Gel-based Electrodes Research Articles

Benchtop Performance of Novel Mixed Ionic-Electronic Conductive Electrode Form Factors for Biopotential Recordings.

Background: Traditional gel-based (wet) electrodes for biopotential recordings have several shortcomings that limit their practicality for real-world measurements. Dry electrodes may improve usability, but they often suffer from reduced signal quality. We sought to evaluate the biopotential recording properties of a novel mixed ionic-electronic conductive (MIEC) material for improved performance. Methods: We fabricated four MIEC electrode form factors and compared their signal recording properties to two control electrodes, which are electrodes commonly used for biopotential recordings (Ag-AgCl and stainless steel). We used an agar synthetic skin to characterize the impedance of each electrode form factor. An electrical phantom setup allowed us to compare the recording quality of simulated biopotentials with ground-truth sources. Results: All MIEC electrode form factors yielded impedances in a similar range to the control electrodes (all <80 kΩ at 100 Hz). Three of the four MIEC samples produced similar signal-to-noise ratios and interfacial charge transfers as the control electrodes. Conclusions: The MIEC electrodes demonstrated similar and, in some cases, better signal recording characteristics than current state-of-the-art electrodes. MIEC electrodes can also be fabricated into a myriad of form factors, underscoring the great potential this novel material has across a wide range of biopotential recording applications.

Pristine cobalt humic acid xerogels embedded with ultrafine cobalt sulfide for enhanced and stable lithium-ion storage

The electrochemical performance of pristine metal–organic xerogels as anodes in lithium-ion batteries is reported for the first time. We propose a novel synthesis approach for the in situ generation of highly dispersed, ultrafine cobalt sulfide nanoparticles on humic acid gels (CoSHA). The CoS nanoparticles in CoSHA have an average diameter of approximately 3 nm. CoSHA electrodes demonstrate enhanced lithium storage capacity, delivering a capacity of 662 mAh g−1 at 0.1 A g−1. They also show stable long-term cycling performance, with no capacity decay after 900 cycles at 1.0 A g−1. Furthermore, our experiments indicate that the improved lithium-ion adsorption results from the oxygen-containing functional groups in humic acid and the ultrafine CoS active sites. This study offers a practical methodology for synthesizing ultrafine metal sulfides and new insights into using pristine gel-based electrodes for energy storage and conversion.

Simultaneous Dry and Gel-Based High-Density Electroencephalography Recordings.

Evaluations of new dry, high-density EEG caps have only been performed so far with serial measurements and not with simultaneous (parallel) measurements. For a first comparison of gel-based and dry electrode performance in simultaneous high-density EEG measurements, we developed a new EEG cap comprising 64 gel-based and 64 dry electrodes and performed simultaneous measurements on ten volunteers. We analyzed electrode-skin impedances, resting state EEG, triggered eye blinks, and visual evoked potentials (VEPs). To overcome the issue of different electrode positions in the comparison of simultaneous measurements, we performed spatial frequency analysis of the simultaneously measured EEGs using spatial harmonic analysis (SPHARA). The impedances were 516 ± 429 kOhm (mean ± std) for the dry electrodes and 14 ± 8 kOhm for the gel-based electrodes. For the dry EEG electrodes, we obtained a channel reliability of 77%. We observed no differences between dry and gel-based recordings for the alpha peak frequency and the alpha power amplitude, as well as for the VEP peak amplitudes and latencies. For the VEP, the RMSD and the correlation coefficient between the gel-based and dry recordings were 1.7 ± 0.7 μV and 0.97 ± 0.03, respectively. We observed no differences in the cumulative power distributions of the spatial frequency components for the N75 and P100 VEP peaks. The differences for the N145 VEP peak were attributed to the different noise characteristics of gel-based and dry recordings. In conclusion, we provide evidence for the equivalence of simultaneous dry and gel-based high-density EEG measurements.

Flexible and Scalable Dry Conductive Elastomeric Nanocomposites for Surface Stimulation Applications.

