Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures

Asymmetric Wettability Hydrogel Surfaces for Enduring Electromyographic Monitoring

Hydrogel electrode interfaces have shown tremendous promise in the acquisition of surface electromyography (EMG) signals. However, the perspiration or moisture environments will trigger the deadhesion between hydrogel electrodes and human skin. Despite the hydrophobic/hydrophilic surfaces can perform the anti-moisture or adhesion respectively, it remains a challenge to integrally form a Janus hydrogel with homogeneous mechanical elasticity and electronic performance. Herein, a surface induction strategy is proposed to approach the hydrophobic/hydrophilic hydrogel surfaces. The hydrophobic interaction between surfactants and molds regulates the distribution of hydrophobic/hydrophilic monomers on the surface. The hydrophobic molds induce a hydrophilic hydrogel surface, while the hydrophilic molds induce a hydrophobic surface. It presents a new phenomenon of reversal wettability inducing and optional hydrogel surfaces. The integral Janus hydrogel can be easily obtained by the hydrophilic molds. Balance of adhesion, elasticity, and conductivity endows the hydrogel electrode patch with durable conformal adhesion and high-fidelity EMG signals even in the sweaty epidermis due to the asymmetric wettability surfaces. This hydrogel performs the quantitative description of muscle strength and accurate fatigue assessment. It offers a reliable candidate for future practical applications in continuous digital healthcare and intelligent human-machine interaction, even the Metaverse.

Deep Learning Model Coupling Wearable Bioelectric and Mechanical Sensors for Refined Muscle Strength Assessment

Muscle strength (MS) is related to our neural and muscle systems, essential for clinical diagnosis and rehabilitation evaluation. Although emerging wearable technology seems promising for MS assessment, problems still exist, including inaccuracy, spatiotemporal differences, and analyzing methods. In this study, we propose a wearable device consisting of myoelectric and strain sensors, synchronously acquiring surface electromyography and mechanical signals at the same spot during muscle activities, and then employ a deep learning model based on temporal convolutional network (TCN) + Transformer (Tcnformer), achieving accurate grading and prediction of MS. Moreover, by combining with deep clustering, named Tcnformer deep cluster (TDC), we further obtain a 25-level classification for MS assessment, refining the conventional 5 levels. Quantification and validation showcase a patient's postoperative recovery from level 3.2 to level 3.6 in the first few days after surgery. We anticipate that this system will importantly advance precise MS assessment, potentially improving relevant clinical diagnosis and rehabilitation outcomes.

Materials-Driven Soft Wearable Bioelectronics for Connected Healthcare

In the era of Internet-of-things, many things can stay connected; however, biological systems, including those necessary for human health, remain unable to stay connected to the global Internet due to the lack of soft conformal biosensors. The fundamental challenge lies in the fact that electronics and biology are distinct and incompatible, as they are based on different materials via different functioning principles. In particular, the human body is soft and curvilinear, yet electronics are typically rigid and planar. Recent advances in materials and materials design have generated tremendous opportunities to design soft wearable bioelectronics, which may bridge the gap, enabling the ultimate dream of connected healthcare for anyone, anytime, and anywhere. We begin with a review of the historical development of healthcare, indicating the significant trend of connected healthcare. This is followed by the focal point of discussion about new materials and materials design, particularly low-dimensional nanomaterials. We summarize material types and their attributes for designing soft bioelectronic sensors; we also cover their synthesis and fabrication methods, including top-down, bottom-up, and their combined approaches. Next, we discuss the wearable energy challenges and progress made to date. In addition to front-end wearable devices, we also describe back-end machine learning algorithms, artificial intelligence, telecommunication, and software. Afterward, we describe the integration of soft wearable bioelectronic systems which have been applied in various testbeds in real-world settings, including laboratories that are preclinical and clinical environments. Finally, we narrate the remaining challenges and opportunities in conjunction with our perspectives.

