Soft Electronics for Health Monitoring Assisted by Machine Learning

Highly Promising 2D/1D BP-C/CNT Bionic Opto-Olfactory Co-Sensory Artificial Synapses for Multisensory Integration

The development of high-performance artificial synaptic neuromorphic devices poses a significant challenge in the creation of biomimetic sensing neural systems that seamlessly integrate both sensory and computational functionalities. In pursuit of this objective, promising bionic opto-olfactory co-sensory artificial synapse devices are constructed utilizing the BP-C/CNT (2D/1D) hybrid filter membrane as the resistive layer. Experimental results demonstrated that the devices seamlessly integrated the light modulation, gas detection, and biological synaptic functions into a single device while addressing the challenge with separating artificial synaptic devices from sensors. These devices offered the following advantages: 1) Simulating visual synapses, they can effectively replicate fundamental synaptic functions under both electrical and optical stimulation. 2) By emulating olfactory synapse responses to specific gases, they can achieve ultra-low detection limits and rapid identification of ethanol and acetone gases. 3) They enable photo-olfactory co-sensing simulations that mimic synaptic function under light-modulated pulse conditions in distinct gas environments, facilitating the study of synaptic learning rules and Pavlovian responses. This work provides a pioneering approach for exploring highly stable 2D BP-based optoelectronics and advancing the development of biomimetic neural systems.

New Carbon Materials for Multifunctional Soft Electronics

Soft electronics are garnering significant attention due to their wide-ranging applications in artificial skin, health monitoring, human-machine interaction, artificial intelligence, and the Internet of Things. Various soft physical sensors such as mechanical sensors, temperature sensors, and humidity sensors are the fundamental building blocks for soft electronics. While the fast growth and widespread utilization of electronic devices have elevated life quality, the consequential electromagnetic interference (EMI) and radiation pose potential threats to device precision and human health. Another substantial concern pertains to overheating issues that occur during prolonged operation. Therefore, the design of multifunctional soft electronics exhibiting excellent capabilities in sensing, EMI shielding, and thermal management is of paramount importance. Because of the prominent advantages in chemical stability, electrical and thermal conductivity, and easy functionalization, new carbon materials including carbon nanotubes, graphene and its derivatives, graphdiyne, and sustainable natural-biomass-derived carbon are particularly promising candidates for multifunctional soft electronics. This review summarizes the latest advancements in multifunctional soft electronics based on new carbon materials across a range of performance aspects, mainly focusing on the structure or composite design, and fabrication method on the physical signals monitoring, EMI shielding, and thermal management. Furthermore, the device integration strategies and corresponding intriguing applications are highlighted. Finally, this review presents prospects aimed at overcoming current barriers and advancing the development of state-of-the-art multifunctional soft electronics.

Naturally Crosslinked Biocompatible Carbonaceous Liquid Metal Aqueous Ink Printing Wearable Electronics for Multi-Sensing and Energy Harvesting

Achieving flexible electronics with comfort and durability comparable to traditional textiles is one of the ultimate pursuits of smart wearables. Ink printing is desirable for e-textile development using a simple and inexpensive process. However, fabricating high-performance atop textiles with good dispersity, stability, biocompatibility, and wearability for high-resolution, large-scale manufacturing, and practical applications has remained challenging. Here, water-based multi-walled carbon nanotubes (MWCNTs)-decorated liquid metal (LM) inks are proposed with carbonaceous gallium-indium micro-nanostructure. With the assistance of biopolymers, the sodium alginate-encapsulated LM droplets contain high carboxyl groups which non-covalently crosslink with silk sericin-mediated MWCNTs. E-textile can be prepared subsequently via printing technique and natural waterproof triboelectric coating, enabling good flexibility, hydrophilicity, breathability, wearability, biocompatibility, conductivity, stability, and excellent versatility, without any artificial chemicals. The obtained e-textile can be used in various applications with designable patterns and circuits. Multi-sensing applications of recognizing complex human motions, breathing, phonation, and pressure distribution are demonstrated with repeatable and reliable signals. Self-powered and energy-harvesting capabilities are also presented by driving electronic devices and lighting LEDs. As proof of concept, this work provides new opportunities in a scalable and sustainable way to develop novel wearable electronics and smart clothing for future commercial applications.

Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording

The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.