The study describes the development and testing of a dry surface stimulation flexible electrode (herein referred to as Flexatrode), a low-cost, flexible, and scalable elastomeric nanocomposite using carbon black (CB) and polydimethylsiloxane (PDMS). Flexatrodes composed of CB and PDMS were developed and tested for mechanical and functional stability up to 7 days. Uniform CB distribution was achieved by optimizing the dispersion process using toluene and methyl-terminated PDMS. Electromechanical testing in the through thickness directions over a long-term duration demonstrated stability of Flexatrode. Thermal stability of Flexatrode for up to a week was tested and validated, thus mitigating concerns of heat generation and deleterious skin reactions such as vasodilation or erythema. 25 wt.% CB was determined to be the optimal concentration. Electrical and thermal stability were demonstrated in the through thickness direction. Flexatrode provides stable electrical properties combined with high flexibility and elasticity. Electrotherapy treated chronic wounds were 81.9% smaller than baseline at day 10. Wounds that received an inactive device (device without any electrical stimulation) were 58.1% smaller than baseline and wounds that received standard of care treatment were 62.2% smaller than baseline. The increasing need for wearable bioelectronics requiring long-term monitoring/treatment has highlighted the limitations of sustained use of gel-based electrodes. These can include skin irritation, bacterial overgrowth at the electrode site, gel dehydration over time, and signal degradation due to eccrine sweat formation. Flexatrode provides stable performance in a nanocomposite with scalable fabrication, thus providing a promising platform technology for wearable bioelectronics.

Environmentally Adaptable Organo-Ionic Gel-Based Electrodes for Real-Time On-Skin Electrocardiography Monitoring.

On-skin personal electrocardiography (ECG) devices, which can monitor real-time cardiac autonomic changes, have been widely applied to predict cardiac diseases and save lives. However, current interface electrodes fail to be unconditionally and universally applicable, often losing their efficiency and functionality under harsh atmospheric conditions (e.g., underwater, abnormal temperature, and humidity). Herein, an environmentally adaptable organo-ionic gel-based electrode (OIGE) is developed with a facile one-pot synthesis of highly conductive choline-based ionic liquid ([DMAEA-Q] [TFSI], I.L.) and monomers (2,2,2-trifluoroethyl acrylate (TFEA) and N-hydroxyethyl acrylamide (HEAA). In virtue of inherent conductivity, self-responsive hydrophobic barriers, dual-solvent effect, and multiple interfacial interactions, this OIGE features distinct sweat and water-resistance, anti-freezing and anti-dehydration properties with strong adhesiveness and electrical stability under all kinds of circumstances. In contrast to the dysfunction of commercial gel electrodes (CGEs), this OIGE with stronger adhesion as well as skin tolerability can realize a real-time and accurate collection of ECG signals under multiple extreme conditions, including aquatic environments (sweat and underwater), cryogenic (<-20°C) and arid (dehydration) environments. Therefore, the OIGE shows great prospects in diagnosing cardiovascular diseases and paves new horizons for multi-harsh environmental personalizedhealthcare.

Extraction of Individual EEG Gamma Frequencies from the Responses to Click-Based Chirp-Modulated Sounds.

Activity in the gamma range is related to many sensory and cognitive processes that are impaired in neuropsychiatric conditions. Therefore, individualized measures of gamma-band activity are considered to be potential markers that reflect the state of networks within the brain. Relatively little has been studied in respect of the individual gamma frequency (IGF) parameter. The methodology for determining the IGF is not well established. In the present work, we tested the extraction of IGFs from electroencephalogram (EEG) data in two datasets where subjects received auditory stimulation consisting of clicks with varying inter-click periods, covering a 30-60 Hz range: in 80 young subjects EEG was recorded with 64 gel-based electrodes; in 33 young subjects, EEG was recorded using three active dry electrodes. IGFs were extracted from either fifteen or three electrodes in frontocentral regions by estimating the individual-specific frequency that most consistently exhibited high phase locking during the stimulation. The method showed overall high reliability of extracted IGFs for all extraction approaches; however, averaging over channels resulted in somewhat higher reliability scores. This work demonstrates that the estimation of individual gamma frequency is possible using a limited number of both the gel and dry electrodes from responses to click-based chirp-modulated sounds.