Water-responsive supercontractile polymer films for bioelectronic interfaces

Connecting different electronic devices is usually straightforward because they have paired, standardized interfaces, in which the shapes and sizes match each other perfectly. Tissue-electronics interfaces, however, cannot be standardized, because tissues are soft1-3 and have arbitrary shapes and sizes4-6. Shape-adaptive wrapping and covering around irregularly sized and shaped objects have been achieved using heat-shrink films because they can contract largely and rapidly when heated7. However, these materials are unsuitable for biological applications because they are usually much harder than tissues and contract at temperatures higher than 90 °C (refs. 8,9). Therefore, it is challenging to prepare stimuli-responsive films with large and rapid contractions for which the stimuli and mechanical properties are compatible with vulnerable tissues and electronic integration processes. Here, inspired by spider silk10-12, we designed water-responsive supercontractile polymer films composed of poly(ethylene oxide) and poly(ethylene glycol)-α-cyclodextrin inclusion complex, which are initially dry, flexible and stable under ambient conditions, contract by more than 50% of their original length within seconds (about 30% per second) after wetting and become soft (about 100 kPa) and stretchable (around 600%) hydrogel thin films thereafter. This supercontraction is attributed to the aligned microporous hierarchical structures of the films, which also facilitate electronic integration. We used this film to fabricate shape-adaptive electrode arrays that simplify the implantation procedure through supercontraction and conformally wrap around nerves, muscles and hearts of different sizes when wetted for in vivo nerve stimulation and electrophysiological signal recording. This study demonstrates that this water-responsive material can play an important part in shaping the next-generation tissue-electronics interfaces as well as broadening the biomedical application of shape-adaptive materials.

DMC (2',4'-dihydroxy-6'-methoxy-3',5'-dimethylchalcone) enhances exercise tolerance via the AMPK-SIRT1-PGC-1α pathway in mice fed a high-fat diet

Obesity is caused by an imbalance between energy intake and energy expenditure. This study aimed to determine the effects and mechanisms of 2',4'-dihydroxy-6'-methoxy-3',5'-dimethylchalcone (DMC) on exercise tolerance in high-fat diet (HFD)-fed mice. Male C57BL/6J mice were randomly divided into two categories (7 groups [n = 8]): sedentary (control [CON], HFD, 200 mg/kg DMC, and 500 mg/kg DMC) and swimming (HFD, 200 mg/kg DMC, and 500 mg/kg DMC). Except the CON group, all other groups were fed HFD with or without DMC intervention for 33 days. The swimming groups were subjected to exhaustive swimming (three sessions/week). Changes in swimming time, glucolipid metabolism, body composition, biochemical indicators, histopathology, inflammation, metabolic mediators, and protein expression were assessed. DMC combined with regular exercise improved endurance performance, body composition, glucose and insulin tolerance, lipid profile, and the inflammatory state in a dose-dependent manner. Further, DMC alone or combined with exercise could restore normal tissue morphology, reduce fatigue-associated markers, and boost whole-body metabolism and the protein expression of phospho-AMP-activated protein kinase alpha/total-AMP-activated protein kinase alpha (AMPK), sirtuin-1 (SIRT1), peroxisome-proliferator-activated receptor gamma coactivator 1alpha (PGC-1α), and peroxisome proliferator-activated receptor alpha in the muscle and adipose tissues of HFD-fed mice. DMC exhibits antifatigue effects by regulating glucolipid catabolism, inflammation, and energy homeostasis. Furthermore, DMC exerts a synergistic exercise-related metabolic effect via the AMPK-SIRT1-PGC-1α signaling pathway, suggesting that DMC is a potential natural sports supplement with mimicked or augmented exercise effects for obesity prevention.

A Single Electronic Tattoo for Multisensory Integration

Wearable electronics are garnering growing interest in various emerging fields including intelligent sensors, artificial limbs, and human-machine interfaces. A remaining challenge is to develop multisensory devices that can conformally adhere to the skin even during dynamic-moving environments. Here, a single electronic tattoo (E-tattoo) based on a mixed-dimensional matrix network, which integrates two-dimensional  MXene nanosheets and one-dimensional cellulose nanofibers/Ag nanowires, is presented for multisensory integration. The multidimensional configurations endow the E-tattoo with excellent multifunctional sensing capabilities including temperature, humidity, in-plane strain, proximity, and material identification. In addition, benefiting from the satisfactory rheology of hybrid inks, the E-tattoos are able to be fabricated through multiple facile strategies including direct writing, stamping, screen printing, and three-dimensional printing on various hard/soft substrates. Especially, the E-tattoo with excellent triboelectric properties also can serve as a power source for activating small electronic devices. It is believed that these skin-conformal E-tattoo systems can provide a promising platform for next-generation wearable and epidermal electronics.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Anatomically Designed Triboelectric Wristbands with Adaptive Accelerated Learning for Human-Machine Interfaces

