Towards real-life EEG applications: novel superporous hydrogel-based semi-dry EEG electrodes enabling automatically "charge-discharge" electrolyte

Biointerface engineering of flexible and wearable electronics

Biointerface sensing is a cutting-edge interdisciplinary field that merges conceptual and practical aspects. Wearable bioelectronics enable efficient interaction and close contact with biological components such as tissues and organs, paving the way for a wide range of medical applications, including personal health monitoring and medical intervention. To be applicable in real-world settings, the patches must be stable and adhere to the skin without causing discomfort or allergies in both wet and dry conditions, as well as other desirable features such as being ultra-soft, thin, flexible, and stretchable. Biosensors have emerged as promising tools primarily used to directly detect biological and electrophysiological signals, enhancing the efficacy of personalized medical treatments and enabling accurate tracking of human well-being. This review highlights the engineering of skin-tissue surfaces/interfaces and their interactions with wearable patches, aiming for both a broad and in-depth understanding of the mechanical and physicochemical properties required for the advancement of flexible and wearable skin patches. Specifically, the advantages of flexible bioelectronics and sensors with optimized surface geometry for long-term diagnosis are discussed. This insight aims to guide the future development of functional materials that can interact with human tissue in a controlled manner. Finally, we provide perspectives on the challenges and potential applications of biointerface engineering in wearable devices.

Technical validation of the Zeto wireless, dry electrode EEG system

Objective.Clinical adoption of innovative EEG technology is contingent on the non-inferiority of the new devices relative to conventional ones. We present the four key results from testing the signal quality of Zeto's WR 19 EEG system against a conventional EEG system conducted on patients in a clinical setting.Methods.We performed 30 min simultaneous recordings using the Zeto WR 19 (zEEG) and a conventional clinical EEG system (cEEG) in a cohort of 15 patients. We compared the signal quality between the two EEG systems by computing time domain statistics, waveform correlation, spectral density, signal-to-noise ratio and signal stability.Results.All statistical comparisons resulted in signal quality non-inferior relative to cEEG. (i) Time domain statistics, including the Hjorth parameters, showed equivalence between the two systems, except for a significant reduction of sensitivity to electric noise in zEEG relative to cEEG. (ii) The point-by-point waveform correlation between the two systems was acceptable (r > 0.6; P < 0.001). (iii) Each of the 15 datasets showed a high spectral correlation (r > 0.99; P < 0.001) and overlapping spectral density across all electrode positions, indicating no systematic signal distortion. (iv) The mean signal-to-noise ratio (SNR) of the zEEG system exceeded that of the cEEG by 4.82 dB, equivalent to a 16% improvement. (v) The signal stability was maintained through the recordings.Conclusion.In terms of signal quality, the zEEG system is non-inferior to conventional clinical EEG systems with respect to all relevant technical parameters that determine EEG readability and interpretability. Zeto's WR 19 wireless dry electrode system has signal quality in the clinical EEG space at least equivalent to traditional cEEG recordings.

Novel AIRTrode-based wearable electrode supports long-term, online brain-computer interface operations

Objective.Non-invasive electroencephalograms (EEG)-based brain-computer interfaces (BCIs) play a crucial role in a diverse range of applications, including motor rehabilitation, assistive and communication technologies, holding potential promise to benefit users across various clinical spectrums. Effective integration of these applications into daily life requires systems that provide stable and reliable BCI control for extended periods. Our prior research introduced the AIRTrode, a self-adhesive (A), injectable (I), and room-temperature (RT) spontaneously-crosslinked hydrogel electrode (AIRTrode). The AIRTrode has shown lower skin-contact impedance and greater stability than dry electrodes and, unlike wet gel electrodes, does not dry out after just a few hours, enhancing its suitability for long-term application. This study aims to demonstrate the efficacy of AIRTrodes in facilitating reliable, stable and long-term online EEG-based BCI operations.Approach.In this study, four healthy participants utilized AIRTrodes in two BCI control tasks-continuous and discrete-across two sessions separated by six hours. Throughout this duration, the AIRTrodes remained attached to the participants' heads. In the continuous task, participants controlled the BCI through decoding of upper-limb motor imagery (MI). In the discrete task, the control was based on decoding of error-related potentials (ErrPs).Main Results.Using AIRTrodes, participants demonstrated consistently reliable online BCI performance across both sessions and tasks. The physiological signals captured during MI and ErrPs tasks were valid and remained stable over sessions. Lastly, both the BCI performances and physiological signals captured were comparable with those from freshly applied, research-grade wet gel electrodes, the latter requiring inconvenient re-application at the start of the second session.Significance.AIRTrodes show great potential promise for integrating non-invasive BCIs into everyday settings due to their ability to support consistent BCI performances over extended periods. This technology could significantly enhance the usability of BCIs in real-world applications, facilitating continuous, all-day functionality that was previously challenging with existing electrode technologies.

Hydrogels in wearable neural interfaces

The integration of wearable neural interfaces (WNIs) with the human nervous system has marked a significant progression, enabling progress in medical treatments and technology integration. Hydrogels, distinguished by their high-water content, low interfacial impedance, conductivity, adhesion, and mechanical compliance, effectively address the rigidity and biocompatibility issues common in traditional materials. This review highlights their important parameters-biocompatibility, interfacial impedance, conductivity, and adhesiveness-that are integral to their function in WNIs. The applications of hydrogels in wearable neural recording and neurostimulation are discussed in detail. Finally, the opportunities and challenges faced by hydrogels for WNIs are summarized and prospected. This review aims to offer a thorough examination of hydrogel technology's present landscape and to encourage continued exploration and innovation. As developments progress, hydrogels are poised to revolutionize wearable neural interfaces, offering significant enhancements in healthcare and technological applications.