Isopropanol-regulated adhesion-controllable conductive gels for robust bioelectric signal monitoring and flexible underwater robots

Flexible gel-based electrodes that can efficiently collect and conduct weak voltages or currents have been used to acquire human bioelectrical signals, thereby demonstrating significant potential for health management and telemedicine. Stable and reliable monitoring of electrocardiograms in an aqueous environment (sweating, swimming, or working underwater) remains a challenge, although it has been successfully achieved in air. In this study, conductive gels with high adhesion strengths were fabricated via isopropanol-softening polymer chains. Isopropanol endows softer gels with low cross-linked networks, promoting gel deformation and polymer chain movement under pressure. Ultimately, strengthened mechanical interlocking and a seamless adhesion interface were formed. The gel showed substantial adhesion strengths on various substrates (22.89, 23.46, and 30.50 kPa on porcine skin, polymethyl methacrylate, and fabrics, respectively). Under hydrophobic interactions of butyl acrylate, gels can also firmly adhere to underwater substrates with adhesion energies of 33.88, 33.15, and 37.21 J/m2 on polymethyl methacrylate, polyvinyl chloride, and polycarbonate, respectively. Acrylic acid provides gels with intrinsic conductivity without the addition of other conductive materials. The considerable adhesion and interface impedance enable gels to collect continuous and reliable electrocardiogram signals, demonstrating significant promise for health monitoring and robotic arms.

Generalizable Deep Learning-based Sleep Staging Approach for Ambulatory Textile Electrode Headband Recordings.

Reliable, automated, and user-friendly solutions for the identification of sleep stages in home environment are needed in various clinical and scientific research settings. Previously we have shown that signals recorded with an easily applicable textile electrode headband (FocusBand, T 2 Green Pty Ltd) contain characteristics similar to the standard electrooculography (EOG, E1-M2). We hypothesize that the electroencephalographic (EEG) signals recorded using the textile electrode headband are similar enough with standard EOG in order to develop an automatic neural network-based sleep staging method that generalizes from diagnostic polysomnographic (PSG) data to ambulatory sleep recordings of textile electrode-based forehead EEG. Standard EOG signals together with manually annotated sleep stages from clinical PSG dataset (n = 876) were used to train, validate, and test a fully convolutional neural network (CNN). Furthermore, ambulatory sleep recordings including a standard set of gel-based electrodes and the textile electrode headband were conducted for 10 healthy volunteers at their homes to test the generalizability of the model. In the test set (n = 88) of the clinical dataset, the model's accuracy for 5-stage sleep stage classification was 80% (κ = 0.73) using only the single-channel EOG. The model generalized well for the headband-data, reaching 82% (κ = 0.75) overall sleep staging accuracy. In comparison, accuracy of the model was 87% (κ = 0.82) in home recordings using the standard EOG. In conclusion, the CNN model shows potential on automatic sleep staging of healthy individuals using a reusable electrode headband in a home environment.

The single-channel dry electrode SSVEP-based biometric approach: data augmentation techniques against overfitting for RNN-based deep models.

Biometric studies based on electroencephalography (EEG) have received increasing attention because each individual has a dynamic and unique pattern. However, classic EEG-based biometrics have significant deficiencies, including noise-prone signals, gel-based electrodes, and the need for multi-training/multi-channel acquisition and high mental effort. In contrast, steady-state visually evoked potential (SSVEP)-based biometrics have the important advantages of high signal-to-noise ratio and untrained usage. Dynamic brain potential responses are a natural subconscious activity and can be elicited by flickering lights having distinct frequencies, such as cell phone flashes, without extra physical or mental effort. Few studies involving multi-channel/multi-trial SSVEP-based biometric research are available in the current literature. Moreover, there is a lack of research comparing them to the single-channel single-trial dry electrode-implemented SSVEP-based biometric approach using Recurrent Neural Networks (RNN). Furthermore, to the best of our knowledge, no prior work has proposed an SSVEP-based biometric comparison of the RNNs using data augmentation strategies against overfitting. It was observed that the biometric recognition results were promising, achieving up to 100% accuracy and > 97% sensitivity and specificity scores for 11 subjects. F-scores were also yielded as > 97% values. This single-channel SSVEP-based biometric approach using RNN deep models may offer low-cost, user-friendly, and reliable individual identification authentication, leading to significant application domains.

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps.

Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain–computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators. We conducted a multi-center and multi-operator study validating multipin dry electrodes to study the reproducibility and generalizability of their performance in different environments and for different operators. Moreover, we aimed to study the interrelation of operator experience, preparation time, and wearing comfort on the EEG signal quality. EEG acquisitions using dry and gel-based EEG caps were carried out in 6 different countries with 115 volunteers, recording electrode-skin impedances, resting state EEG and evoked activity. The dry cap showed average channel reliability of 81% but higher average impedances than the gel-based cap. However, the dry EEG caps required 62% less preparation time. No statistical differences were observed between the gel-based and dry EEG signal characteristics in all signal metrics. We conclude that the performance of the dry multipin electrodes is highly reproducible, whereas the primary influences on channel reliability and signal quality are operator skill and experience.