Recent advances in flexible wearable devices have boosted the remarkable development of devices for human-machine interfaces, which are of great value to emerging cybernetics, robotics, and Metaverse systems. However, the effectiveness of existing approaches is limited by the quality of sensor data and classification models with high computational costs. Here, a novel gesture recognition system with triboelectric smart wristbands and an adaptive accelerated learning (AAL) model is proposed. The sensor array is well deployed according to the wrist anatomy and retrieves hand motions from a distance, exhibiting highly sensitive and high-quality sensing capabilities beyond existing methods. Importantly, the anatomical design leads to the close correspondence between the actions of dominant muscle/tendon groups and gestures, and the resulting distinctive features in sensor signals are very valuable for differentiating gestures with data from 7 sensors. The AAL model realizes a 97.56% identification accuracy in training 21 classes with only one-third operands of the original neural network. The applications of the system are further exploited in real-time somatosensory teleoperations with a low latency of <1 s, revealing a new possibility for endowing cyber-human interactions with disruptive innovation and immersive experience.

Silk Fibroin-Based Tough Hydrogels with Strong Underwater Adhesion for Fast Hemostasis and Wound Sealing

Rapid and strong adhesion of hydrogel adhesives is required for instant wound closure and hemostasis. However, in situ hydrogel formation and sufficient adhesion at target tissue sites in biological environments are severely compromised by the presence of blood and body fluids. In this work, an underwater adhesive hydrogel (named SHCa) is fabricated with rapid in situ gelation, enhanced mechanical toughness, and robust underwater adhesion. The SHCa can undergo rapid UV irradiation-induced gelation under water within 5 s and adhere firmly to underwater surfaces for 6 months. The synergistic effects of crystalline β-sheet structures and dynamic energy-dissipating mechanisms enhance the mechanical toughness and cohesion, supporting the balance between adhesion and cohesion in wet environments. Importantly, the SHCa can achieve rapid in situ gelation and robust underwater adhesion at various tissue surfaces in highly dynamic fluid environments, substantially outperforming the commercially available tissue adhesives. The lap shear adhesion strength and wound closure strength of SHCa on blood-covered substrates are 7.24 and 12.68 times higher than those of cyanoacrylate glue, respectively. Its fast hemostasis and wound sealing performance are further demonstrated in in vivo animal models. The proposed hydrogel with strong underwater adhesion provides an effective tool for fast wound closure and hemostasis.

In Situ Forming Epidermal Bioelectronics for Daily Monitoring and Comprehensive Exercise

Conventional epidermal bioelectronics usually do not conform well with natural skin surfaces and are susceptible to motion artifact interference, due to incompatible dimensions, insufficient adhesion, imperfect compliance, and usually require complex manufacturing and high costs. We propose in situ forming hydrogel electrodes or electronics (ISF-HEs) that can establish highly conformal interfaces on curved biological surfaces without auxiliary adhesions. The ISF-HEs also have favorable flexibility and soft compliance comparable to human skin (≈0.02 kPa^-1), which can stably maintain synchronous movements with deformed skins. Thus, the as-prepared ISF-HEs can accurately monitor large and tiny human motions with short response time (≈180 ms), good biocompatibility, and excellent performance. The as-obtained nongapped hydrogel electrode-skin interfaces achieve ultralow interfacial impedance (≈50 KΩ), nearly an order of magnitude lower than commercial Ag|AgCl electrodes as well as other reported dry and wet electrodes, regardless of the intrinsic micro-obstacles (wrinkles, hair) and skin deformation interference. Therefore, the ISF-HEs can collect high-quality electrocardiography and surface electromyography (sEMG) signals, with high signal-to-noise ratio (SNR ≈ 32.04 dB), reduced signal crosstalk, and minimized motion artifact interference. Simultaneously monitoring human motions and sEMG signals have also been implemented for the general exercise status assessment, such as the shooting competition in the Olympics. The as-prepared ISF-HEs can be considered as supplements/substitutes of conventional electrodes in percutaneously noninvasive monitoring of multifunctional physiological signals for health and exercise status.

