Effects of Vaccination against Recombinant FSH or LH Receptor Subunits on Gonadal Development and Functioning Male Rats.

Luteinizing hormone (LH) and follicle-stimulating hormone (FSH) play key roles in regulating testosterone secretion and spermatogenesis in male mammals, respectively, and they maintain the fertility of male animals by binding to their corresponding receptors. We designed and prepared a recombinant LH receptor (LHR) subunit vaccine and a recombinant FSH receptor (FSHR) subunit vaccine and used male Sprague Dawley (SD) rats as a model to examine their effects on testicular development, spermatogenesis, and testosterone secretion in prepubertal and pubertal mammals. Both vaccines (LHR-DTT and FSHR-DTT) significantly decreased the serum testosterone level in prepubertal rats (p < 0.05) but had no effect on the testosterone secretion in pubertal rats; both vaccines decreased the number of cell layers in the seminiferous tubules and reduced spermatogenesis in prepubertal and pubertal rats. Subunit vaccine FSHR-DTT decreased the sperm density in the epididymis in both prepubertal and pubertal rats (p < 0.01) and lowered testicular index and sperm motility in pubertal rats (p < 0.05), whereas LHR-DTT only reduced the sperm density in the epididymis in pubertal rats (p < 0.05). These results indicate that the FSHR subunit vaccine may be a promising approach for immunocastration, but it still needs improvements in effectiveness.

Millimeter-scale magnetic implants paired with a fully integrated wearable device for wireless biophysical and biochemical sensing.

Implantable sensors can directly interface with various organs for precise evaluation of health status. However, extracting signals from such sensors mainly requires transcutaneous wires, integrated circuit chips, or cumbersome readout equipment, which increases the risks of infection, reduces biocompatibility, or limits portability. Here, we develop a set of millimeter-scale, chip-less, and battery-less magnetic implants paired with a fully integrated wearable device for measuring biophysical and biochemical signals. The wearable device can induce a large amplitude damped vibration of the magnetic implants and capture their subsequent motions wirelessly. These motions reflect the biophysical conditions surrounding the implants and the concentration of a specific biochemical depending on the surface modification. Experiments in rat models demonstrate the capabilities of measuring cerebrospinal fluid (CSF) viscosity, intracranial pressure, and CSF glucose levels. This miniaturized system opens the possibility for continuous, wireless monitoring of a wide range of biophysical and biochemical conditions within the living organism.

Functional bio-inspired hybrid fliers with separated ring and leading edge vortices.

Recent advances in passive flying systems inspired by wind-dispersed seeds contribute to increasing interest in their use for remote sensing applications across large spatial domains in the Lagrangian frame of reference. These concepts create possibilities for developing and studying structures with performance characteristics and operating mechanisms that lie beyond those found in nature. Here, we demonstrate a hybrid flier system, fabricated through a process of controlled buckling, to yield unusual geometries optimized for flight. Specifically, these constructs simultaneously exploit distinct fluid phenomena, including separated vortex rings from features that resemble those of dandelion seeds and the leading-edge vortices derived from behaviors of maple seeds. Advanced experimental measurements and computational simulations of the aerodynamics and induced flow physics of these hybrid fliers establish a concise, scalable analytical framework for understanding their flight mechanisms. Demonstrations with functional payloads in various forms, including bioresorbable, colorimetric, gas-sensing, and light-emitting platforms, illustrate examples with diverse capabilities in sensing and tracking.

Closed-Loop Wearable Device Network of Intrinsically-Controlled, Bilateral Coordinated Functional Electrical Stimulation for Stroke.

Innovative functional electrical stimulation has demonstrated effectiveness in enhancing daily walking and rehabilitating stroke patients with foot drop. However, its lack of precision in stimulating timing, individual adaptivity, and bilateral symmetry, resulted in diminished clinical efficacy. Therefore, a closed-loop wearable device network of intrinsically controlled functional electrical stimulation (CI-FES) system is proposed, which utilizes the personal surface myoelectricity, derived from the intrinsic neuro signal, as the switch to activate/deactivate the stimulation on the affected side. Simultaneously, it decodes the myoelectricity signal of the patient's healthy side to adjust the stimulation intensity, forming an intrinsically controlled loop with the inertial measurement units. With CI-FES assistance, patients' walking ability significantly improved, evidenced by the shift in ankle joint angle mean and variance from 105.53° and 28.84 to 102.81° and 17.71, and the oxyhemoglobin concentration tested by the functional near-infrared spectroscopy. In long-term CI-FES-assisted clinical testing, the discriminability in machine learning classification between patients and healthy individuals gradually decreased from 100% to 92.5%, suggesting a remarkable recovery tendency, further substantiated by performance on the functional movement scales. The developed CI-FES system is crucial for contralateral-hemiplegic stroke recovery, paving the way for future closed-loop stimulation systems in stroke rehabilitation is anticipated.