A highly stable electrode with low electrode-skin impedance for wearable brain-computer interface

To date, brain-computer interfaces (BCIs) have proved to play a key role in many medical applications, for example, the rehabilitation of stroke patients. For post-stroke rehabilitation, the BCIs require the EEG electrodes to precisely translate the brain signals of patients into intended movements of the paralyzed limb for months. However, the gold standard silver/silver-chloride electrodes cannot satisfy the requirements for long-term stability and preparation-free recording capability in wearable EEG devices, thus limiting the versatility of EEG in wearable BCI applications over time outside the rehabilitation center. Here, we design a long-term stable and low electrode-skin interfacial impedance conductive polymer-hydrogel EEG electrode that maintains a lower impedance value than gel-based electrodes for 29 days. With this technology, EEG-based long-term and wearable BCIs could be realized in the near future. To demonstrate this, our designed electrode is applied for a wireless single-channel EEG device that detects changes in alpha rhythms in eye-open/eye-close conditions. In addition, we validate that the designed electrodes could capture oscillatory rhythms in motor imagery protocols as well as low-frequency time-locked event-related potentials from healthy subjects, with similar or better performance than gel-based electrodes. Finally, we demonstrate the use of the designed electrode in online BCI-based functional electrical stimulation, which could be used for post-stroke rehabilitation.

Novel replaceable EEG electrode system

Abstract Due to the direct contact between electrode and scalp, dry EEG electrodes are exposed to increased mechanical wear compared to conventional gel-based electrodes. However, state-of-the-art commercial cap systems commonly use permanently fixated electrodes which can lead to downtime of the EEG cap during professional repair and replacement as well as reduced overall lifetime. An easily replaceable EEG electrode would furthermore improve hygiene, especially for newborn and infant applications. We propose a novel replaceable electrode system, consisting of an electrode holder, a snap top, a contact ring fixated inside the electrode holder, and a replaceable electrode. The production process consists of 3D printing, silicone molding, resin casting, and electroless plating. The replaceable electrode system is integrated into a multichannel EEG cap system. A verification study is conducted with 30 volunteers. The operators experienced that the new electrode holder eases adjustment of the electrode to have proper contact with the scalp. During the study, defective electrodes can be replaced without a soldering process. Furthermore, all electrodes stayed in the holder and did not fall off the cap for the whole session. In conclusion, the novel replaceable electrode system is suitable for EEG measurements.

Development and Characterization of Embroidery-Based Textile Electrodes for Surface EMG Detection

The interest in wearable devices has expanded to measurement devices for building IoT-based mobile healthcare systems and sensing bio-signal data through clothing. Surface electromyography, called sEMG, is one of the most popular bio-signals that can be applied to health monitoring systems. In general, gel-based (Ag/AgCl) electrodes are mainly used, but there are problems, such as skin irritation due to long-time wearing, deterioration of adhesion to the skin due to moisture or sweat, and low applicability to clothes. Hence, research on dry electrodes as a replacement is increasing. Accordingly, in this study, a textile-based electrode was produced with a range of electrode shapes, and areas were embroidered with conductive yarn using an embroidery technique in the clothing manufacturing process. The electrode was applied to EMG smart clothing for fitness, and the EMG signal detection performance was analyzed. The electrode shape was manufactured using the circle and wave type. The wave-type electrode was more morphologically stable than the circle-type electrode by up to 30% strain, and the electrode shape was maintained as the embroidered area increased. Skin-electrode impedance analysis confirmed that the embroidered area with conductive yarn affected the skin contact area, and the impedance decreased with increasing area. For sEMG performance analysis, the rectus femoris was selected as a target muscle, and the sEMG parameters were analyzed. The wave-type sample showed higher EMG signal strength than the circle-type. In particular, the electrode with three lines showed better performance than the fill-type electrode. These performances operated without noise, even with a commercial device. Therefore, it is expected to be applicable to the manufacture of electromyography smart clothing based on embroidered electrodes in the future.