Stretchable and Self-Healable Graphene–Polymer Conductive Composite for Wearable EMG Sensor

In bioelectronics, stretchable and self-healable electrodes can reliably measure electrophysiological signals from the human body because they have good modulus matching with tissue and high durability. In particular, the polymer–graphene composite has advantages when it is used as an electrode for bioelectronic sensor devices. However, it has previously been reported that external stimuli such as heat or light are required for the self-healing process of polymer/graphene composites. In this study, we optimized a conducting composite by mixing a self-healing polymer (SHP) and graphene. The composite materials can not only self-heal without external stimulation but also have rapid electrical recovery from repeated mechanical damage such as scratches. In addition, they had stable electrical endurance even when the cyclic test was performed over 200 cycles at 50% strain, so they can be useful for a bioelectronic sensor device with high durability. Finally, we measured the electromyogram signals caused by the movement of arm muscles using our composite, and the measured data were transmitted to a microcontroller to successfully control the movement of the robot’s hand.

Proposal of a Wearable Multimodal Sensing-Based Serious Games Approach for Hand Movement Training After Stroke

Stroke often leads to hand motor dysfunction, and effective rehabilitation requires keeping patients engaged and motivated. Among the existing automated rehabilitation approaches, data glove-based systems are not easy to wear for patients due to spasticity, and single sensor-based approaches generally provided prohibitively limited information. We thus propose a wearable multimodal serious games approach for hand movement training after stroke. A force myography (FMG), electromyography (EMG), and inertial measurement unit (IMU)-based multi-sensor fusion model was proposed for hand movement classification, which was worn on the user’s affected arm. Two movement recognition-based serious games were developed for hand movement and cognition training. Ten stroke patients with mild to moderate motor impairments (Brunnstrom Stage for Hand II-VI) performed experiments while playing interactive serious games requiring 12 activities-of-daily-living (ADLs) hand movements taken from the Fugl Meyer Assessment. Feasibility was evaluated by movement classification accuracy and qualitative patient questionnaires. The offline classification accuracy using combined FMG-EMG-IMU was 81.0% for the 12 movements, which was significantly higher than any single sensing modality; only EMG, only FMG, and only IMU were 69.6, 63.2, and 47.8%, respectively. Patients reported that they were more enthusiastic about hand movement training while playing the serious games as compared to conventional methods and strongly agreed that they subjectively felt that the proposed training could be beneficial for improving upper limb motor function. These results showed that multimodal-sensor fusion improved hand gesture classification accuracy for stroke patients and demonstrated the potential of this proposed approach to be used as upper limb movement training after stroke.

Conductive Materials with Elaborate Micro/Nanostructures for Bioelectronics

Bioelectronics, an emerging field with the mutual penetration of biological systems and electronic sciences, allows the quantitative analysis of complicated biosignals together with the dynamic regulation of fateful biological functions. In this area, the development of conductive materials with elaborate micro/nanostructures has been of great significance to the improvement of high-performance bioelectronic devices. Thus, here, a comprehensive and up-to-date summary of relevant research studies on the fabrication and properties of conductive materials with micro/nanostructures and their promising applications and future opportunities in bioelectronic applications is presented. In addition, a critical analysis of the current opportunities and challenges regarding the future developments of conductive materials with elaborate micro/nanostructures for bioelectronic applications is also presented.

Biodegradable Elastomers and Gels for Elastic Electronics

Biodegradable electronics are considered as an important bio-friendly solution for electronic waste (e-waste) management, sustainable development, and emerging implantable devices. Elastic electronics with higher imitative mechanical characteristics of human tissues, have become crucial for human-related applications. The convergence of biodegradability and elasticity has emerged a new paradigm of next-generation electronics especially for wearable and implantable electronics. The corresponding biodegradable elastic materials are recognized as a key to drive this field toward the practical applications. The review first clarifies the relevant concepts including biodegradable and elastic electronics along with their general design principles. Subsequently, the crucial mechanisms of the degradation in polymeric materials are discussed in depth. The diverse types of biodegradable elastomers and gels for electronics are then summarized. Their molecular design, modification, processing, and device fabrication especially the structure-properties relationship as well as recent advanced are reviewed in detail. Finally, the current challenges and the future directions are proposed. The critical insights of biodegradability and elastic characteristics in the elastomers and gel allows them to be tailored and designed more effectively for electronic applications.

