Design of hydrogel-based wearable EEG electrodes for medical applications

From lab to wearables: Innovations in multifunctional hydrogel chemistry for next-generation bioelectronic devices

Functional hydrogels have emerged as foundational materials in diagnostics, therapy, and wearable devices, owing to their high stretchability, flexibility, sensing, and outstanding biocompatibility. Their significance stems from their resemblance to biological tissue and their exceptional versatility in electrical, mechanical, and biofunctional engineering, positioning themselves as a bridge between living organisms and electronic systems, paving the way for the development of highly compatible, efficient, and stable interfaces. These multifaceted capability revolutionizes the essence of hydrogel-based wearable devices, distinguishing them from conventional biomedical devices in real-world practical applications. In this comprehensive review, we first discuss the fundamental chemistry of hydrogels, elucidating their distinct properties and functionalities. Subsequently, we examine the applications of these bioelectronics within the human body, unveiling their transformative potential in diagnostics, therapy, and human-machine interfaces (HMI) in real wearable bioelectronics. This exploration serves as a scientific compass for researchers navigating the interdisciplinary landscape of chemistry, materials science, and bioelectronics.

Advances in conductive hydrogels for neural recording and stimulation

The brain-computer interface (BCI) allows the human or animal brain to directly interact with the external environment through the neural interfaces, thus playing the role of monitoring, protecting, improving/restoring, enhancing, and replacing. Recording electrophysiological information such as brain neural signals is of great importance in health monitoring and disease diagnosis. According to the electrode position, it can be divided into non-implantable, semi-implantable, and implantable. Among them, implantable neural electrodes can obtain the highest-quality electrophysiological information, so they have the most promising application. However, due to the chemo-mechanical mismatch between devices and tissues, the adverse foreign body response and performance loss over time seriously restrict the development and application of implantable neural electrodes. Given the challenges, conductive hydrogel-based neural electrodes have recently attracted much attention, owing to many advantages such as good mechanical match with the native tissues, negligible foreign body response, and minimal signal attenuation. This review mainly focuses on the current development of conductive hydrogels as a biocompatible framework for neural tissue and conductivity-supporting substrates for the transmission of electrical signals of neural tissue to speed up electrical regeneration and their applications in neural sensing and recording as well as stimulation.

Hydrogel-Based Biosensors for Bacterial Infections

Hydrogels are known to have the advantages such as good biodegradability, biocompatibility, and easy functionalization, making them ideal candidates for biosensors. Hydrogel-based biosensors that respond to bacteria-induced microenvironmental changes such as pH, enzymes, antigens, etc., or directly interact with bacterial surface receptors, can be applied for early diagnosis of bacterial infections, providing information for timely treatment while avoiding antibiotic abuse. Furthermore, hydrogel biosensors capable of both bacteria diagnosis and treatment will greatly facilitate the development of point-of-care monitoring of bacterial infections. In this review, the recent advancement of hydrogel-based biosensors for bacterial infection is summarized and discussed. First, the biosensors based on pH-sensitive hydrogels, bacterial-specific secretions-sensitive hydrogels, and hydrogels directly in contact with bacterial surfaces are presented. Next, hydrogel biosensors capable of detecting bacterial infection in the early stage followed by immediate on-demand treatment are discussed. Finally, the challenges and future development of hydrogel biosensors for bacterial infections are proposed.

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.

Harnessing the power of biological macromolecules in hydrogels for controlled drug release in the central nervous system: A review

Hydrogels have immense potential in revolutionizing central nervous system (CNS) drug delivery, improving outcomes for neurological disorders. They serve as promising tools for controlled drug delivery to the CNS. Available hydrogel types include natural macromolecules (e.g., chitosan, hyaluronic acid, alginate), as well as hybrid hydrogels combining natural and synthetic polymers. Each type offers distinct advantages in terms of biocompatibility, mechanical properties, and drug release kinetics. Design and engineering considerations encompass hydrogel composition, crosslinking density, porosity, and strategies for targeted drug delivery. The review emphasizes factors affecting drug release profiles, such as hydrogel properties and formulation parameters. CNS drug delivery applications of hydrogels span a wide range of therapeutics, including small molecules, proteins and peptides, and nucleic acids. However, challenges like limited biodegradability, clearance, and effective CNS delivery persist. Incorporating 3D bioprinting technology with hydrogel-based CNS drug delivery holds the promise of highly personalized and precisely controlled therapeutic interventions for neurological disorders. The review explores emerging technologies like 3D bioprinting and nanotechnology as opportunities for enhanced precision and effectiveness in hydrogel-based CNS drug delivery. Continued research, collaboration, and technological advancements are vital for translating hydrogel-based therapies into clinical practice, benefiting patients with CNS disorders. This comprehensive review article delves into hydrogels for CNS drug delivery, addressing their types, design principles, applications, challenges, and opportunities for clinical translation.