Wearable ring bioelectrical impedance analyzer for estimation and monitoring of body fat

The World Health Organization has declared obesity as one of the fastest growing global epidemics. People suffering from obesity are at an increased risk of serious health conditions including stroke, diabetes, high blood pressure, and other chronic diseases caused by excess fat in the body. To study and control this obesity epidemic, precise measurement of the body fat mass is necessary. Bioelectrical impedance analysis (BIA) is a common yet effective method for body composition, especially fat mass, measurement in which the electrical impedance of a human body is measured. Here we report a novel wireless BIA device, in the form of a wearable ring, for estimating the body fat as well as a smartphone application for users to manage and track their health data. The wearable analyzer was compared with an off-the-shelf body fat monitor in terms of performance for 40 healthy volunteers. In addition, the small, dry electrodes used in the ring analyzer are compared with traditional gel-based electrodes. Although the dry electrodes impose a larger skin-electrode contact impedance (5.18 ± 0.655 kΩ) than gel-based electrodes (933.37 ± 40.06 Ω), the designed system provides critical compensation for the higher electrode impedance and the parasitic effects for the dry electrodes. With the compensation implemented, these two types of electrodes are highly correlated with correlation coefficients r = 0.96 for resistance and r = 0.93 for reactance. Body fat estimation equations proposed by four different groups are analyzed and compared using the results from the wearable ring device. Our ring analyzer and the reference monitor demonstrate a linear regression with a strong correlation (r = 0.90) for estimating fat mass. Furthermore, the Bland-Altman plot shows that only 2 out of 40 subjects lie outside the 95% limit of agreement. All these findings show that the ring BIA system is highly portable, easy to use, and with comparable performance to large reference analyzers.

Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator.

Transfer from experiments in the laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. In this study, we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 71.5% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenues toward detecting cognitive failures in real-life situations, such as real flight.

Me-Doped Ti-Me Intermetallic Thin Films Used for Dry Biopotential Electrodes: A Comparative Case Study.

In a new era for digital health, dry electrodes for biopotential measurement enable the monitoring of essential vital functions outside of specialized healthcare centers. In this paper, a new type of nanostructured titanium-based thin film is proposed, revealing improved biopotential sensing performance and overcoming several of the limitations of conventional gel-based electrodes such as reusability, durability, biocompatibility, and comfort. The thin films were deposited on stainless steel (SS) discs and polyurethane (PU) substrates to be used as dry electrodes, for non-invasive monitoring of body surface biopotentials. Four different Ti–Me (Me = Al, Cu, Ag, or Au) metallic binary systems were prepared by magnetron sputtering. The morphology of the resulting Ti–Me systems was found to be dependent on the chemical composition of the films, specifically on the type and amount of Me. The existence of crystalline intermetallic phases or glassy amorphous structures also revealed a strong influence on the morphological features developed by the different systems. The electrodes were tested in an in-vivo study on 20 volunteers during sports activity, allowing study of the application-specific characteristics of the dry electrodes, based on Ti–Me intermetallic thin films, and evaluation of the impact of the electrode–skin impedance on biopotential sensing. The electrode–skin impedance results support the reusability and the high degree of reliability of the Ti–Me dry electrodes. The Ti–Al films revealed the least performance as biopotential electrodes, while the Ti–Au system provided excellent results very close to the Ag/AgCl reference electrodes.

Micromolding fabrication of biocompatible dry micro-pyramid array electrodes for wearable biopotential monitoring

Thin dry electrodes are promising components in wearable healthcare devices. Assessing the condition of the human body by monitoring biopotentials facilitates the early diagnosis of diseases as well as their prevention, treatment, and therapy. Existing clinical-use electrodes have limited wearable-device usage because they use gels, require many preparation steps, and can be uncomfortable to wear. Dry electrodes can improve these issues and have demonstrated performance on par with gel-based electrodes, providing advantages in mobile and wearable applications. However, the materials and fabrication methods used are not yet at the level of disposable gel electrodes for low-cost mass manufacturing and wide adoption. Here, a low-cost manufacturing process for thin dry electrodes with a conductive micro-pyramidal array (MPA) is presented for large-scale on-skin wearable applications. The electrode is fabricated using micromolding techniques in conjunction with solution processes in order to guarantee ease of fabrication, high device yield, and the possibility of mass production compatible with current semiconductor production processes. Fabricated using a conductive paste and an epoxy resin that are both biocompatible, the developed MPA electrode operates in a conformal, non-invasive manner, with low skin irritation, which ensures improved comfort for brief or extended use. The operation of the developed electrode was examined by analyzing electrode-skin-electrode impedance, electroencephalography, electrocardiography, and electromyography signals and comparing them with those measured simultaneously using gel electrodes.

