Review Articles MORE

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  Advances in microneedle electrodes for electromyography acquisition in sports rehabilitation

  Abstract Full Text PDF Electromyography (EMG) is widely used in sports rehabilitation to evaluate muscle activation, coordination, fatigue, and functional recovery, yet reliable recording remains limited by the electrode-skin interface during repeated motion and prolonged wear. Microneedle electrodes offer a distinct interface strategy by penetrating the stratum corneum and forming lower-impedance, more stable electrical contact than conventional wet or dry electrodes. This review discusses microneedle electrodes for EMG acquisition in sports rehabilitation from a design-to-application perspective. We first clarify the interface requirements of EMG recording in rehabilitation settings and the technical rationale for using microneedle interfaces. We then summarize material and structural design strategies in silicon-, polymer-, and metal-based systems, focusing on how they balance penetration capability, mechanical compliance, stretchability, conductivity, and recording stability. Fabrication routes are further examined in terms of material-structure-process coupling, followed by applications in static assessment, dynamic motion monitoring, and clinical rehabilitation evaluation. This review integrates interface requirements, design, manufacturing, and validation to provide a structured overview of microneedle EMG electrodes' capabilities and limitations for sports rehabilitation.

  Electromyography (EMG) is widely used in sports rehabilitation to evaluate muscle activation, coordination, fatigue, and functional recovery, yet reliable recording remains limited by the electrode-skin interface during repeated motion and prolonged wear. Microneedle electrodes offer a distinct interface strategy by penetrating the stratum corneum and forming lower-impedance, more stable electrical contact than conventional wet or dry electrodes. This review discusses microneedle electrodes for EMG acquisition in sports rehabilitation from a design-to-application perspective. We first clarify the interface requirements of EMG recording in rehabilitation settings and the technical rationale for using microneedle interfaces. We then summarize material and structural design strategies in silicon-, polymer-, and metal-based systems, focusing on how they balance penetration capability, mechanical compliance, stretchability, conductivity, and recording stability. Fabrication routes are further examined in terms of material-structure-process coupling, followed by applications in static assessment, dynamic motion monitoring, and clinical rehabilitation evaluation. This review integrates interface requirements, design, manufacturing, and validation to provide a structured overview of microneedle EMG electrodes' capabilities and limitations for sports rehabilitation.
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  Organic electrochemical transistor-based theranostics: materials, mechanisms, and system integration

  Abstract Full Text PDF Organic electrochemical transistors (OECTs), leveraged by their unique volumetric doping mechanism and ultra-high transconductance performance, have emerged as a pivotal device platform for constructing high-performance bioelectronic interfaces. OECT-based theranostics aim to develop intelligent closed-loop systems that integrate sensing, decision-making, and execution, thereby overcoming the latency and discretization limitations of traditional medical models when managing dynamic physiological fluctuations. This article systematically reviews the performance evolution of OECT materials from p-type to n-type, discusses critical strategies for enhancing device stability and transconductance density, such as side-chain engineering and ladder-type molecular design, while emphasizing the essential role of complementary logic circuits in minimizing the static power consumption of implantable electronics. Furthermore, breakthroughs in OECT-based neuromorphic computing are addressed; by simulating synaptic plasticity (STP/LTP) and engineering organic electrochemical neurons (OECNs), a highly efficient sensing-computing closed-loop architecture has been realized. The current application landscape of OECTs in electrophysiological monitoring, neurochemical sensing, and multimodal synergistic sensing is detailed, alongside a summary of high-density array fabrication and system integration strategies, including 3D printing, inkjet printing, and 3D hydrogel integration. Finally, future outlooks are provided, focusing on challenges such as the environmental stability of n-type materials, multimodal signal crosstalk, and long-term clinical reliability.

  Organic electrochemical transistors (OECTs), leveraged by their unique volumetric doping mechanism and ultra-high transconductance performance, have emerged as a pivotal device platform for constructing high-performance bioelectronic interfaces. OECT-based theranostics aim to develop intelligent closed-loop systems that integrate sensing, decision-making, and execution, thereby overcoming the latency and discretization limitations of traditional medical models when managing dynamic physiological fluctuations. This article systematically reviews the performance evolution of OECT materials from p-type to n-type, discusses critical strategies for enhancing device stability and transconductance density, such as side-chain engineering and ladder-type molecular design, while emphasizing the essential role of complementary logic circuits in minimizing the static power consumption of implantable electronics. Furthermore, breakthroughs in OECT-based neuromorphic computing are addressed; by simulating synaptic plasticity (STP/LTP) and engineering organic electrochemical neurons (OECNs), a highly efficient sensing-computing closed-loop architecture has been realized. The current application landscape of OECTs in electrophysiological monitoring, neurochemical sensing, and multimodal synergistic sensing is detailed, alongside a summary of high-density array fabrication and system integration strategies, including 3D printing, inkjet printing, and 3D hydrogel integration. Finally, future outlooks are provided, focusing on challenges such as the environmental stability of n-type materials, multimodal signal crosstalk, and long-term clinical reliability.
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  Ion-migration memristive synaptic devices: mechanisms, device architectures, and integration strategies