Graphical Abstract

Paintable, Fast Gelation, Highly Adhesive Hydrogels for High-fidelity Electrophysiological Monitoring Wirelessly

High-fidelity wireless electrophysiological monitoring is essential for ambulatory healthcare applications. Soft solid-like hydrogels have received significant attention as epidermal electrodes because of their tissue-like mechanical properties and high biocompatibility. However, it is challenging to develop a hydrogel electrode that provides robust contact and high adhesiveness with glabrous skin and hairy scalp for high-fidelity, continuous electrophysiological signal detection. Here, a paintable, fast gelation, highly adhesive, and conductive hydrogel is engineered for high-fidelity wireless electrophysiological monitoring. The hydrogel, consisting of gelatin, gallic acid, sodium citrate, lithium chloride, glycerol, and Tris-HCl buffer solution exhibits a reversible thermal phase transition capability, which endows it with the attributes of on-skin applicability and fast in situ gelation with 15 s, thereby addressing the aforementioned limitations. The introduction of gallic acid enhances the adhesive properties of the hydrogel, facilitating secure electrode attachment to the skin or hairy scalp. To accentuate the potential applications in at-home electrophysiological health monitoring, the hydrogel electrodes are demonstrated for high-fidelity electrocardiogram recording for one hour during various daily activities, as well as in simultaneous electroencephalogram and electrocardiogram recording during a 30 min nap.

Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation

The global rise in lower limb amputation cases necessitates advancements in prosthetic limb technology to enhance the quality of life for affected patients. This review paper explores recent advancements in the integration of EEG and fNIRS modalities for smart lower prosthetic limbs for rehabilitation applications. The paper synthesizes current research progress, focusing on the synergy between brain-computer interfaces and neuroimaging technologies to enhance the functionality and user experience of lower limb prosthetics. The review discusses the potential of EEG and fNIRS in decoding neural signals, enabling more intuitive and responsive control of prosthetic devices. Additionally, the paper highlights the challenges, innovations, and prospects associated with the incorporation of these neurotechnologies in the field of rehabilitation. The insights provided in this review contribute to a deeper understanding of the evolving landscape of smart lower prosthetic limbs and pave the way for more effective and user-friendly solutions in the realm of neurorehabilitation.

Microneedle Array Electrodes Fabricated With 3D Printing Technology for High-Quality Electrophysiological Acquisition

Electrophysiological recordings are vital in assessing biological functions, diagnosing diseases, and facilitating biofeedback and rehabilitation. The applications of conventional wet (gel) electrodes often come with some limitations. Microneedle array electrodes (MAEs) present a possible solution for high-quality electrophysiological acquisition, while the prior technologies for MAE fabrication have been either complex, expensive, or incapable of producing microneedles with uniform dimensions. This work employed a projection stereolithography (P μ SL) 3D printing technology to fabricate MAEs with micrometer-level precision. The MAEs were compared with gel and flat electrodes on electrode-skin interface impedance (EII) and performances of EMG and ECG acquisition. The experimental results indicate that the P μ SL 3D printing technology contributed to an easy-to-perform and low-cost fabrication approach for MAEs. The developed MAEs exhibited promising EII and enabled a stable EMG and ECG acquisition in different conditions without inducing skin allergies, inflammation, or injuries. This research lies in the development of a type of customizable MAE with considerable biomedical application potentials for ultra-minimally invasive or non-invasive electrophysiological acquisition.

Design, Fabrication, and Evaluation of 3D Biopotential Electrodes and Intelligent Garment System for Sports Monitoring

This study presents the development and evaluation of an innovative intelligent garment system, incorporating 3D knitted silver biopotential electrodes, designed for long-term sports monitoring. By integrating advanced textile engineering with wearable monitoring technologies, we introduce a novel approach to real-time physiological signal acquisition, focusing on enhancing athletic performance analysis and fatigue detection. Utilizing low-resistance silver fibers, our electrodes demonstrate significantly reduced skin-to-electrode impedance, facilitating improved signal quality and reliability, especially during physical activities. The garment system, embedded with these electrodes, offers a non-invasive, comfortable solution for continuous ECG and EMG monitoring, addressing the limitations of traditional Ag/AgCl electrodes, such as skin irritation and signal degradation over time. Through various experimentation, including impedance measurements and biosignal acquisition during cycling activities, we validate the system's effectiveness in capturing high-quality physiological data. Our findings illustrate the electrodes' superior performance in both dry and wet conditions. This study not only advances the field of intelligent garments and biopotential monitoring, but also provides valuable insights for the application of intelligent sports wearables in the future.

Design of an injectable, self-adhesive, and highly stable hydrogel electrode for sleep recording

High-quality and continuous electroencephalogram (EEG) monitoring is desirable for sleep research, sleep monitoring, and the evaluation and treatment of sleep disorders. Existing continuous EEG monitoring technologies suffer from fragile connections, long-term stability, and complex preparation for electrodes under real-life conditions. Here, we report an injectable and spontaneously cross-linked hydrogel electrode for long-term EEG applications. Specifically, our electrodes have a long-term low impedance on hairy scalp regions of 17.53 kΩ for more than 8 h of recording, high adhesiveness on the skin of 0.92 N cm-1 with repeated attachment capability, and long-term wearability during daily activities and overnight sleep. In addition, our electrodes demonstrate a superior signal-to-noise-ratio of 23.97 decibels (dB) in comparison with commercial wet electrodes of 17.98 dB and share a high agreement of sleep stage classification with commercial wet electrodes during multichannel recording. These results exhibit the potential of our on-site-formed electrodes for high-quality, prolonged EEG monitoring in various scenarios.