The Arch Electrode: A Novel Dry Electrode Concept for Improved Wearing Comfort.

Electroencephalography (EEG) is increasingly used for repetitive and prolonged applications like neurofeedback, brain computer interfacing, and long-term intermittent monitoring. Dry-contact electrodes enable rapid self-application. A common drawback of existing dry electrodes is the limited wearing comfort during prolonged application. We propose a novel dry Arch electrode. Five semi-circular arches are arranged parallelly on a common baseplate. The electrode substrate material is a flexible thermoplastic polyurethane (TPU) produced by additive manufacturing. A chemical coating of Silver/Silver-Chloride (Ag/AgCl) is applied by electroless plating using a novel surface functionalization method. Arch electrodes were manufactured and validated in terms of mechanical durability, electrochemical stability, in vivo applicability, and signal characteristics. We compare the results of the dry arch electrodes with dry pin-shaped and conventional gel-based electrodes. 21-channel EEG recordings were acquired on 10 male and 5 female volunteers. The tests included resting state EEG, alpha activity, and a visual evoked potential. Wearing comfort was rated by the subjects directly after application, as well as at 30 min and 60 min of wearing. Our results show that the novel plating technique provides a well-adhering electrically conductive and electrochemically stable coating, withstanding repetitive strain and bending tests. The signal quality of the Arch electrodes is comparable to pin-shaped dry electrodes. The average channel reliability of the Arch electrode setup was 91.9 ± 9.5%. No considerable differences in signal characteristics have been observed for the gel-based, dry pin-shaped, and arch-shaped electrodes after the identification and exclusion of bad channels. The comfort was improved in comparison to pin-shaped electrodes and enabled applications of over 60 min duration. Arch electrodes required individual adaptation of the electrodes to the orientation and hairstyle of the volunteers. This initial preparation time of the 21-channel cap increased from an average of 5 min for pin-like electrodes to 15 min for Arch electrodes and 22 min for gel-based electrodes. However, when re-applying the arch electrode cap on the same volunteer, preparation times of pin-shaped and arch-shaped electrodes were comparable. In summary, our results indicate the applicability of the novel Arch electrode and coating for EEG acquisition. The novel electrode enables increased comfort for prolonged dry-contact measurement.

Impact of size and shape for textile surface electromyography electrodes: a study of the biceps brachii muscle

Electromyography is a technique to record and analyze signals from muscle tissue. Commonly, gel-based (Ag/AgCl) electrodes are used to detect muscle action potentials. Current gel-based electrode designs, however, do not perform well under constant movement and therefore are less suitable to monitor muscle behavior under everyday activities. Textile electrodes do well under movement and extended use, but produce weaker signals than their gel-based counterparts. This work points towards a reduction of this performance gap when the textile electrodes are designed to fit the target muscle. Four textile electrodes of different sizes and shapes are tested on the biceps brachii of 13 subjects. Signal parameters such as the signal-to-noise ratio and voltage root-mean-square are used to determine the quality of the myoelectric signals generated by these electrodes. Results with statistically significant differences show that the electrode area and alignment to the muscle fibers affect signal quality and strength. These results indicate that target muscle characteristics should dictate the electrode dimensional parameters to optimize surface electromyography signal acquisition.

Novel dry electrode EEG headbands for home use: Comparing performance and comfort

Abstract Monitoring brain activity at home using electroencephalography (EEG) is an increasing trend for both medical and non-medical applications. Gel-based electrodes are not suitable due to the gel application requiring extensive preparation and cleaning support for the patient or user. Dry electrodes can be applied without prior preparation by the patient or user. We investigate and compare two dry electrode headbands for EEG acquisition: a novel hybrid dual-textile headband comprising multipin and multiwave electrodes and a neoprene-based headband comprising hydrogel and spidershaped electrodes. We compare the headbands and electrodes in terms of electrode-skin impedance, comfort, electrode offset potential and EEG signal quality. We did not observe considerable differences in the power spectral density of EEG recordings. However, the hydrogel electrodes showed considerably increased impedances and offset potentials, limiting their compatibility with many EEG amplifiers. The hydrogel and spider-shaped electrodes required increased adduction, resulting in a lower wearing comfort throughout the application time compared to the novel headband comprising multipin and multiwave electrodes.