  Abstract Full Text PDF Ion-migration memristive synaptic devices provide a physical route for hardware neuromorphic computing by using ionic redistribution, conductive-filament evolution, and interfacial barrier modulation to regulate synaptic weights. However, existing studies are often discussed according to specific material systems or individual device demonstrations, which makes it difficult to compare how different ion-migration mechanisms determine synaptic behavior, device stability, and integration potential. This mini review organizes recent progress from the perspective of operating mechanism and device type. Electrochemical metallization (ECM)-based synaptic devices are discussed with emphasis on metallic-filament formation and the challenge of achieving gradual and reproducible conductance modulation. Filamentary valence-change memory (VCM)-based devices are reviewed in terms of oxygen-vacancy channel evolution, while interfacial VCM devices are examined through interfacial ionic modulation and barrier-controlled analog switching. Hybrid ECM-VCM devices are further discussed as integrated designs that couple multiple ionic processes to balance switching window, stability, and multifunctionality. By linking mobile ionic species, switching pathways, and synaptic functions, this review provides a mechanism-based framework for understanding ion-migration memristive synaptic devices and for identifying the material, interface, and device-level issues that remain before scalable neuromorphic hardware can be realized.

  Ion-migration memristive synaptic devices provide a physical route for hardware neuromorphic computing by using ionic redistribution, conductive-filament evolution, and interfacial barrier modulation to regulate synaptic weights. However, existing studies are often discussed according to specific material systems or individual device demonstrations, which makes it difficult to compare how different ion-migration mechanisms determine synaptic behavior, device stability, and integration potential. This mini review organizes recent progress from the perspective of operating mechanism and device type. Electrochemical metallization (ECM)-based synaptic devices are discussed with emphasis on metallic-filament formation and the challenge of achieving gradual and reproducible conductance modulation. Filamentary valence-change memory (VCM)-based devices are reviewed in terms of oxygen-vacancy channel evolution, while interfacial VCM devices are examined through interfacial ionic modulation and barrier-controlled analog switching. Hybrid ECM-VCM devices are further discussed as integrated designs that couple multiple ionic processes to balance switching window, stability, and multifunctionality. By linking mobile ionic species, switching pathways, and synaptic functions, this review provides a mechanism-based framework for understanding ion-migration memristive synaptic devices and for identifying the material, interface, and device-level issues that remain before scalable neuromorphic hardware can be realized.
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  Application of memristors for efficient neuromorphic computing in tactile sensing

  Abstract Full Text PDF With the rapid development of the Internet of Things (IoT) and wearable electronics, tactile sensors play an indispensable role in intelligent sensing systems. However, traditional tactile sensing systems follow the von Neumann architecture, where sensors and processing units are physically separated. This leads to frequent data transfer of large raw data volumes, causing high latency and energy consumption. Such bottlenecks cannot meet the requirements of real-time closed-loop control and edge intelligence. Inspired by the highly integrated "perception-storage-computation" mechanism of biological sensory systems, memristor-based neuromorphic computing offers a groundbreaking solution beyond conventional approaches. Memristors combine non-volatile storage with tunable resistance. They enable in-situ emulation of synaptic plasticity, in-memory computing, and brain-inspired processing, thereby holding the potential to significantly improve the energy efficiency and response speed of tactile systems. This review systematically discusses the physical mechanisms of mainstream memristors, highlights recent progress in memristor-based neuromorphic computing for tactile sensing, and outlines key challenges and future directions for neuromorphic tactile perception systems.

  With the rapid development of the Internet of Things (IoT) and wearable electronics, tactile sensors play an indispensable role in intelligent sensing systems. However, traditional tactile sensing systems follow the von Neumann architecture, where sensors and processing units are physically separated. This leads to frequent data transfer of large raw data volumes, causing high latency and energy consumption. Such bottlenecks cannot meet the requirements of real-time closed-loop control and edge intelligence. Inspired by the highly integrated "perception-storage-computation" mechanism of biological sensory systems, memristor-based neuromorphic computing offers a groundbreaking solution beyond conventional approaches. Memristors combine non-volatile storage with tunable resistance. They enable in-situ emulation of synaptic plasticity, in-memory computing, and brain-inspired processing, thereby holding the potential to significantly improve the energy efficiency and response speed of tactile systems. This review systematically discusses the physical mechanisms of mainstream memristors, highlights recent progress in memristor-based neuromorphic computing for tactile sensing, and outlines key challenges and future directions for neuromorphic tactile perception systems.