Flexible Electronics and Devices as Human-Machine Interfaces for Medical Robotics

Medical robots are invaluable players in non-pharmaceutical treatment of disabilities. Particularly, using prosthetic and rehabilitation devices with human-machine interfaces can greatly improve the quality of life for impaired patients. In recent years, flexible electronic interfaces and soft robotics have attracted tremendous attention in this field due to their high biocompatibility, functionality, conformability, and low-cost. Flexible human-machine interfaces on soft robotics will make a promising alternative to conventional rigid devices, which can potentially revolutionize the paradigm and future direction of medical robotics in terms of rehabilitation feedback and user experience. In this review, the fundamental components of the materials, structures, and mechanisms in flexible human-machine interfaces are summarized by recent and renowned applications in five primary areas: physical and chemical sensing, physiological recording, information processing and communication, soft robotic actuation, and feedback stimulation. This review further concludes by discussing the outlook and current challenges of these technologies as a human-machine interface in medical robotics.

Noncontact human-machine interaction based on hand-responsive infrared structural color

Noncontact human-machine interaction provides a hygienic and intelligent approach for the communication between human and robots. Current noncontact human-machine interactions are generally limited by the interaction distance or conditions, such as in the dark. Here we explore the utilization of hand as an infrared light source for noncontact human-machine interaction. Metallic gratings are used as the human-machine interface to respond to infrared radiation from hand and the generated signals are visualized as different infrared structural colors. We demonstrate the applications of the infrared structural color-based human-machine interaction for user-interactive touchless display and real-time control of a robot vehicle. The interaction is flexible to the hand-interface distance ranging from a few centimeters to tens of centimeters and can be used in low lighting condition or in the dark. The findings in this work provide an alternative and complementary approach to traditional noncontact human-machine interactions, which may further broaden the potential applications of human-machine interaction.

The IR radiation from human hand can selectively interact with grating patterns in the generation of distinct IR structural colors, which can be used for human-machine interaction with flexible interaction distance in low or no light conditions.

Highly-integrated, miniaturized, stretchable electronic systems based on stacked multilayer network materials

Elastic stretchability and function density represent two key figures of merits for stretchable inorganic electronics. Various design strategies have been reported to provide both high levels of stretchability and function density, but the function densities are mostly below 80%. While the stacked device layout can overcome this limitation, the soft elastomers used in previous studies could highly restrict the deformation of stretchable interconnects. Here, we introduce stacked multilayer network materials as a general platform to incorporate individual components and stretchable interconnects, without posing any essential constraint to their deformations. Quantitative analyses show a substantial enhancement (e.g., by ~7.5 times) of elastic stretchability of serpentine interconnects as compared to that based on stacked soft elastomers. The proposed strategy allows demonstration of a miniaturized electronic system (11 mm by 10 mm), with a moderate elastic stretchability (~20%) and an unprecedented areal coverage (~110%), which can serve as compass display, somatosensory mouse, and physiological-signal monitor.

Activities of Daily Living-based Rehabilitation System for Arm and Hand Motor Function Retraining after Stroke

Most stroke survivors have difficulties completing activities of daily living (ADLs) independently. However, few rehabilitation systems have focused on ADLs-related training for gross and fine motor function together. We propose an ADLs-based serious game rehabilitation system for the training of motor function and coordination of both arm and hand movement where the user performs corresponding ADLs movements to interact with the target in the serious game. A multi-sensor fusion model based on electromyographic (EMG), force myographic (FMG), and inertial sensing was developed to estimate users' natural upper limb movement. Eight healthy subjects and three stroke patients were recruited in an experiment to validate the system's effectiveness. The performance of different sensor and classifier configurations on hand gesture classification against the arm position variations were analyzed, and qualitative patient questionnaires were conducted. Results showed that elbow extension/flexion has a more significant negative influence on EMG-based, FMG-based, and EMG+FMG-based hand gesture recognition than shoulder abduction/adduction does. In addition, there was no significant difference in the negative influence of shoulder abduction/adduction and shoulder flexion/extension on hand gesture recognition. However, there was a significant interaction between sensor configurations and algorithm configurations in both offline and real-time recognition accuracy. The EMG+FMG-combined multi-position classifier model had the best performance against arm position change. In addition, all the stroke patients reported their ADLs-related ability could be restored by using the system. These results demonstrate that the multi-sensor fusion model could estimate hand gestures and gross movement accurately, and the proposed training system has the potential to improve patients' ability to perform ADLs.