Evaluating and benchmarking the EEG signal quality of high-density, dry MXene-based electrode arrays against gelled Ag/AgCl electrodes

Objective.To evaluate the signal quality of dry MXene-based electrode arrays (also termed 'MXtrodes') for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard.Approach.We placed 4 × 4 MXtrode arrays and gelled Ag/AgCl electrodes on different scalp locations. The scalp was cleaned with alcohol and rewetted with saline before application. We recorded from both electrode types simultaneously while participants performed a vigilance task.Main results.The root mean squared amplitude of MXtrodes was slightly higher than that of Ag/AgCl electrodes (.24-1.94 uV). Most MXtrode pairs had slightly lower broadband spectral coherence (.05 to .1 dB) and Delta- and Theta-band timeseries correlation (.05 to .1 units) compared to the Ag/AgCl pair (p< .001). However, the magnitude of correlation and coherence was high across both electrode types. Beta-band timeseries correlation and spectral coherence were higher between neighboring MXtrodes in the array (.81 to .84 units) than between any other pair (.70 to .75 units). This result suggests the close spacing of the nearest MXtrodes (3 mm) more densely sampled high spatial-frequency topographies. Event-related potentials were more similar between MXtrodes (ρ⩾ .95) than equally spaced Ag/AgCl electrodes (ρ⩽ .77,p< .001). Dry MXtrode impedance (x̄= 5.15 KΩ cm2) was higher and more variable than gelled Ag/AgCl electrodes (x̄= 1.21 KΩ cm2,p< .001). EEG was also recorded on the scalp across diverse hair types.Significance.Dry MXene-based electrodes record EEG at a quality comparable to conventional gelled Ag/AgCl while requiring minimal scalp preparation and no gel. MXtrodes can record independent signals at a spatial density four times higher than conventional electrodes, including through hair, thus opening novel opportunities for research and clinical applications that could benefit from dry and higher-density configurations.

Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces

Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.

Detection of common EEG phenomena using individual electrodes placed outside the hair

Many studies over the past decades have provided exciting evidence that electrical signals recorded from the scalp (electroencephalogram, EEG) hold meaningful information about the brain's function or dysfunction. This information is used routinely in research laboratories to test specific hypotheses and in clinical settings to aid in diagnoses (such as during polysomnography evaluations). Unfortunately, with very few exceptions, such meaningful information about brain function has not yet led to valuable solutions that can address the needs of many people outside such research laboratories or clinics. One of the major hurdles to practical application of EEG-based neurotechnologies is the current predominant requirement to use electrodes that are placed in the hair, which greatly reduces practicality and cosmesis. While several studies reported results using one specific combination of signal/reference electrode outside the hair in one specific context (such as a brain-computer interface experiment), it has been unclear what information about brain function can be acquired using different signal/referencing locations placed outside the hair. To address this issue, in this study, we set out to determine to what extent EEG phenomena related to auditory, visual, cognitive, motor, and sleep function can be detected from different combinations of individual signal/referencing electrodes that are placed outside the hair. The results of our study from 15 subjects suggest that only a few EEG electrodes placed in locations on the forehead or around the ear can provide substantial task-related information in 6 of 7 tasks. Thus, the results of our study provide encouraging evidence and guidance that should invigorate and facilitate the translation of laboratory experiments into practical, useful, and valuable EEG-based neurotechnology solutions.

A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation

Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.

Flexible Electrodes for Brain-Computer Interface System

Brain-computer interface (BCI) has been the subject of extensive research recently. Governments and companies have substantially invested in relevant research and applications. The restoration of communication and motor function, the treatment of psychological disorders, gaming, and other daily and therapeutic applications all benefit from BCI. The electrodes hold the key to the essential, fundamental BCI precondition of electrical brain activity detection and delivery. However, the traditional rigid electrodes are limited due to their mismatch in Young's modulus, potential damages to the human body, and a decline in signal quality with time. These factors make the development of flexible electrodes vital and urgent. Flexible electrodes made of soft materials have grown in popularity in recent years as an alternative to conventional rigid electrodes because they offer greater conformance, the potential for higher signal-to-noise ratio (SNR) signals, and a wider range of applications. Therefore, the latest classifications and future developmental directions of fabricating these flexible electrodes are explored in this paper to further encourage the speedy advent of flexible electrodes for BCI. In summary, the perspectives and future outlook for this developing discipline are provided.

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Electroencephalogram (EEG) records the electrical activity of neurons in the cerebral cortex and is used extensively to diagnose, treat, and monitor psychiatric and neurological conditions. Reliable contact between the skin and the electrodes is essential for achieving consistency and for obtaining electroencephalographic information. There has been an increasing demand for effective equipment and electrodes to overcome the time-consuming and cumbersome application of traditional systems. Recently, ear-centered EEG has met with growing interest since it can provide good signal quality due to the proximity of the ear to the brain. In addition, it can facilitate mobile and unobtrusive usage due to its smaller size and ease of use, since it can be used without interfering with the patient's daily activities. The purpose of this mini-review is to first introduce the broad range of electrodes used in conventional (scalp) EEG and subsequently discuss the state-of-the-art literature about around- and in-the-ear EEG.

Hydrogel electrodes with conductive and substrate-adhesive layers for noninvasive long-term EEG acquisition

Noninvasive brain-computer interfaces (BCIs) show great potential in applications including sleep monitoring, fatigue alerts, neurofeedback training, etc. While noninvasive BCIs do not impose any procedural risk to users (as opposed to invasive BCIs), the acquisition of high-quality electroencephalograms (EEGs) in the long term has been challenging due to the limitations of current electrodes. Herein, we developed a semidry double-layer hydrogel electrode that not only records EEG signals at a resolution comparable to that of wet electrodes but is also able to withstand up to 12 h of continuous EEG acquisition. The electrode comprises dual hydrogel layers: a conductive layer that features high conductivity, low skin-contact impedance, and high robustness; and an adhesive layer that can bond to glass or plastic substrates to reduce motion artifacts in wearing conditions. Water retention in the hydrogel is stable, and the measured skin-contact impedance of the hydrogel electrode is comparable to that of wet electrodes (conductive paste) and drastically lower than that of dry electrodes (metal pin). Cytotoxicity and skin irritation tests show that the hydrogel electrode has excellent biocompatibility. Finally, the developed hydrogel electrode was evaluated in both N170 and P300 event-related potential (ERP) tests on human volunteers. The hydrogel electrode captured the expected ERP waveforms in both the N170 and P300 tests, showing similarities in the waveforms generated by wet electrodes. In contrast, dry electrodes fail to detect the triggered potential due to low signal quality. In addition, our hydrogel electrode can acquire EEG for up to 12 h and is ready for recycled use (7-day tests). Altogether, the results suggest that our semidry double-layer hydrogel electrodes are able to detect ERPs in the long term in an easy-to-use fashion, potentially opening up numerous applications in real-life scenarios for noninvasive BCI.

