Minimally invasive surgery is widely recognized for its efficacy in treating cardiovascular and cerebrovascular diseases. However, challenges arise when the guidewire navigates through complex and tortuous vessels, as the friction between the guidewire and the vessel wall can significantly impede its movement and potentially damage the vessel. Consequently, this chapter proposes the innovative application of ultrasonic vibration to minimally invasive procedures to mitigate this friction. Sliding tests of the guidewire on a silicon film are conducted to examine the impact of ultrasonic vibration on both the friction coefficient and the sliding distance. The findings indicate that the friction coefficient with ultrasound ( μ_with=0.047 ) is reduced by 16.07 μ_no=0.056 ) without ultrasound. Moreover, the sliding distance of the ultrasonic transducer moving with the tip of the guidewire (s2 = 73.22 mm) is 18.21 times that (s1 = 4.02 mm) of the ultrasonic transducer fixed. Furthermore, when the inclination angle of the silicon film is different (θ = 4.589 ° , θ = 6.123°), the sliding distance increases with the advancing distance.

Objective: Whether it is manual suture or robotic automatic suture, the suture parameters of the kidney directly determine the recovery effect of the wound. However, there is a lack of quantitative research. The purpose of this paper is to reveal the influence of the different suture methods on the effect of the suture operation. Methods: Firstly, an editable three-dimensional model of the kidney was established using CT images. Subsequently, wounds were incised on the surface of the kidney entity and sutures were embedded. Secondly, the ABAQUS software was utilized to conduct a simulation analysis of the suturing process. Thirdly, experiments on the ex vivo porcine renal specimens were sutured manually in parallel to the simulation analysis. Meanwhile, the different tensile forces, under suture intervals, various wound conditions, and suturing methods, were measured to derive the tensile force values. Finally, a comparative study of finite element analysis and specimen experiments was performed. Results: The results showed that the 5 mm suture interval and the internal figure-of-eight suture are the optimal choice for suture and the suture of circular wounds is more difficult than elliptical wounds and rectangular wounds, the tensile force is around 0.3-0.5 N. Conclusion: This paper presents the variation law of the tensile force for different wounds and provides the optimal suturing method for both manual and robotic autonomous suturing. Significance: By revealing the influence of different suture methods and providing the optimal suturing method, it can contribute to improving the suture operation effect and promoting the development of suture technology.

Abstract The purpose of this study is to improve the performance of high-precision robot joints in terms of control accuracy and running stability, focusing on the adaptive control and optimal design of permanent magnet synchronous motor. In view of the influence of time-varying disturbance and measurement noise, this study gives a strict stability proof to ensure that the system meets the uniform ultimate boundedness (UUB), and corrects the misjudgment of traditional analysis methods under nonlinear conditions. By constructing a response surface model with sensitive weight of magnetic parameters, the accuracy and optimization range of the model are improved, and the total harmonic distortion of stator current is included in the optimization target. The simulation incorporated the nonlinear characteristics of the inverter. To assess the rationality of the motor structural design, a quantitative evaluation framework was established, and a dedicated simulation module was developed to verify joint control accuracy and operational stability. This study thereby achieved a closed-loop analysis spanning motor optimization and system-level performance validation. These extensions effectively fill the analysis gap in the process of transforming control algorithm and motor performance into actual robot joint application. The results suggest that the improved algorithm empowers accurate parameter identification. The motor efficiency increased from 91.50% to 91.95%, while the cogging torque decreased from 148.51 mN·m to 20.84 mN·m, representing a reduction of 85.99%. In the joint-level simulations, low-speed velocity fluctuations were suppressed to below 1.2%, and the root-mean-square tracking error at high speeds was reduced by 35%. Comparative analyses with recursive least squares and the non-dominated sorting genetic algorithm III (NSGA-III) verified the effectiveness and superiority of the proposed method. These findings provide simulation-based evidence supporting the practical compatibility and potential application value of the proposed approach in high-precision robotic joint systems.

The Fracture Reduction Robot (FRR) is a crucial component of robot-assisted fracture correction technology. However, long-term clinical experiments have identified significant challenges with the forward kinematics of the parallel FRR, notably slow computation speeds and low precision. To address these issues, this paper proposes a hybrid algorithm that integrates the Newton method with a genetic algorithm. This approach harnesses the rapid computation and high precision of the Newton method alongside the strong global convergence capabilities of the genetic algorithm. To comprehensively evaluate the performance of the proposed algorithm, comparisons are made against the analytical method and the Additional Sensor Algorithm (ASA) using identical computational examples. Additionally, iterative comparisons of iteration counts and precision are conducted between traditional numerical methods and the Newton-Genetic algorithm. Experimental results show that the Newton-Genetic algorithm achieves a balance between computation speed and precision, with an accuracy reaching the 10-4 mm order of magnitude, effectively meeting the clinical requirements for fracture reduction robots in medical correction. (c) 2025 The Author(s). Published by Elsevier B.V. on behalf of Shandong University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