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization

For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are subjective, time-consuming, and labor-consuming. With the development of affective computing and Artificial Intelligence (AI) technologies, Electroencephalogram (EEG)-based depression detection methods have emerged. However, previous research has virtually neglected practical application scenarios, as most studies have focused on analyzing and modeling EEG data. Furthermore, EEG data is typically obtained from specialized devices that are large, complex to operate, and poorly ubiquitous. To address these challenges, a wearable three-lead EEG sensor with flexible electrodes was developed to obtain prefrontal-lobe EEG data. Experimental measurements show that the EEG sensor achieves promising performance (background noise of no more than 0.91 μVpp, Signal-to-Noise Ratio (SNR) of 26--48 dB, and electrode-skin contact impedance of less than 1 K Ω). In addition, EEG data from 70 depressed patients and 108 healthy controls were collected using the EEG sensor, and the linear and nonlinear features were extracted. The features were then weighted and selected using the Ant Lion Optimization (ALO) algorithm to improve classification performance. The experimental results show that the k-NN classifier achieves a classification accuracy of 90.70%, specificity of 96.53%, and sensitivity of 81.79%, indicating the promising potential of the three-lead EEG sensor combined with the ALO algorithm and the k-NN classifier for EEG-assisted depression diagnosis.

An Ultra-Thin MXene Film for Multimodal Sensing of Neuroelectrical Signals with Artifacts Removal

Neuroelectrical signals transmitted onto the skin tend to decay to an extremely weak level, making them highly susceptible to interference from the environment and body movement. Meanwhile, for comprehensively understanding cognitive nerve conduction, multimodal sensing of neural signals, such as magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIRS), is highly required. Previous metal or polymer conductors cannot either provide a seamless on-skin feature for accurate sensing of neuroelectrical signals or be compatible with multimodal imaging techniques without opto- and magnet- artifacts. Herein, a ≈20 nm thick MXene film that is able to simultaneously detect electrophysiological signals and perform imaging by MRI and fNIRS with high fidelity is reported. The ultrathin film is made of crosslinked Ti3 C2 Tx film via poly (3,4-ethylene dioxythiophene): polystyrene sulfonate (PEDOT: PSS), showing a record high electroconductivity and transparency combination (11 000 S cm-1 @89%). Among them, PEDOT: PSS not only plays a cross-linking role to stabilize MXene film but also shortens the interlayer distance for effective charge transfer and high transparency. Thus, it can achieve a low interfacial impedance with skin or neural surfaces for accurate recording of electrophysiological signals with low motion artifacts. Besides, the high transparency originating from the ultrathin feature leads to good compatibility with fNIRS and MRI without optical and magnetic artifacts, enabling multimodal cognitive neural monitoring during prolonged use.

Robust, self-adhesive and anti-bacterial silk-based LIG electrodes for electrophysiological monitoring

Flexible wearable electrodes have been extensively used for obtaining electrophysiological signals towards smart health monitoring and disease diagnosis. Here, low-cost, and non-conductive silk fabric (SF) have been processed into highly conductive laser induced graphene (LIG) electrodes while maintaining the original structure of SF. A CO2-pulsed laser was utilized to produce LIG-SF with controlled sheet resistance and mechanical properties. Laser processing of SFs under optimized conditions yielded LIG-SF electrodes with a high degree of homogeneity on both, top and bottom layers. Silk fibroin/Ca2+ adhesive layers effectively promoted the adhesive, anti-bacterial properties and provided a conformal contact of LIG-SF electrodes with human skin. Compared with conventional Ag/AgCl electrodes, LIG-SF electrodes possesses a much lower contact impedance in contact with human skin enabling highly stable electrophysiological signals recording. The applicability of adhesive LIG-SF electrodes to acquire electrocardiogram (ECG) signals was investigated. ECG signals recordings of adhesive LIG-SF electrodes showed excellent performance compared to conventional Ag/AgCl electrodes at intense body movements while running at different speeds for up to 9 km over a duration of 24 h. Therefore, our proposed adhesive LIG-SF electrodes can be applied for long-term personalized healthcare monitoring and sports management applications.