A garment that measures brain activity: proof of concept of an EEG sensor layer fully implemented with smart textiles

This paper presents the first garment capable of measuring brain activity with accuracy comparable to that of state-of-the art dry electroencephalogram (EEG) systems. The main innovation is an EEG sensor layer (i.e., the electrodes, the signal transmission, and the cap support) made entirely of threads, fabrics, and smart textiles, eliminating the need for metal or plastic materials. The garment is connected to a mobile EEG amplifier to complete the measurement system. As a first proof of concept, the new EEG system (Garment-EEG) was characterized with respect to a state-of-the-art Ag/AgCl dry-EEG system (Dry-EEG) over the forehead area of healthy participants in terms of: (1) skin-electrode impedance; (2) EEG activity; (3) artifacts; and (4) user ergonomics and comfort. The results show that the Garment-EEG system provides comparable recordings to Dry-EEG, but it is more susceptible to artifacts under adverse recording conditions due to poorer contact impedances. The textile-based sensor layer offers superior ergonomics and comfort compared to its metal-based counterpart. We provide the datasets recorded with Garment-EEG and Dry-EEG systems, making available the first open-access dataset of an EEG sensor layer built exclusively with textile materials. Achieving user acceptance is an obstacle in the field of neurotechnology. The introduction of EEG systems encapsulated in wearables has the potential to democratize neurotechnology and non-invasive brain-computer interfaces, as they are naturally accepted by people in their daily lives. Furthermore, supporting the EEG implementation in the textile industry may result in lower cost and less-polluting manufacturing processes compared to metal and plastic industries.

Polyvinyl alcohol/polyacrylamide double-network hydrogel-based semi-dry electrodes for robust electroencephalography recording at hairy scalp for noninvasive brain-computer interfaces

Objective.Reliable and user-friendly electrodes can continuously and real-time capture the electroencephalography (EEG) signals, which is essential for real-life brain-computer interfaces (BCIs). This study develops a flexible, durable, and low-contact-impedance polyvinyl alcohol/polyacrylamide double-network hydrogel (PVA/PAM DNH)-based semi-dry electrode for robust EEG recording at hairy scalp.Approach.The PVA/PAM DNHs are developed using a cyclic freeze-thaw strategy and used as a saline reservoir for semi-dry electrodes. The PVA/PAM DNHs steadily deliver trace amounts of saline onto the scalp, enabling low and stable electrode-scalp impedance. The hydrogel also conforms well to the wet scalp, stabilizing the electrode-scalp interface. The feasibility of the real-life BCIs is validated by conducting four classic BCI paradigms on 16 participants.Main results.The results show that the PVA/PAM DNHs with 7.5 wt% PVA achieve a satisfactory trade-off between the saline load-unloading capacity and the compressive strength. The proposed semi-dry electrode exhibits a low contact impedance (18 ± 8.9 kΩ at 10 Hz), a small offset potential (0.46 mV), and negligible potential drift (1.5 ± 0.4μV min^-1). The temporal cross-correlation between the semi-dry and wet electrodes is 0.91, and the spectral coherence is higher than 0.90 at frequencies below 45 Hz. Furthermore, no significant differences are present in BCI classification accuracy between these two typical electrodes.Significance.Based on the durability, rapid setup, wear-comfort, and robust signals of the developed hydrogel, PVA/PAM DNH-based semi-dry electrodes are a promising alternative to wet electrodes in real-life BCIs.

Wearable System Based on Ultra-Thin Parylene C Tattoo Electrodes for EEG Recording

In an increasingly interconnected world, where electronic devices permeate every aspect of our lives, wearable systems aimed at monitoring physiological signals are rapidly taking over the sport and fitness domain, as well as biomedical fields such as rehabilitation and prosthetics. With the intent of providing a novel approach to the field, in this paper we discuss the development of a wearable system for the acquisition of EEG signals based on a portable, low-power custom PCB specifically designed to be used in combination with non-conventional ultra-conformable and imperceptible Parylene-C tattoo electrodes. The proposed system has been tested in a standard rest-state experiment, and its performance in terms of discrimination of two different states has been compared to that of a commercial wearable device for EEG signal acquisition (i.e., the Muse headset), showing comparable results. This first preliminary validation demonstrates the possibility of conveniently employing ultra-conformable tattoo-electrodes integrated portable systems for the unobtrusive acquisition of brain activity.

The Feature, Performance, and Prospect of Advanced Electrodes for Electroencephalogram

Recently, advanced electrodes have been developed, such as semi-dry, dry contact, dry non-contact, and microneedle array electrodes. They can overcome the issues of wet electrodes and maintain high signal quality. However, the variations in these electrodes are still unclear and not explained, and there is still confusion regarding the feasibility of electrodes for different application scenarios. In this review, the physical features and electroencephalogram (EEG) signal performances of these advanced EEG electrodes are introduced in view of the differences in contact between the skin and electrodes. Specifically, contact features, biofeatures, impedance, signal quality, and artifacts are discussed. The application scenarios and prospects of different types of EEG electrodes are also elucidated.

Modeling the Design Characteristics of Woven Textile Electrodes for long-Term ECG Monitoring

An electrocardiograph records the periodic voltage generated by the heart over time. There is growing demand to continuously monitor the ECG for proactive health care and human performance optimization. To meet this demand, new conductive textile electrodes are being developed which offer an attractive alternative to adhesive gel electrodes but they come with their own challenges. The key challenge with textile electrodes is that the relationship between the manufacturing parameters and the ECG measurement is not well understood, making design an iterative process without the ability to prospectively develop woven electrodes with optimized performance. Here we address this challenge by applying the traditional skin-electrode interface circuit model to woven electrodes by constructing a parameterized model of the ECG system. Then the unknown parameters of the system are solved for with an iterative MATLAB optimizer using measured data captured with the woven electrodes. The results of this novel analysis confirm that yarn conductivity and total conductive area reduce skin electrode impedance. The results also indicate that electrode skin pressure and moisture require further investigation. By closing this gap in development, textile electrodes can be better designed and manufactured to meet the demands of long-term ECG capture.