Electrostatic-Mechanical Synergistic In Situ Multiscale Tissue Adhesion for Sustainable Residue-Free Bioelectronics Interfaces

Recent studies on soft adhesives have sought to deeply understand how their chemical or mechanical structures interact strongly with living tissues. The aim is to optimally address the unmet needs of patients with acute or chronic diseases. Synergistic adhesion involving both electrostatic (hydrogen bonds) and mechanical interactions (capillarity-assisted suction stress) seems to be effective in overcoming the challenges associated with long-term unstable coupling to tissues. Here, an electrostatically and mechanically synergistic mechanism of residue-free, sustainable, in situ tissue adhesion by implementing hybrid multiscale architectonics. To deduce the mechanism, a thermodynamic model based on a tailored multiscale combinatory adhesive is proposed. The model supports the experimental results that the thermodynamically controlled swelling of the nanoporous hydrogel embedded in the hierarchical elastomeric structure enhances biofluid-insensitive, sustainable, in situ adhesion to diverse soft, slippery, and wet organ surfaces, as well as clean detachment in the peeling direction. Based on the robust tissue adhesion capability, universal reliable measurements of electrophysiological signals generated by various tissues, ranging from rodent sciatic nerve, the muscle, brain, and human skin, are successfully demonstrated.

Moisture-Wicking, Breathable, and Intrinsically Antibacterial Electronic Skin Based on Dual-Gradient Poly(ionic liquid) Nanofiber Membranes

Electronic skin can detect minute electrical potential changes in the human skin and represent the body's state, which is critical for medical diagnostics and human-computer interface development. On the other hand, sweat has a significant effect on the signal stability, comfort, and safety of electronic skin in a real-world application. In this study, by modifying the cation and anion of a poly(ionic liquid) (PIL) and employing a spinning process, a PIL-based multilayer nanofiber membrane (PIL membrane) electronic skin with a dual gradient is created. The PIL electronic skin is moisture-wicking and breathable due to the hydrophilicity and pore size-gradients. The intrinsically antimicrobial activities of PILs allow the safe collection of bioelectrical signals from the human body, such as electrocardiography (ECG) and electromyography (EMG). In addition, a robotic hand may be operated in real-time, and a preliminary human-computer interface can be accomplished by simple processing of the collected EMG signal. This study establishes a novel practical approach for monitoring and using bioelectrical signals in real-world circumstances via the multifunctional electronic skin.

Artificial Sense Technology: Emulating and Extending Biological Senses

Biological senses are critical for the survival of organisms. A great deal of attention has focused on elucidating the underlying physiological mechanisms of the senses, inspiring various sensing techniques. Despite progress in this area, gaps remain between the biological senses and conventional sensing techniques. In this Perspective, we propose the concept of artificial sense technology, which mimics the biological senses but differs in terms of objective sensing and intelligent feedback capabilities. We first summarize recent progress in the use of nanotechnologies to emulate the biological senses and then outline the advantages of artificial sense technology, which extend the capabilities of its biological counterparts. We envision artificial sense technology as a powerful perceptual interface that will play key roles in sensation substitution, digital healthcare, animal interactions, plant electronics, smart robots, and other areas that enrich the connections of the physical and virtual worlds.

Advances in Medical Wearable Biosensors: Design, Fabrication and Materials Strategies in Healthcare Monitoring

In the past decade, wearable biosensors have radically changed our outlook on contemporary medical healthcare monitoring systems. These smart, multiplexed devices allow us to quantify dynamic biological signals in real time through highly sensitive, miniaturized sensing platforms, thereby decentralizing the concept of regular clinical check-ups and diagnosis towards more versatile, remote, and personalized healthcare monitoring. This paradigm shift in healthcare delivery can be attributed to the development of nanomaterials and improvements made to non-invasive biosignal detection systems alongside integrated approaches for multifaceted data acquisition and interpretation. The discovery of new biomarkers and the use of bioaffinity recognition elements like aptamers and peptide arrays combined with the use of newly developed, flexible, and conductive materials that interact with skin surfaces has led to the widespread application of biosensors in the biomedical field. This review focuses on the recent advances made in wearable technology for remote healthcare monitoring. It classifies their development and application in terms of electrochemical, mechanical, and optical modes of transduction and type of material used and discusses the shortcomings accompanying their large-scale fabrication and commercialization. A brief note on the most widely used materials and their improvements in wearable sensor development is outlined along with instructions for the future of medical wearables.