FPGA-based Lightweight QDS-CNN System for sEMG Gesture and Force Level Recognition.

Deep learning (DL) has been used for electromyographic (EMG) signal recognition and achieved high accuracy for multiple classification tasks. However, implementation in resource-constrained prostheses and human-computer interaction devices remains challenging. To overcome these problems, this paper implemented a low-power system for EMG gesture and force level recognition using Zynq architecture. Firstly, a lightweight network model structure was proposed by Ultra-lightweight depth separable convolution (UL-DSC) and channel attention-global average pooling (CA-GAP) to reduce the computational complexity while maintaining accuracy. A wearable EMG acquisition device for real-time data acquisition was subsequently developed with size of 36mm×28mm×4mm. Finally, a highly parallelized dedicated hardware accelerator architecture was designed for inference computation. 18 gestures were tested, including force levels from 22 healthy subjects. The results indicate that the average accuracy rate was 94.92% for a model with 5.0k parameters and a size of 0.026MB. Specifically, the average recognition accuracy for static and force-level gestures was 98.47% and 89.92%, respectively. The proposed hardware accelerator architecture was deployed with 8-bit precision, a single-frame signal inference time of 41.9µs, a power consumption of 0.317W, and a data throughput of 78.6 GOP/s.

Effects of Training and Calibration Data on Surface Electromyogram-Based Recognition for Upper Limb Amputees.

Surface electromyogram (sEMG)-based gesture recognition has emerged as a promising avenue for developing intelligent prostheses for upper limb amputees. However, the temporal variations in sEMG have rendered recognition models less efficient than anticipated. By using cross-session calibration and increasing the amount of training data, it is possible to reduce these variations. The impact of varying the amount of calibration and training data on gesture recognition performance for amputees is still unknown. To assess these effects, we present four datasets for the evaluation of calibration data and examine the impact of the amount of training data on benchmark performance. Two amputees who had undergone amputations years prior were recruited, and seven sessions of data were collected for analysis from each of them. Ninapro DB6, a publicly available database containing data from ten healthy subjects across ten sessions, was also included in this study. The experimental results show that the calibration data improved the average accuracy by 3.03%, 6.16%, and 9.73% for the two subjects and Ninapro DB6, respectively, compared to the baseline results. Moreover, it was discovered that increasing the number of training sessions was more effective in improving accuracy than increasing the number of trials. Three potential strategies are proposed in light of these findings to enhance cross-session models further. We consider these findings to be of the utmost importance for the commercialization of intelligent prostheses, as they demonstrate the criticality of gathering calibration and cross-session training data, while also offering effective strategies to maximize the utilization of the entire dataset.

Hard Magnetic Graphene Nanocomposite for Multimodal, Reconfigurable Soft Electronics.

Soft electronics provide effective means for continuous monitoring of a diverse set of biophysical and biochemical signals from the human body. However, the sensitivities, functions, spatial distributions, and many other features of such sensors remain fixed after deployment and cannot be adjusted on demand. Here, laser-induced porous graphene is exploited as the sensing material, and dope it with permanent magnetic particles to create hard magnetic graphene nanocomposite (HMGN) that can self-assemble onto a flexible carrying substrate through magnetic force, in a reversible and reconfigurable manner. A set of soft electronics in HMGN exhibits enhanced performances in the measurements of electrophysiological signals, temperature, and concentrations of metabolites. All these flexible HMGN sensors can adhere to a carrying substrate at any position and in any spatial arrangement, to allow for wearable sensing with customizable sensitivity, modality, and spatial coverage. The HMGN represents a promising material for constructing soft electronics that can be reconfigured for various applications.

Editorial for the Special Issue on Flexible Sensors and Actuators for Biomedicine.

Flexible sensors and actuators typically rely on functional materials with low Young's moduli or ultrathin geometries [...].

Recent Advancements in Physiological, Biochemical, and Multimodal Sensors Based on Flexible Substrates: Strategies, Technologies, and Integrations.