Intelligent, Flexible Artificial Throats with Sound Emitting, Detecting, and Recognizing Abilities

In recent years, there has been a notable rise in the number of patients afflicted with laryngeal diseases, including cancer, trauma, and other ailments leading to voice loss. Currently, the market is witnessing a pressing demand for medical and healthcare products designed to assist individuals with voice defects, prompting the invention of the artificial throat (AT). This user-friendly device eliminates the need for complex procedures like phonation reconstruction surgery. Therefore, in this review, we will initially give a careful introduction to the intelligent AT, which can act not only as a sound sensor but also as a thin-film sound emitter. Then, the sensing principle to detect sound will be discussed carefully, including capacitive, piezoelectric, electromagnetic, and piezoresistive components employed in the realm of sound sensing. Following this, the development of thermoacoustic theory and different materials made of sound emitters will also be analyzed. After that, various algorithms utilized by the intelligent AT for speech pattern recognition will be reviewed, including some classical algorithms and neural network algorithms. Finally, the outlook, challenge, and conclusion of the intelligent AT will be stated. The intelligent AT presents clear advantages for patients with voice impairments, demonstrating significant social values.

Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials

The conventional computing architecture faces substantial challenges, including high latency and energy consumption between memory and processing units. In response, in-memory computing has emerged as a promising alternative architecture, enabling computing operations within memory arrays to overcome these limitations. Memristive devices have gained significant attention as key components for in-memory computing due to their high-density arrays, rapid response times, and ability to emulate biological synapses. Among these devices, two-dimensional (2D) material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing, thanks to their exceptional performance driven by the unique properties of 2D materials, such as layered structures, mechanical flexibility, and the capability to form heterojunctions. This review delves into the state-of-the-art research on 2D material-based memristive arrays, encompassing critical aspects such as material selection, device performance metrics, array structures, and potential applications. Furthermore, it provides a comprehensive overview of the current challenges and limitations associated with these arrays, along with potential solutions. The primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing, leveraging the potential of 2D material-based memristive devices.

Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual-Olfactory Crossmodal Perception

The crossmodal interaction of different senses, which is an important basis for learning and memory in the human brain, is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception, but related researches are scarce. Here, we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus (VP) van der Waals heterojunctions. Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene, the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude, reaching up to 7.7 A W-1. Excited by ultraviolet light, multiple synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, short/long-term plasticity and "learning-experience" behavior, were demonstrated with a low power consumption. Furthermore, the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments, enabling it to simulate the interaction of visual and olfactory information for crossmodal perception. This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.

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.

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.

Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

Smart Contact Lenses-A Step towards Non-Invasive Continuous Eye Health Monitoring

According to the age-old adage, while eyes are often considered the gateway to the soul, they might also provide insights into a more pragmatic aspect of our health: blood sugar levels. This potential breakthrough could be realized through the development of smart contact lenses (SCLs). Although contact lenses were first developed for eyesight correction, new uses have recently become available. In the near future, it might be possible to monitor a variety of ocular and systemic disorders using contact lens sensors. Within the realm of glaucoma, SCLs present a novel prospect, offering a potentially superior avenue compared to traditional management techniques. These lenses introduce the possibility of non-invasive and continuous monitoring of intraocular pressure (IOP) while also enabling the personalized administration of medication as and when needed. This convergence holds great promise for advancing glaucoma care. In this review, recent developments in SCLs, including their potential applications, such as IOP and glucose monitoring, are briefly discussed.

Advancements in Wearable and Implantable Intraocular Pressure Biosensors for Ophthalmology: A Comprehensive Review

Glaucoma, marked by its intricate association with intraocular pressure (IOP), stands as a predominant cause of non-reversible vision loss. In this review, the physiological relevance of IOP is detailed, alongside its potential pathological consequences. The review further delves into innovative engineering solutions for IOP monitoring, highlighting the latest advancements in wearable and implantable sensors and their potential in enhancing glaucoma management. These technological innovations are interwoven with clinical practice, underscoring their real-world applications, patient-centered strategies, and the prospects for future development in IOP control. By synthesizing theoretical concepts, technological innovations, and practical clinical insights, this review contributes a cohesive and comprehensive perspective on the IOP biosensor's role in glaucoma, serving as a reference for ophthalmological researchers, clinicians, and professionals.

Conformal Human-Machine Integration Using Highly Bending-Insensitive, Unpixelated, and Waterproof Epidermal Electronics Toward Metaverse

Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals, which is critical to the breakthrough development of metaverse. Interactive electronics face common dilemmas, which realize high-precision and stable touch detection but are rigid, bulky, and thick or achieve high flexibility to wear but lose precision. Here, we construct highly bending-insensitive, unpixelated, and waterproof epidermal interfaces (BUW epidermal interfaces) and demonstrate their interactive applications of conformal human-machine integration. The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection, high flexibility, rapid response time, excellent stability, and versatile "cut-and-paste" character. Regardless of whether being flat or bent, the BUW epidermal interface can be conformally attached to the human skin for real-time, comfortable, and unrestrained interactions. This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics, which offers a new technology route and may further broaden human-machine interactions toward metaverse.