Highly Stretchable, Transparent and Adhesive Ionogel Based on Chitosan-Poly(acrylic acid) Double Networks for Flexible Strain Sensors

A stretchable double-network (DN) ionogel composed of a physically crosslinked network of chitosan (CS) and a chemically crosslinked network of polyacrylic acid (PAA) was prepared in an ionic liquid ([EMIM][OAc]) using a one-step polymerization method. In this ionogel (CS/PAA), the CS and the PAA polymer chains served as backbones, which constructed an interpenetrating DN structure via numerous hydrogen bonds formed through the hydroxyl, amino and carboxyl groups on the polymer chains. The DN structure improves the mechanical properties of the ionogel. Therefore, the CS/PAA DN ionogel exhibited outstanding mechanical performance in many ways: tensile strength up to 2.04 MPa, strain range up to 1046% and the value of toughness up to 8.52 MJ/m³. The ionogel also showed good self-recovery performance, fatigue resistance, ability to work in a broad temperature range (-20~80 °C) and adhesion properties. As a flexible sensor, the CS/PAA DN ionogel showed high strain sensitivity (gauge factor = 6.235). It can sensitively detect human motion (such as joint-bending, vocal fold vibration, walking gait and other human body motions), revealing the practical application potential of flexible electronic devices.

The Difference in Electromyographic Activity While Wearing a Medical Mask in Women with and without Temporomandibular Disorders

Wearing a medical mask influences resting activity of the temporalis anterior and masseter muscles in healthy young women. However, no studies link medical mask-wearing with masticatory muscle activity in patients with temporomandibular disorders (TMDs). Therefore, this study aims to compare electromyographic patterns while wearing a medical mask between women with and without temporomandibular disorders. Based on the Research Diagnostic Criteria for Temporomandibular Disorders, 115 adult women qualified for the study. Participants were divided into the following two groups: diagnosed TMDs (n = 55; mean age: 23.5 ± 2.3 years) and healthy women (n = 60; mean age: 23.7 ± 2.6 years). Examinations of the resting and functional electromyographic activity of the temporalis anterior (TA), superficial masseter (MM), anterior bellies of the digastric muscle (DA), and the middle part of the sternocleidomastoid muscle (SCM) were carried out using the BioEMG III™. Both groups showed statistically significant decreases in resting masticatory muscle activity during medical mask examination compared to no mask measurement. The significant differences in no mask measurement between both groups were noted regarding resting masticatory activity, clenching in the intercuspal position, and clenching on dental cotton rollers. During medical mask examination, women with TMDs showed differences in resting masticatory activity and clenching on dental cotton rollers compared to the healthy group. In all analyzed variables, both groups showed similar electromyographic patterns in the maximum mouth opening measurement during medical mask and no mask examination. A medical mask influences the resting bioelectric activity of the masticatory muscles in women with temporomandibular disorders and healthy women. We observed differences and some similarities in resting and functional electromyographic patterns within masticatory and neck muscles in both groups during medical mask and no mask examination.

Dependence of Skin-Electrode Contact Impedance on Material and Skin Hydration

Dry electrodes offer an accessible continuous acquisition of biopotential signals as part of current in-home monitoring systems but often face challenges of high-contact impedance that results in poor signal quality. The performance of dry electrodes could be affected by electrode material and skin hydration. Herein, we investigate these dependencies using a circuit skin-electrode interface model, varying material and hydration in controlled benchtop experiments on a biomimetic skin phantom simulating dry and hydrated skin. Results of the model demonstrate the contribution of the individual components in the circuit to total impedance and assist in understanding the role of electrode material in the mechanistic principle of dry electrodes. Validation was performed by conducting in vivo skin-electrode contact impedance measurements across ten normative human subjects. Further, the impact of the electrode on biopotential signal quality was evaluated by demonstrating an ability to capture clinically relevant electrocardiogram signals by using dry electrodes integrated into a toilet seat cardiovascular monitoring system. Titanium electrodes resulted in better signal quality than stainless steel electrodes. Results suggest that relative permittivity of native oxide of electrode material come into contact with the skin contributes to the interface impedance, and can lead to enhancement in the capacitive coupling of biopotential signals, especially in dry skin individuals.

Developing Disposable EEG Cap for Infant Recordings at the Neonatal Intensive Care Unit

Long-term EEG monitoring in neonatal intensive care units (NICU) is challenged with finding solutions for setting up and maintaining a sufficient recording quality with limited technical experience. The current study evaluates different solutions for the skin-electrode interface and develops a disposable EEG cap for newborn infants. Several alternative materials for the skin-electrode interface were compared to the conventional gel and paste: conductive textiles (textured and woven), conductive Velcro, sponge, super absorbent hydrogel (SAH), and hydro fiber sheets (HF). The comparisons included the assessment of dehydration and recordings of signal quality (skin interphase impedance and powerline (50 Hz) noise) for selected materials. The test recordings were performed using snap electrodes integrated into a forearm sleeve or a forehead band along with skin-electrode interfaces to mimic an EEG cap with the aim of long-term biosignal recording on unprepared skin. In the hydration test, conductive textiles and Velcro performed poorly. While the SAH and HF remained sufficiently hydrated for over 24 h in an incubator-mimicking environment, the sponge material was dehydrated during the first 12 h. Additionally, the SAH was found to have a fragile structure and was electrically prone to artifacts after 12 h. In the electrical impedance and recording comparisons of muscle activity, the results for thick-layer HF were comparable to the conventional gel on unprepared skin. Moreover, the mechanical instability measured by 1-2 Hz and 1-20 Hz normalized relative power spectrum density was comparable with clinical EEG recordings using subdermal electrodes. The results together suggest that thick-layer HF at the skin-electrode interface is an effective candidate for a preparation-free, long-term recording, with many advantages, such as long-lasting recording quality, easy use, and compatibility with sensitive infant skin contact.

