With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.

Epidermal electronics, an emerging interdisciplinary field, is advancing the development of flexible devices that can seamlessly integrate with the skin. These devices, especially Electric Double Layer (EDL)-based sensors, overcome the limitations of conventional electronic devices, offering high sensitivity, rapid response, and excellent stability. Especially, Electric Double Layer (EDL)-based epidermal sensors show great potential in the application of wearable electronics to detect biological signals due to their high sensitivity, fast response, and excellent stability. The advantages can be attributed to the biocompatibility of the materials, the flexibility of the devices, and the large capacitance due to the EDL effect. Furthermore, we discuss the potential of EDL epidermal electronics as wearable sensors for health monitoring and wound healing. These devices can analyze various biofluids, offering real-time feedback on parameters like pH, temperature, glucose, lactate, and oxygen levels, which aids in accurate diagnosis and effective treatment. Beyond healthcare, we explore the role of EDL epidermal electronics in human-machine interaction, particularly their application in prosthetics and pressure-sensing robots. By mimicking the flexibility and sensitivity of human skin, these devices enhance the functionality and user experience of these systems. This review summarizes the latest advancements in EDL-based epidermal electronic devices, offering a perspective for future research in this rapidly evolving field.

The long-term stable monitoring of brain signals, including electroencephalogram (EEG), electrocorticogram (ECoG) and local field potential (LFP), is of great significance for the fundamental research in brain science, artificial intelligence and the diagnosis and treatment of brain-related disorders. Therefore, both non-invasive and invasive brain-machine interfaces based on different materials and structures have been widely studied due to their unique performance. Among these materials, hydrogels have emerged as a promising interface material for brain signal collection systems due to their similar mechanical properties to biological tissues, excellent biocompatibility, strong self-adhesive properties, and exceptional ionic conductive characteristics. This review aims to provide an overview on the recent progress of hydrogel-based brain interfaces in the recording of brain signals with non-invasive and invasive methods. It is expected that this paper will serve as a valuable summary and reference for future research in the hydrogel-based brain interface.

The exploration of multi-dimensional brain activity with high temporal and spatial resolution is of great significance in the diagnosis of neurological disease and the study of brain science. Although the integration of electroencephalogram (EEG) with magnetic resonance imaging (MRI) and computed tomography (CT) provides a potential solution to achieve a brain-functional image with high spatiotemporal resolution, the critical issues of interface stability and magnetic compatibility remain challenging. Therefore, in this research, we proposed a conductive hydrogel EEG electrode with an asymmetrical bilayer structure, which shows the potential to overcome the challenges. Benefiting from the bilayer structure with different moduli, the hydrogel electrode exhibits high biological and mechanical compatibility with the heterogeneous brain-electrode interface. As a result, the impedance can be reduced compared with conventional metal electrodes. In addition, the hydrogel-based ionic conductive electrodes, which are free from metal conductors, are compatible with MRI and CT. Therefore, they can obtain high spatiotemporal resolution multi-dimensional brain information in clinical settings. The research outcome provides a new approach for establishing a platform for early diagnosis of brain diseases and the study of brain science.

Wearable sensors for continuous physiological monitoring during intense exercise face significant challenges, including motion artifacts and skin discomfort. Conductive hydrogels offer a promising solution due to their skin-like flexibility and excellent electrical conductivity, yet their application in extreme conditions like marathon running remains challenges. Here, we develop a MXene-based dual-network hydrogel composed of polyvinyl alcohol (PVA) and tempo-oxidized cellulose nanofibers (TOCNF) crosslinked with MXene nanosheets and borax. This hydrogel exhibits exceptional environmental stability (35 days at 4 °C and 30% relative humidity) and strain sensitivity (gauge factor of 7.79 at 800% strain), while MXene integration provides outstanding antibacterial properties (>99% inhibition). As a proof of concept, under simulated marathon conditions (38°C, 52% relative humidity), the sensor maintains stable performance for 6 h, demonstrating reliable heart rate and respiration monitoring. These capabilities are crucial for identifying early signs of cardiorespiratory abnormalities during endurance sports. Our work presents a robust strategy for developing wearable hydrogel sensors with long-term reliability in extreme environments, offering significant potential for sports medicine, exercise physiology, and continuous health monitoring applications.