X-ray images of the lower limb bone are the most commonly used imaging modality for clinical studies, and segmentation of the femur and tibia in an X-ray image is helpful for many medical studies such as diagnosis, surgery and treatment. In this paper, we propose a new approach based on pure dilated residual U-Net for the segmentation of the femur and tibia bones. The proposed approach employs dilated convolution completely to increase the receptive field, in this way, we can make full use of the advantages of dilated convolution. We conducted experiments and evaluations on datasets provided by Tianjin hospital. Comparison with the classical U-net and FusionNet, our method has fewer parameters, higher accuracy, and converges more rapidly, which means the high performance of the proposed method.

Gels, as typical flexible and soft materials, possess the intrinsic merits of transparent bionic structures, superior mechanical properties and excellent elasticity and viscosity. Recently, gel-based materials have attracted significant attention as a result of their broad and promising applications in biomedical, energy storage, light emission, actuator, military and aerospace devices, especially the intelligent sensing for human-related applications. Among the various flexible and soft pressure sensors, gel-based ones have been gradually studied as an emerging hot research topic. This review focuses on the latest findings in the rapidly developing field of gel-based pressure sensors. Firstly, the classification and properties of the three types of gels and their corresponding fabrication methods are introduced. Secondly, the four basic working principles of pressure sensors are summarized with a comparison of their advantages and disadvantages, followed by an introduction to the construction of pressure sensors based on gel structures. Thirdly, the latest representative research on the three types of gel-based materials towards various wearable sensing applications, including electronic skin, human motion capture, healthcare and rehabilitation, physiological activity monitoring and human-machine interactions, is comprehensively reviewed. Finally, a summary of the remaining challenges and an outline of the development trend for this field are presented.

As an electrically driven artificial muscle, dielectric elastomer actuators (DEAs) are notable for their large deformation, fast response speed, and high energy density, showing significant potential in soft robots. The paper discusses the working principles of DEAs, focusing on their reversible deformation under electric fields and performance optimization through material and structural innovations. Key applications include soft grippers, locomotion robots (e.g., multilegged, crawling, swimming, and jumping/flying), humanoid robots, and wearable devices. The challenges associated with DEAs are also examined, including the actuation properties of DE material, material fatigue, viscoelastic effects, and environmental adaptability. Finally, modeling and control strategies to enhance DEA performance are introduced, with a perspective on future technological advancements in the field.

Wearable exoskeletons can help people with spinal cord injuries regain mobility. For the control of wearable exoskeletons, transient performance, and steady-state performance are the important indices to be considered. In this article, a model-free fractional-order prescribed performance sliding-mode control scheme is proposed for the joint angle tracking control. Time-delay control is developed based on the ultralocal model of the wearable exoskeleton to form the model-free feature. Afterward, a novel exponential-type barrier Lyapunov function is de ed to ensure the prescribed transient performance on the tracking errors. Then, a fractional-order sliding-mode surface is introduced, based on the exponential-type barrier Lyapunov function and fractional-order sliding-mode surface, a fixed-time sliding-mode controller is designed to further enhance the control performance. Benefiting from the abovementioned methods, the proposed controller is model-free and has fixed-time convergence with the prescribed performance. In addition, the adjustable range of the parameters is enlarged by the fractional-order sliding-mode surface. Stability is analyzed based on the Lyapunov theory. Finally, experiments are implemented in the wearable exoskeleton experimental platform, experiment results demonstrate the effectiveness of the proposed scheme.

Hydrogels are three-dimensional polymer networks with excellent flexibility. In recent years, ionic hydrogels have attracted extensive attention in the development of tactile sensors owing to their unique properties, such as ionic conductivity and mechanical properties. These features enable ionic hydrogel-based tactile sensors with exceptional performance in detecting human body movement and identifying external stimuli. Currently, there is a pressing demand for the development of self-powered tactile sensors that integrate ionic conductors and portable power sources into a single device for practical applications. In this paper, we introduce the basic properties of ionic hydrogels and highlight their application in self-powered sensors working in triboelectric, piezoionic, ionic diode, battery, and thermoelectric modes. We also summarize the current difficulty and prospect the future development of ionic hydrogel self-powered sensors.

Tactile sensing is crucial for the safety, accuracy and robustness of the human-robot interactions in the fields of wearable equipment, service robots and healthcare robots. Although many efforts have been made, it still requires much work to develop functional and reliable flexible tactile sensors with superior sensitivity, wide measurement range, high spatial resolution and low cost based on simple structures and easy fabrication. Here, this paper introduces a flexible supercapacitive tactile sensor with outstanding and balanced performance. The tactile sensor contains two layers of flexible electrodes and a layer of ionic-gel coated microfiber matrix to form a supercapacitive sensing structure. The flexible electrodes and the ionic microfiber matrix are processed with scalable techniques such as screen printing and gel-coating, which guarantee the ultra-flexibility and low fabrication cost. The experimental data suggests strong linearity in the pressure-capacitance relationship and high sensitivity (135.9 nF·kPa-1·cm2 or 27.11 kPa-1). Wide pressure measurement range (from 0 kPa to 1200 kPa) is also achieved by balancing structure parameters. Dynamic responses of the tactile sensors could accurately reflect the applied pressure cycles from human-finger tapping and machine pressing. The tactile sensor can map the pressure distribution with a high spatial resolution (>2 points·mm-2) when connected with the specially designed electric circuitry. The spatial resolution from sub-mm to large area makes it promising for various sensing applications in human-robot interactions, from finger touch to body contact. The developed tactile sensor in this study owns superior applicability and universality which makes it a trustworthy candidate to benefit various applications in robotics, flexible electronics and bioengineered equipment.