An Efficient Voltammetric Sensor Based on Graphene Oxide-Decorated Binary Transition Metal Oxides Bi2O3/MnO2 for Trace Determination of Lead Ions

Herein we present a facile synthesis of the graphene oxide-decorated binary transition metal oxides of Bi₂O₃ and MnO₂ nanocomposites (Bi₂O₃/MnO₂/GO) and their applications in the voltammetric detection of lead ions (Pb²⁺) in water samples. The surface morphologies, crystal structures, electroactive surface area, and charge transferred resistance of the Bi₂O₃/MnO₂/GO nanocomposites were investigated through the scanning electron microscopy (SEM), power X-ray diffraction (XRD), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) techniques, respectively. The Bi₂O₃/MnO₂/GO nanocomposites were further decorated onto the surface of a glassy carbon electrode (GCE), and Pb²⁺ was quantitatively analyzed by using square-wave anodic stripping voltammetry (SWASV). We explored the effect of the analytical parameters, including deposition potential, deposition time, and solution pH, on the stripping peak current of Pb²⁺. The Bi₂O₃/MnO₂/GO nanocomposites enlarged the electroactive surface area and reduced the charge transferred resistance by significant amounts. Moreover, the synergistic enhancement effect of MnO₂, Bi₂O₃ and GO endowed Bi₂O₃/MnO₂/GO/GCE with extraordinary electrocatalytic activity toward Pb²⁺ stripping. Under optimal conditions, the Bi₂O₃/MnO₂/GO/GCE showed a broad linear detection range (0.01-10 μM) toward Pb²⁺ detection, with a low limit of detection (LOD, 2.0 nM). The proposed Bi₂O₃/MnO₂/GO/GCE electrode achieved an accurate detection of Pb²⁺ in water with good recoveries (95.5-105%).

Homogeneity Characterization of Textile-Integrated Wearable Sensors based on Impedance Spectroscopy

One of the main challenges during the integration of a carbon/polymer-based nanocomposite sensor on textile substrates is the fabrication of a homogeneous surface of the nanocomposite-based thin films, which play a major role in the reproducibility of the sensor. Characterizations are therefore required in every fabrication step to control the quality of the material preparation, deposition, and curing. As a result, microcharacterization methods are more suitable for laboratory investigations, and electrical methods can be easily implemented for in situ characterization within the manufacturing process. In this paper, several textile-based pressure sensors are fabricated at an optimized concentration of 0.3 wt.% of multiwalledcarbon nanotubes (MWCNTs) composite material in PDMS. We propose to use impedance spectroscopy for the characterization of both of the resistive behavior and capacitive behavior of the sensor at several frequencies and under different loads from 50 g to 500 g. The impedance spectra are fitted to a model composed of a resistance in series with a parallel combination of resistance and a constant phase element (CPE). The results show that the printing parameters strongly influence the impedance behavior under different loads. The deviation of the model parameter α of the CPE from the value 1 is strongly dependent on the nonhomogeneity of the sensor. Based on an impedance spectrum measurement followed by parameter extraction, the parameter α can be determined to realize a novel method for homogeneity characterization and in-line quality control of textile-integrated wearable sensors during the manufacturing process.

Ultrasensitive, label-free voltammetric determination of norfloxacin based on molecularly imprinted polymers and Au nanoparticle-functionalized black phosphorus nanosheet nanocomposite

Norfloxacin (NOR) is an antibiotic commonly used to treat humans and food-producing animals. Owing to NOR abuse, its residues are frequently found in animal-derived food products and the surrounding environment. Therefore, development of an efficient analytical technique for the selective determination of trace NOR is greatly significant for food safety and environmental protection. Here, we fabricated an ultrasensitive, label-free molecularly imprinted polymer (MIP) voltammetric sensor for the selective determination of NOR, based on an Au nanoparticle-functionalized black phosphorus nanosheet nanocomposite (BPNS-AuNP) covered by a polypyrrole-imprinted film. BPNS-AuNP nanocomposites were prepared via an in-situ one-step method without the use of reducing agents. The imprinted polypyrrole film was formed on the surface of the BPNS-AuNPs in the presence of NOR. The physical properties and electrochemical behavior of the MIP/BPNS-AuNPs were investigated using various characterization techniques, and the analytical parameters were optimized. We found that BPNS-AuNPs improve the ambient stability and electrocatalytic activity, providing a large surface area for locating a higher number of specific recognition sites. Consequently, the MIP/BPNS-AuNP/GCE showed excellent sensing performance toward NOR, with a wide linear response range (0.1 nM - 10 μM), an extremely low limit of detection (0.012 nM), and extraordinary selectivity. Moreover, the MIP/BPNS-AuNP/GCE was used to determine NOR in various experimental samples with satisfactory results.

On-skin paintable biogel for long-term high-fidelity electroencephalogram recording

Long-term high-fidelity electroencephalogram (EEG) recordings are critical for clinical and brain science applications. Conductive liquid-like or solid-like wet interface materials have been conventionally used as reliable interfaces for EEG recording. However, because of their simplex liquid or solid phase, electrodes with them as interfaces confront inadequate dynamic adaptability to hairy scalp, which makes it challenging to maintain stable and efficient contact of electrodes with scalp for long-term EEG recording. Here, we develop an on-skin paintable conductive biogel that shows temperature-controlled reversible fluid-gel transition to address the abovementioned limitation. This phase transition endows the biogel with unique on-skin paintability and in situ gelatinization, establishing conformal contact and dynamic compliance of electrodes with hairy scalp. The biogel is demonstrated as an efficient interface for long-term high-quality EEG recording over several days and for the high-performance capture and classification of evoked potentials. The paintable biogel offers a biocompatible and long-term reliable interface for EEG-based systems.

Insight into the Contact Impedance between the Electrode and the Skin Surface for Electrophysical Recordings

To obtain a performance improved dry electrode for bioelectrical activity detection is still a challenge, which is mainly due to the poor fundamental understanding on the impedance of the electrode-skin interface. Herein, the impedance between the electrode and the skin interface of three types of electrodes, which are the wet electrode, semidry electrode, and dry electrode, is investigated with electrochemical impedance spectroscopy combined with the spectra fitting technique. The parameters of performance duration, potential, and frequency associated with the impedance are explored for these three types of electrodes. The overall impedance is roughly constant within the performance duration and the potential applied in this study. Along with the frequency decreases, the impedance of the dry electrode reduces faster and is more complicated compared with the other two types of electrodes. Moreover, the results computed with the equivalent circuits show that the charge transfer resistance is additionally present compared to the wet and semidry electrodes. This large and additional charge transfer resistance may explain its relatively poorer electrophysiological properties.