Flexible wearable devices have been widely used in biomedical applications, the Internet of Things, and other fields, attracting the attention of many researchers. The physiological and biochemical information on the human body reflects various health states, providing essential data for human health examination and personalized medical treatment. Meanwhile, physiological and biochemical information reveals the moving state and position of the human body, and it is the data basis for realizing human-computer interactions. Flexible wearable physiological and biochemical sensors provide real-time, human-friendly monitoring because of their light weight, wearability, and high flexibility. This paper reviews the latest advancements, strategies, and technologies of flexibly wearable physiological and biochemical sensors (pressure, strain, humidity, saliva, sweat, and tears). Next, we systematically summarize the integration principles of flexible physiological and biochemical sensors with the current research progress. Finally, important directions and challenges of physiological, biochemical, and multimodal sensors are proposed to realize their potential applications for human movement, health monitoring, and personalized medicine.

Wearable and flexible electrochemical sensors for sweat analysis: a review.

Flexible wearable sweat sensors allow continuous, real-time, noninvasive detection of sweat analytes, provide insight into human physiology at the molecular level, and have received significant attention for their promising applications in personalized health monitoring. Electrochemical sensors are the best choice for wearable sweat sensors due to their high performance, low cost, miniaturization, and wide applicability. Recent developments in soft microfluidics, multiplexed biosensing, energy harvesting devices, and materials have advanced the compatibility of wearable electrochemical sweat-sensing platforms. In this review, we summarize the potential of sweat for medical detection and methods for sweat stimulation and collection. This paper provides an overview of the components of wearable sweat sensors and recent developments in materials and power supply technologies and highlights some typical sensing platforms for different types of analytes. Finally, the paper ends with a discussion of the challenges and a view of the prospective development of this exciting field.

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa-1) and a broad response range (0-18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.

A dynamically reprogrammable surface with self-evolving shape morphing.

Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines1-3, flexible electronics4,5 and smart medicines6. Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications7-24. Challenges lie in the development of schemes to reprogram target shapes after fabrication, especially when complexities associated with the operating physics and disturbances from the environment can stop the use of deterministic theoretical models to guide inverse design and control strategies25-30. Here we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from the passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 second. Implementing an in situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm yields surfaces that can follow a self-evolving inverse design to morph into a wide range of three-dimensional target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic soft matter, with many unique characteristics.

Double-Sided Wearable Multifunctional Sensing System with Anti-interference Design for Human-Ambience Interface.

Multifunctional sensing systems play important roles in a variety of applications, incluing health surveillance, intelligent prothetics, human-machine/ambinece interfaces, and many others. The richness of the signal and the decoupling among multiple parameters are essential for simultaneous, multimodal measurements. However, current multifunctional sensing fails to decouple interferences from various signals. Here, we propose a double-sided wearable system that both enables multifunctional sensing and avoids the interferences among multiple parameters. Specifically, the sensitivities of system modules to strain are controlled through customizing the pattern and morphology of sensing electrodes as well as the modification of active materials. Compensation of temperature drift and selection of sensing mechanisms ensure the thermal stability of the system. The encapsulation of modules resists the interferences of proximity, normal pressure, and gas molecules at the same time. A double-sided partition layout with serpentine interconnections reduces the effect of motion artifacts and ensures simultaneous operation of electrochemical-sensing modules. Cooperation among decoupled modules acts as the bridge between the perception of ambience changes and the timely feedback of the human body. In addition, to sense the signal at the interface, modules for energy harvesting and storage are also integrated into the system to broaden its application scenarios.

Mechanically Active Materials and Devices for Bio-Interfaced Pressure Sensors-A Review.

Pressures generated by external forces or by internal body processes represent parameters of critical importance in diagnosing physiological health and in anticipating injuries. Examples span intracranial hypertension from traumatic brain injuries, high blood pressure from poor diet, pressure-induced skin ulcers from immobility, and edema from congestive heart failure. Pressures measured on the soft surfaces of vital organs or within internal cavities of the body can provide essential insights into patient status and progression. Challenges lie in the development of high-performance pressure sensors that can softly interface with biological tissues to enable safe monitoring for extended periods of time. This review focuses on recent advances in mechanically active materials and structural designs for classes of soft pressure sensors that have proven uses in these contexts. The discussions include applications of such sensors as implantable and wearable systems, with various unique capabilities in wireless continuous monitoring, minimally invasive deployment, natural degradation in biofluids, and/or multiplexed spatiotemporal mapping. A concluding section summarizes challenges and future opportunities for this growing field of materials and biomedical research.

Integrated, Transparent Silicon Carbide Electronics and Sensors for Radio Frequency Biomedical Therapy.