Hydrogel-Based Bioelectronics and Their Applications in Health Monitoring

Flexible bioelectronics exhibit promising potential for health monitoring, owing to their soft and stretchable nature. However, the simultaneous improvement of mechanical properties, biocompatibility, and signal-to-noise ratio of these devices for health monitoring poses a significant challenge. Hydrogels, with their loose three-dimensional network structure that encapsulates massive amounts of water, are a potential solution. Through the incorporation of polymers or conductive fillers into the hydrogel and special preparation methods, hydrogels can achieve a unification of excellent properties such as mechanical properties, self-healing, adhesion, and biocompatibility, making them a hot material for health monitoring bioelectronics. Currently, hydrogel-based bioelectronics can be used to fabricate flexible bioelectronics for motion, bioelectric, and biomolecular acquisition for human health monitoring and further clinical applications. This review focuses on materials, devices, and applications for hydrogel-based bioelectronics. The main material properties and research advances of hydrogels for health monitoring bioelectronics are summarized firstly. Then, we provide a focused discussion on hydrogel-based bioelectronics for health monitoring, which are classified as skin-attachable, implantable, or semi-implantable depending on the depth of penetration and the location of the device. Finally, future challenges and opportunities of hydrogel-based bioelectronics for health monitoring are envisioned.

Evolution of nanostructured skin patches towards multifunctional wearable platforms for biomedical applications

Recent advances in the field of skin patches have promoted the development of wearable and implantable bioelectronics for long-term, continuous healthcare management and targeted therapy. However, the design of electronic skin (e-skin) patches with stretchable components is still challenging and requires an in-depth understanding of the skin-attachable substrate layer, functional biomaterials and advanced self-powered electronics. In this comprehensive review, we present the evolution of skin patches from functional nanostructured materials to multi-functional and stimuli-responsive patches towards flexible substrates and emerging biomaterials for e-skin patches, including the material selection, structure design and promising applications. Stretchable sensors and self-powered e-skin patches are also discussed, ranging from electrical stimulation for clinical procedures to continuous health monitoring and integrated systems for comprehensive healthcare management. Moreover, an integrated energy harvester with bioelectronics enables the fabrication of self-powered electronic skin patches, which can effectively solve the energy supply and overcome the drawbacks induced by bulky battery-driven devices. However, to realize the full potential offered by these advancements, several challenges must be addressed for next-generation e-skin patches. Finally, future opportunities and positive outlooks are presented on the future directions of bioelectronics. It is believed that innovative material design, structure engineering, and in-depth study of fundamental principles can foster the rapid evolution of electronic skin patches, and eventually enable self-powered close-looped bioelectronic systems to benefit mankind.

A Nanoclay-Enhanced Hydrogel for Self-Adhesive Wearable Electrophysiology Electrodes with High Sensitivity and Stability