Mechanomaterials: A Rational Deployment of Forces and Geometries in Programming Functional Materials

The knowledge of mechanics of materials has been extensively implemented in developing functional materials, giving rise to recent advances in soft actuators, flexible electronics, mechanical metamaterials, tunable mechanochromics, regenerative mechanomedicine, etc. While conventional mechanics of materials offers passive access to mechanical properties of materials in existing forms, a paradigm shift is emerging toward proactive programming of materials' functionality by leveraging the force-geometry-property relationships. Here, such a rising field is coined as "mechanomaterials". To profile the concept, the design principles in this field at four scales is first outlined, namely the atomic scale, the molecular scale, the manipulation of nanoscale materials, and the microscale design of structural materials. A variety of techniques have been recruited to deliver the multiscale programming of functional mechanomaterials, such as strain engineering, capillary assembly, topological interlocking, kirigami, origami, to name a few. Engineering optical and biological functionalities have also been achieved by implementing the fundamentals of mechanochemistry and mechanobiology. Nonetheless, the field of mechanomaterials is still in its infancy, with many open challenges and opportunities that need to be addressed. The authors hope this review can serve as a modest spur to attract more researchers to further advance this field.

Emerging Wearable Interfaces and Algorithms for Hand Gesture Recognition: A Survey

Hands are vital in a wide range of fundamental daily activities, and neurological diseases that impede hand function can significantly affect quality of life. Wearable hand gesture interfaces hold promise to restore and assist hand function and to enhance human-human and human-computer communication. The purpose of this review is to synthesize current novel sensing interfaces and algorithms for hand gesture recognition, and the scope of applications covers rehabilitation, prosthesis control, sign language recognition, and human-computer interaction. Results showed that electrical, dynamic, acoustical/vibratory, and optical sensing were the primary input modalities in gesture recognition interfaces. Two categories of algorithms were identified: 1) classification algorithms for predefined, fixed hand poses and 2) regression algorithms for continuous finger and wrist joint angles. Conventional machine learning algorithms, including linear discriminant analysis, support vector machines, random forests, and non-negative matrix factorization, have been widely used for a variety of gesture recognition applications, and deep learning algorithms have more recently been applied to further facilitate the complex relationship between sensor signals and multi-articulated hand postures. Future research should focus on increasing recognition accuracy with larger hand gesture datasets, improving reliability and robustness for daily use outside of the laboratory, and developing softer, less obtrusive interfaces.

A Morphable Ionic Electrode Based on Thermogel for Non-Invasive Hairy Plant Electrophysiology

Plant electrophysiology lays the foundation for smart plant interrogation and intervention. However, plant trichomes with hair-like morphologies present topographical features that challenge stable and high-fidelity non-invasive electrophysiology, due to the inadequate dynamic shape adaptability of conventional electrodes. Here, this issue is overcome using a morphable ionic electrode based on a thermogel, which gradually transforms from a viscous liquid to a viscoelastic gel. This transformation enables the morphable electrode to lock into the abrupt hairy surface irregularities and establish a conformal and adhesive interface. It achieves down to one tenth of the impedance and 4-5 times the adhesive strengths of conventional hydrogel electrodes on hairy leaves. As a result of the improved electrical and mechanical robustness, the morphable electrode can record more than one order of magnitude higher signal-to-noise ratio on hairy plants and maintains high-fidelity recording despite plant movements, achieving superior performance to conventional hydrogel electrodes. The reported morphable electrode is a promising tool for hairy plant electrophysiology and may be applied to diversely textured plants for advanced sensing and modulation.

