographic (EEG) alterations may likely represent markers of disordered cortical maturation in ADHD, although literature data are still conflicting, deserving further assessment. After having systematically reviewed the literature, we included 11 studies from 598 abstracts, and assessed 23 parameters of cyclic alternating pattern (CAP), four parameters of sleep EEG power and one parameter of sleep graphoelements through 29 meta-analyses and, when possible, univariate meta-regressions. Slow wave activity (SWA) in ADHD was significantly higher in early childhood and lower in late childhood/adolescence compared to controls, with an inversion point at 10 years. Total CAP rate and CAP A1 index in non-rapid eye movement (NREM) stage 2 sleep, and CAP A1 rate in NREM sleep were significantly lower in ADHD patients than controls. SWA and CAP A1 changes are therefore possible markers of altered cortical maturation in ADHD, consistently with the neuropsychological deficits characterizing the disorder, likely fostering earlier detection of at-risk/milder conditions, and more tailored therapeutic interventions.

This study investigates the feasibility of a dry electrode cap design for neonatal electroencephalogram (EEG) recordings. Recordings on a phantom and a real infant are compared between a novel dry electrode cap and a clinically used gel-based electrode cap. The phantom recordings included measuring both the electrode contact force and the signal quality during still and respiration-like head motion. The real infant recordings were assessed for the EEG signals’ spectral characteristics, including powerline interference. Compared to gel-based caps, the dry caps showed a largely comparable skin force, an expectedly greater sensitivity to motion-induced artifacts, and a slightly lower powerline interference. Recordings on the real infant showed no significant skin marks after using the dry electrode, and the spectral compositions were comparable between dry- and gel-based electrode caps. These findings suggest that neonatal EEG recordings with a dry electrode cap are technically feasible, but movement-related artifacts, such as respiration in a supine lying infant, may challenge long-term recordings of spontaneous EEG activity. Yet, the ease of use of dry electrode caps calls for future studies to define the optimal use case in neonatal recordings.