Hydrogel-based wet electrodes are the most important biosensors for electromyography (EMG), electrocardiogram (ECG), and electroencephalography (EEG); but, are limited by poor strength and weak adhesion. Herein, a new nanoclay-enhanced hydrogel (NEH) has been reported, which can be fabricated simply by dispersing nanoclay sheets (Laponite XLS) into the precursor solution (containing acrylamide, N, N'-Methylenebisacrylamide, ammonium persulfate, sodium chloride, glycerin) and then thermo-polymerizing at 40 °C for 2 h. This NEH, with a double-crosslinked network, has nanoclay-enhanced strength and self-adhesion for wet electrodes with excellent long-term stability of electrophysiology signals. First of all, among existing hydrogels for biological electrodes, this NEH has outstanding mechanical performance (93 kPa of tensile strength and 1326% of breaking elongation) and adhesion (14 kPa of adhesive force), owing to the double-crosslinked network of the NEH and the composited nanoclay, respectively. Furthermore, this NEH can still maintain a good water-retaining property (it can remain at 65.4% of its weight after 24 h at 40 °C and 10% humidity) for excellent long-term stability of signals, on account of the glycerin in the NEH. In the stability test of skin-electrode impedance at the forearm, the impedance of the NEH electrode can be stably kept at about 100 kΩ for more than 6 h. As a result, this hydrogel-based electrode can be applied for a wearable self-adhesive monitor to highly sensitively and stably acquire EEG/ECG electrophysiology signals of the human body over a relatively long time. This work provides a promising wearable self-adhesive hydrogel-based electrode for electrophysiology sensing; which, will also inspire the development of new strategies to improve electrophysiological sensors.

Selection of the optimal channel configuration for implementing wearable EEG devices for the diagnosis of mild cognitive impairment

Background

Early diagnosis of mild cognitive impairment (MCI) is essential for timely treatment planning. With recent advances in the wearable technology, interest has increasingly shifted toward computer-aided self-diagnosis of MCI using wearable electroencephalography (EEG) devices in daily life. However, no study so far has investigated the optimal electrode configurations for the efficient diagnosis of MCI while considering the design factors of wearable EEG devices. In this study, we aimed to determine the optimal channel configurations of wearable EEG devices for the computer-aided diagnosis of MCI.

Method

We employed an EEG dataset collected from 21 patients with MCI and 21 healthy control subjects. After evaluating the classification accuracies for all possible electrode configurations for the two-, four-, six-, and eight-electrode conditions using a support vector machine, the optimal electrode configurations that provide the highest diagnostic accuracy were suggested for each electrode condition.

Results

The highest classification accuracies of 74.04% ± 4.82, 82.43% ± 6.14, 86.28% ± 2.81, and 86.85% ± 4.97 were achieved for the optimal two-, four-, six-, and eight-electrode configurations, respectively, which demonstrated the possibility of precise machine-learning-based diagnosis of MCI with a limited number of EEG electrodes. Additionally, further simulations with the EEG dataset revealed that the optimal electrode configurations had significantly higher classification accuracies than commercial EEG devices with the same number of electrodes, which suggested the importance of electrode configuration optimization for wearable EEG devices based on clinical EEG datasets.

Conclusions

This study highlighted that the optimization of the electrode configuration, assuming the wearable EEG devices can potentially be utilized for daily life monitoring of MCI, is necessary to enhance the performance and portability.

Sialic acid biosensing by post-printing modification of PEDOT:PSS with pyridylboronic acid

A poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)-based conducting polymer, which has biorecognition capabilities, has promising biosensing applications. Previously, we developed a facile method for post-printing chemical modification of PEDOT:PSS thin films from commercial sources. Molecular recognition elements were directly introduced into the PSS side chain by a two-step chemical reaction: introduction of an ethylenediamine linker via an acid chloride reaction of the sulfonate moiety, and subsequent receptor attachment to the linker via amine coupling. In this study, the same method was used to introduce 6-carboxypyridine-3-boronic acid (carboxy-PyBA) into the linker for specifically detecting N-acetylneuraminic acid (sialic acid, SA), as a cancer biomarker. The surface-modified PEDOT:PSS films were characterized by X-ray photoelectron spectroscopy, attenuated total reflection Fourier-transform infrared spectroscopy, and static water contact angle and conductivity measurements. The specific interaction between PyBA and SA was detected by label-free reagent-free potentiometry. The SA-specific negative potential responses of modified PEDOT:PSS electrodes, which was ascribed to an SA carboxyl anion, were observed in a physiologically relevant SA range (1.6-2.9 mM) at pH 5, in a concentration-dependent manner even in the presence of 10% fetal bovine serum. The sensitivity was -2.9 mV/mM in 1-5 mM SA with a limit of detection of 0.7 mM. The sensing performances were almost equivalent to those of existing graphene-based electrical SA sensors. These results show that our chemical derivatization method for printing PEDOT:PSS thin films will have applications in SA clinical diagnostics.