Materials for Dry Electrodes for the Electroencephalography: Advances, Challenges, Perspectives

Electroencephalography (EEG) is extensively applied in brain cognition, clinical diagnosis, and artificial intelligence through detecting and analyzing the human brain biopotential. The Ag/AgCl combined with a conductive gel is the most widely used electrode in EEG. However, pre‐preparation before testing is time‐consuming and complicated. The dried gel has to be cleaned from hair after testing, otherwise discomforting the subjects. Therefore, it is strongly desired to develop a dry electrode to ease the test process and comfort the subjects. However, the high electrode–skin contact impedance weakens the intensity of biopotential signals. The materials with the features of high conductivity, good biocompatibility, and ease to obtain are more favorable for the dry EEG electrodes. This review provides state‐of‐the‐art materials for the dry electrode for the EEG with respect to the material preparation, and their electrical and electroencephalographical properties. Challenges and perspectives related to the material preparation, cost, and applications are also discussed.

Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device

The demand for non-laboratory and long-term EEG acquisition in scientific and clinical applications has put forward new requirements for wearable EEG devices. In this paper, a new wearable frontal EEG device called Mindeep was proposed. A signal quality study was then conducted, which included simulated signal tests and signal quality comparison experiments. Simulated signals with different frequencies and amplitudes were used to test the stability of Mindeep’s circuit, and the high correlation coefficients (>0.9) proved that Mindeep has a stable and reliable hardware circuit. The signal quality comparison experiment, between Mindeep and the gold standard device, Neuroscan, included three tasks: (1) resting; (2) auditory oddball; and (3) attention. In the resting state, the average normalized cross-correlation coefficients between EEG signals recorded by the two devices was around 0.72 ± 0.02, Berger effect was observed (p < 0.01), and the comparison results in the time and frequency domain illustrated the ability of Mindeep to record high-quality EEG signals. The significant differences between high tone and low tone in auditory event-related potential collected by Mindeep was observed in N2 and P2. The attention recognition accuracy of Mindeep achieved 71.12% and 74.76% based on EEG features and the XGBoost model in the two attention tasks, respectively, which were higher than that of Neuroscan (70.19% and 72.80%). The results validated the performance of Mindeep as a prefrontal EEG recording device, which has a wide range of potential applications in audiology, cognitive neuroscience, and daily requirements.

A novel flexible hydrogel electrode with a strong moisturizing ability for long-term EEG recording

Objective. A novel flexible hydrogel electrode with a strong moisturizing ability was prepared for long-term electroencephalography (EEG) monitoring.Approach. The hydrogel was synthesized by polymerizing the N-acryloyl glycinamide monomer. And a proper amount of glycerin was added to the hydrogel to increase the moisture retention ability of the electrodes. The hydrogel shows high mechanical properties, and the liquid in the hydrogel produces a hydrating effect on the skin stratum corneum, which could decrease the contact impedance between skin and electrode. In addition, the installation of hydrogel electrode is very convenient, and the skin of the subject does not need to be abraded.Main results. Scanning electron microscope images show that there are a large number of micropores in the hydrogel, which provide storage space for water molecules. The average potential drift of the hydrogel electrode is relatively low (1.974 ± 0.560µV min^-1). The average contact impedance of hydrogel electrode in forehead region and hair region are 6.43 ± 0.84 kΩ cm²and 13.15 ± 3.72 kΩ cm², respectively. The result of open/closed paradigm, steady-state visual evoked potentials, and P300 visual evoked potential show that hydrogel electrode has excellent performance. Compared with the hydrogel without glycerin, the moisture retention ability of hydrogel containing glycerin was greatly improved.Significance.Compared with standard Ag/AgCl wet electrode, hydrogel electrode is more convenient to install and has strong moisture retention ability, which makes it have great potential in daily life for long-term EEG recording.

Non-invasive on-skin sensors for brain machine interfaces with epitaxial graphene

Objective. Brain-machine interfaces are key components for the development of hands-free, brain-controlled devices. Electroencephalogram (EEG) electrodes are particularly attractive for harvesting the neural signals in a non-invasive fashion.Approach.Here, we explore the use of epitaxial graphene (EG) grown on silicon carbide on silicon for detecting the EEG signals with high sensitivity.Main results and significance.This dry and non-invasive approach exhibits a markedly improved skin contact impedance when benchmarked to commercial dry electrodes, as well as superior robustness, allowing prolonged and repeated use also in a highly saline environment. In addition, we report the newly observed phenomenon of surface conditioning of the EG electrodes. The prolonged contact of the EG with the skin electrolytes functionalize the grain boundaries of the graphene, leading to the formation of a thin surface film of water through physisorption and consequently reducing its contact impedance more than three-fold. This effect is primed in highly saline environments, and could be also further tailored as pre-conditioning to enhance the performance and reliability of the EG sensors.

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.

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review

Electroencephalography (EEG) is a non-invasive technique used to record the brain's evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, group membership classification, and brain-computer interface purposes. This study aimed to systematically review recent advances in ML and DL supervised models for decoding and classifying EEG signals. Moreover, this article provides a comprehensive review of the state-of-the-art techniques used for EEG signal preprocessing and feature extraction. To this end, several academic databases were searched to explore relevant studies from the year 2000 to the present. Our results showed that the application of ML and DL in both mental workload and motor imagery tasks has received substantial attention in recent years. A total of 75% of DL studies applied convolutional neural networks with various learning algorithms, and 36% of ML studies achieved competitive accuracy by using a support vector machine algorithm. Wavelet transform was found to be the most common feature extraction method used for all types of tasks. We further examined the specific feature extraction methods and end classifier recommendations discovered in this systematic review.