A Lamellibranchia-inspired epidermal electrode for electrophysiology

The capability to accurately monitor electrophysiological signals and instantly provide feedback to users is crucial for wearable healthcare. However, commercial gel electrodes suffer from drying out and irritation on skin with time, severely affecting signal quality for practical use. Toward a gel-free electrophysiology, epidermal electrodes that can accurately detect biosignals and simultaneously achieve the multifunctional properties of on-skin electronics needs are highly desirable. In this work, inspired by Lamellibranchia, which can adhere tightly to various surfaces using their extensible, adhesive and self-healing byssal threads, we developed a gel-free epidermal electrode to acquire high-quality electrophysiological signals based on a novel polymer substrate design. This polymer (STAR) features extreme stretchability (>2300% strain), high transparency (>90% transmittance at λ = 550 nm), gentle adhesion (adhesion strengths: tens of kPa), and rapid self-healing ability (95% healing efficiency in 10 min). Combined with silver nanowires as conductors, STAR was employed as a self-healing, stretchable and adhesive epidermal electrode for electrophysiological signal recording, showing a signal-to-noise ratio (SNR) even higher than that of commercial electrodes, and being able to control an artificial limb as an intermediate for human-machine interface. We believe our Lamellibranchia inspired STAR will pave a new way to design multifunctional polymers for epidermal electronics, accelerating the development of emerging wearable healthcare.

High-Strength and High-Toughness Silk Fibroin Hydrogels: A Strategy Using Dynamic Host-Guest Interactions

Natural polymer-based hydrogels attract great attention because of their inherent biocompatibility and controllable biodegradability. However, the broad applications of these hydrogels require a combination of high mechanical strength, high toughness, fatigue resistance, as well as self-healing. The integration of this combination into one natural polymer-based hydrogel remains challenging. Here, a molecular design strategy was proposed to fabricate mechanically robust silk fibroin-based hydrogels using host-guest interactions. Silk fibroin molecules was chemically modified with cholesterol (Chol, guest) or β-cyclodextrin (β-CD, host), and host-guest interaction between Chol and β-CD moieties drove the supramolecular assemblies of hydrogels. The dissociation/reassociation behavior of host-guest complexation, serving as sacrificial bonds, endowed hydrogels with effective energy dissipation and rapid self-healing ability. The prepared silk fibroin-based hydrogels exhibited high mechanical strength, high toughness, and remarkable fatigue resistance, superior to conventional silk fibroin hydrogels. Moreover, due to reversible host-guest interactions, hydrogels achieved facile functional recovery after damage without any external stimuli. This design strategy provides an avenue to develop natural polymer-based materials with robust mechanical properties, thus broadening current hydrogel applications.

An artificial sensory neuron with visual-haptic fusion

Human behaviors are extremely sophisticated, relying on the adaptive, plastic and event-driven network of sensory neurons. Such neuronal system analyzes multiple sensory cues efficiently to establish accurate depiction of the environment. Here, we develop a bimodal artificial sensory neuron to implement the sensory fusion processes. Such a bimodal artificial sensory neuron collects optic and pressure information from the photodetector and pressure sensors respectively, transmits the bimodal information through an ionic cable, and integrates them into post-synaptic currents by a synaptic transistor. The sensory neuron can be excited in multiple levels by synchronizing the two sensory cues, which enables the manipulating of skeletal myotubes and a robotic hand. Furthermore, enhanced recognition capability achieved on fused visual/haptic cues is confirmed by simulation of a multi-transparency pattern recognition task. Our biomimetic design has the potential to advance technologies in cyborg and neuromorphic systems by endowing them with supramodal perceptual capabilities.

A Compliant Ionic Adhesive Electrode with Ultralow Bioelectronic Impedance

Simultaneous implementation of high signal-to-noise ratio (SNR) but low crosstalk is of great importance for weak surface electromyography (sEMG) signals when precisely driving a prosthesis to perform sophisticated activities. However, due to gaps with the curved skin during muscle contraction, many electrodes have poor compliance with skin and suffer from high bioelectrical impedance. This causes serious noise and error in the signals, especially the signals from low-level muscle contractions. Here, the design of a compliant electrode based on an adhesive hydrogel, alginate-polyacrylamide (Alg-PAAm) is reported, which eliminates those large gaps through the strong electrostatic interaction and abundant hydrogen bond with the skin. The obtained compliant electrode, having an ultralow bioelectrical impedance of ≈20 kΩ, can monitor even 2.1% maximal voluntary contraction (MVC) of muscle. Furthermore, benefiting from the high SNR of >5:1 at low-level MVC, the crosstalk from irrelevant muscle is minimized through reducing the electrode size. Finally, a prosthesis is successfully demonstrated to precisely grasp a needle based on a 9 mm² Alg-PAAm compliant electrode. The strategy to design such compliant electrodes provides the potential for improving the quality of dynamically weak sEMG signals to precisely control prosthesis in performing purposefully dexterous activity.