The integration of micro- and nanoelectronics into or onto biomedical devices can facilitate advanced diagnostics and treatments of digestive disorders, cardiovascular diseases, and cancers. Recent developments in gastrointestinal endoscopy and balloon catheter technologies introduce promising paths for minimally invasive surgeries to treat these diseases. However, current therapeutic endoscopy systems fail to meet requirements in multifunctionality, biocompatibility, and safety, particularly when integrated with bioelectronic devices. Here, we report materials, device designs, and assembly schemes for transparent and stable cubic silicon carbide (3C-SiC)-based bioelectronic systems that facilitate tissue ablation, with the capability for integration onto the tips of endoscopes. The excellent optical transparency of SiC-on-glass (SoG) allows for direct observation of areas of interest, with superior electronic functionalities that enable multiple biological sensing and stimulation capabilities to assist in electrical-based ablation procedures. Experimental studies on phantom, vegetable, and animal tissues demonstrated relatively short treatment times and low electric field required for effective lesion removal using our SoG bioelectronic system. In vivo experiments on an animal model were conducted to explore the versatility of SoG electrodes for peripheral nerve stimulation, showing an exciting possibility for the therapy of neural disorders through electrical excitation. The multifunctional features of SoG integrated devices indicate their high potential for minimally invasive, cost-effective, and outcome-enhanced surgical tools, across a wide range of biomedical applications.

Self-Powered Tactile Sensor for Gesture Recognition Using Deep Learning Algorithms.

A multifunctional wearable tactile sensor assisted by deep learning algorithms is developed, which can realize the functions of gesture recognition and interaction. This tactile sensor is the fusion of a triboelectric nanogenerator and piezoelectric nanogenerator to construct a hybrid self-powered sensor with a higher power density and sensibility. The power generation performance is characterized with an open-circuit voltage VOC of 200 V, a short-circuit current ISC of 8 µA, and a power density of 0.35 mW cm-2 under a matching load. It also has an excellent sensibility, including a response time of 5 ms, a signal-to-noise ratio of 22.5 dB, and a pressure resolution of 1% (1-10 kPa). The sensor is successfully integrated on a glove to collect the electrical signal output generated by the gesture. Using deep learning algorithms, the functions of gesture recognition and control can be realized in real time. The combination of tactile sensor and deep learning algorithms provides ideas and guidance for its applications in the field of artificial intelligence, such as human-computer interaction, signal monitoring, and smart sensing.

Submillimeter-scale multimaterial terrestrial robots.

Robots with submillimeter dimensions are of interest for applications that range from tools for minimally invasive surgical procedures in clinical medicine to vehicles for manipulating cells/tissues in biology research. The limited classes of structures and materials that can be used in such robots, however, create challenges in achieving desired performance parameters and modes of operation. Here, we introduce approaches in manufacturing and actuation that address these constraints to enable untethered, terrestrial robots with complex, three-dimensional (3D) geometries and heterogeneous material construction. The manufacturing procedure exploits controlled mechanical buckling to create 3D multimaterial structures in layouts that range from arrays of filaments and origami constructs to biomimetic configurations and others. A balance of forces associated with a one-way shape memory alloy and the elastic resilience of an encapsulating shell provides the basis for reversible deformations of these structures. Modes of locomotion and manipulation span from bending, twisting, and expansion upon global heating to linear/curvilinear crawling, walking, turning, and jumping upon laser-induced local thermal actuation. Photonic structures such as retroreflectors and colorimetric sensing materials support simple forms of wireless monitoring and localization. These collective advances in materials, manufacturing, actuation, and sensing add to a growing body of capabilities in this emerging field of technology.

Mechanically Guided Hierarchical Assembly of 3D Mesostructures.

3D, hierarchical micro/nanostructures formed with advanced functional materials are of growing interest due to their broad potential utility in electronics, robotics, battery technology, and biomedical engineering. Among various strategies in 3D micro/nanofabrication, a set of methods based on compressive buckling offers wide-ranging material compatibility, fabrication scalability, and precise process control. Previously reports on this type of approach rely on a single, planar prestretched elastomeric platform to transform thin-film precursors with 2D layouts into 3D architectures. The simple planar configuration of bonding sites between these precursors and their assembly substrates prevents the realization of certain types of complex 3D geometries. In this paper, a set of hierarchical assembly concepts is reported that leverage multiple layers of prestretched elastomeric substrates to induce not only compressive buckling of 2D precursors bonded to them but also of themselves, thereby creating 3D mesostructures mounted at multiple levels of 3D frameworks with complex, elaborate configurations. Control over strains used in these processes provides reversible access to multiple different 3D layouts in a given structure. Examples to demonstrate these ideas through both experimental and computational results span vertically aligned helices to closed 3D cages, selected for their relevance to 3D conformal bio-interfaces and multifunctional microsystems.