Brain Symmetry Analysis during the Use of a BCI Based on Motor Imagery for the Control of a Lower-Limb Exoskeleton

Brain–Computer Interfaces (BCI) are systems that allow external devices to be controlled by means of brain activity. There are different such technologies, and electroencephalography (EEG) is an example. One of the most common EEG control methods is based on detecting changes in sensorimotor rhythms (SMRs) during motor imagery (MI). The aim of this study was to assess the laterality of cortical function when performing MI of the lower limb. Brain signals from five subjects were analyzed in two conditions, during exoskeleton-assisted gait and while static. Three different EEG electrode configurations were evaluated: covering both hemispheres, covering the non-dominant hemisphere and covering the dominant hemisphere. In addition, the evolution of performance and laterality with practice was assessed. Although sightly superior results were achieved with information from all electrodes, differences between electrode configurations were not statistically significant. Regarding the evolution during the experimental sessions, the performance of the BCI generally evolved positively the higher the experience was.

Human Body-Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

Several on-body sensing and communication applications use electrodes in contact with the human body. Body-electrode interfaces in these cases act as a transducer, converting ionic current in the body to electronic current in the sensing and communication circuits and vice versa. An ideal body-electrode interface should have the characteristics of an electrical short, i.e., the transfer of ionic currents and electronic currents across the interface should happen without any hindrance. However, practical body-electrode interfaces often have definite impedances and potentials that hinder the free flow of currents, affecting the application's performance. Minimizing the impact of body-electrode interfaces on the application's performance requires one to understand the physics of such interfaces, how it distorts the signals passing through it, and how the interface-induced signal degradations affect the applications. Our work deals with reviewing these elements in the context of biopotential sensing and human body communication.

A Novel Highly Durable Carbon/Silver/Silver Chloride Composite Electrode for High-Definition Transcranial Direct Current Stimulation

High-definition transcranial direct current stimulation (HD-tDCS) is a promising non-invasive neuromodulation technique, which has been widely used in the clinical intervention and treatment of neurological or psychiatric disorders. Sintered Ag/AgCl electrode has become a preferred candidate for HD-tDCS, but its service life is very short, especially for long-term anodal stimulation. To address this issue, a novel highly durable conductive carbon/silver/silver chloride composite (C/Ag/AgCl) electrode was fabricated by a facile cold rolling method. The important parameters were systematically optimized, including the conductive enhancer, the particle size of Ag powder, the C:Ag:PTFE ratio, the saline concentration, and the active substance loading. The CNT/Ag/AgCl-721 electrode demonstrated excellent specific capacity and cycling performance. Both constant current anodal polarization and simulated tDCS measurement demonstrated that the service life of the CNT/Ag/AgCl-721 electrodes was 15-16 times of that of sintered Ag/AgCl electrodes. The much longer service life can be attributed to the formation of the three-dimensional interpenetrating conductive network with CNT doping, which can maintain a good conductivity and cycling performance even if excessive non-conductive AgCl is accumulated on the surface during long-term anodal stimulation. Considering their low cost, long service life, and good skin tolerance, the proposed CNT/Ag/AgCl electrodes have shown promising application prospects in HD-tDCS, especially for daily life scenarios.

Modeling Stratum Corneum Swelling for the Optimization of Electrode-Based Skin Hydration Sensors

We present a novel computational model of the human skin designed to investigate dielectric spectroscopy electrodes for stratum corneum hydration monitoring. The multilayer skin model allows for the swelling of the stratum corneum, as well as the variations of the dielectric properties under several hydration levels. According to the results, the stratum corneum thickness variations should not be neglected. For high hydration levels, swelling reduces the skin capacitance in comparison to a fixed stratum corneum thickness model. In addition, different fringing-field electrodes are evaluated in terms of sensitivity to the stratum corneum hydration level. As expected, both conductance and capacitance types of electrodes are influenced by the electrode geometry and dimension. However, the sensitivity of the conductance electrodes is more affected by dimension changes than the capacitance electrode leading to potential design optimization.

A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data

Sleep disturbances are common in Alzheimer’s disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for studying sleep in patients with dementia is the requirement for overnight polysomnography (PSG) to achieve formal sleep staging. This is not only costly, but also spending a night in a hospital setting is not always advisable in this patient group. As an alternative to PSG, portable electroencephalography (EEG) headbands (HB) have been developed, which reduce cost, increase patient comfort, and allow sleep recordings in a person’s home environment. However, naïve applications of current automated sleep staging systems tend to perform inadequately with HB data, due to their relatively lower quality. Here we present a deep learning (DL) model for automated sleep staging of HB EEG data to overcome these critical limitations. The solution includes a simple band-pass filtering, a data augmentation step, and a model using convolutional (CNN) and long short-term memory (LSTM) layers. With this model, we have achieved 74% (±10%) validation accuracy on low-quality two-channel EEG headband data and 77% (±10%) on gold-standard PSG. Our results suggest that DL approaches achieve robust sleep staging of both portable and in-hospital EEG recordings, and may allow for more widespread use of ambulatory sleep assessments across clinical conditions, including neurodegenerative disorders.

Custom-Fitted In- and Around-the-Ear Sensors for Unobtrusive and On-the-Go EEG Acquisitions: Development and Validation

OBJECTIVES

This paper aims to validate the performance and physical design of a wearable, unobtrusive ear-centered electroencephalography (EEG) device, dubbed "EARtrodes", using early and late auditory evoked responses. Results would also offer a proof-of-concept for the device to be used as a concealed brain-computer interface (BCI).

DESIGN

The device is composed of a custom-fitted earpiece and an ergonomic behind-the-ear piece with embedded electrodes made of a soft and flexible combination of silicone rubber and carbon fibers. The location of the conductive silicone electrodes inside the ear canal and the optimal geometry of the behind-the-ear piece were obtained through morphological and geometrical analysis of the human ear canal and the region around-the-ear. An entirely conductive generic earpiece was also developed to assess the potential of a universal, more affordable solution.

RESULTS

Early latency results illustrate the conductive silicone electrodes' capability to record quality EEG signals, comparable to those obtained with traditional gold-plated electrodes. Additionally, late latency results demonstrate EARtrodes' capacity to reliably detect decision-making processes from the ear.

CONCLUSIONS

EEG results validate the performance of EARtrodes as a circum-aural and intra-aural EEG recording system adapted for a wide range of applications in audiology, neuroscience, clinical research, and as an unobtrusive BCI.