(1) Background: Patients bedridden due to accidental injuries, diseases, or age-related functional impairments require accelerated recovery of autonomous limb movement. A prone-position rehabilitation training device was developed to provide training intensity tailored to patients’ motor capabilities. (2) Methods: Based on principles of human prone limb motion mechanics and torque balance, this study analyzed joint torque during limb movements using optical motion capture and six-dimensional force plate data. Joint torque curves during prone-position training were simulated, and a prototype device was developed. Prototype assembly and experimental validation of device–human synergy was conducted. (3) Results: Comparative analysis of joint torques between healthy individuals and patients revealed that joint torque increases as limbs contract inward. The maximum torque for upper limb joints was approximately 3.5 Nm, while the knee joint torque reached around 40 Nm. (4) Conclusions: Prototype testing confirmed the device’s design rationality, meeting human–machine synergy and rehabilitation training intensity requirements. This study provides a reference for the design of prone-position rehabilitation training devices.

With the global ecological environment facing continuous deterioration, effective monitoring of arboreal birds in complex canopy environments remains challenging due to limitations of conventional drones in endurance, size, and habitat disturbance. To address these challenges, this paper presents an ant-inspired micro quadrotor UAV equipped with a lightweight bistable gripper system mimicking the mandibular morphology of leafcutter ants. The design integrates shape memory alloy (SMA)-driven actuation and thermoplastic polyurethane (TPU)-based adaptive grippers, enabling rapid deformation (71 ms switching time) and energy-efficient operation (zero power consumption during perching). Experimental results demonstrate exceptional adaptability in grasping irregular objects (e.g., branches, pen caps) with an 8:1 payload-to-weight ratio. Field tests confirm stable navigation through dense foliage and reliable perching at heights exceeding 5 meters. The system’s compact dimensions (7 cm diameter, 70.5 g weight) and biomimetic approach offer a non-invasive solution for prolonged wildlife observation. This work advances bistable actuator design by combining bio-inspired structural optimization with rapid energy transition principles, showing potential in agile robotics and environmental sensing.

Flexible wearable spinal robots are a new type of medical rehabilitation assistive device that has emerged in recent years. They aim to provide spinal support, rehabilitation training, or assistance for daily activities by mimicking the softness and adaptability of living organisms. Porous structures play a crucial role in the design and manufacturing of flexible robots, as their tunable mechanical and permeability properties enable precise control over the flexibility and breathability of the robots. In this paper, we propose a triple periodic minimal surface (TPMS) gradient fusion design method based on variable volume fractions. This method constructs four gradient-fused porous structures by fusing two TPMS structures with variable volume fractions, namely body-centered cubic I-WP and face-centered cubic F-RD, and investigates the fabrication of polymorphic flexible TPMS structures using additive manufacturing technology. Simulation and physical experimental results indicate that among the four novel structures constructed, the I-F-dx structure outperforms the I-F-xd, I-F-dxd, and I-F-xdx structures in terms of strength and energy absorption performance. Furthermore, the I-F-dx porous structure exhibits the highest permeability, while the I-F-xd structure has the lowest permeability, with the I-F-dxd and I-F-xdx structures falling between the two. Based on patient body surface information monitored by multi-sensor fusion technology, the designed porous structures are applied to optimize the wearable spinal robot to meet individual patient needs. Therefore, designing novel porous structures with excellent performance holds potential application value in the field of variable stiffness and breathability optimization for wearable spinal robots.

The effectiveness and accuracy of the planning of reverse shoulder arthroplasty plays a key role in the success of the surgery. In this paper, an automated reverse shoulder arthroplasty planning method based on point cloud processing is proposed. CT data of 55 patients were retrospectively collected, and 3D reconstruction was performed using 3D Slicer software to obtain the skeletal model of the shoulder joint area, which was converted into point cloud data. Accurate segmentation of the scapula and articular glenoid was realized by the PointNet++ network, which provided the basis for surgical planning. In the study, PCA and RANSAC algorithms were used to extract the humeral stem axis and the feature points of the scapular glenoid, respectively, and then automatically plan the surgical paths. The results of the study showed that the average differences between this automatic planning method and the actual surgical results in surgical path planning on the humeral and scapular were 2.247 mm and 2.604 mm, respectively, and the angular differences were 1.932° and 3.686°, respectively, which were within acceptable ranges, proving the effectiveness and accuracy of the proposed method.

(1) Background: A severe decline in knee joint function significantly affects the mobility of the elderly, making it a key concern in the field of geriatric health. To alleviate the pressure on the knee joints of the elderly during daily movements such as sitting and standing, effective biomechanical solutions are required. (2) Methods: In this study, a biomechanical framework was established based on mechanical analysis to derive the transfer relationship between the ground reaction force and the knee joint moment. Experiments were designed to collect knee joint data on the elderly during the sit-to-stand process. Meanwhile, magnetic resonance imaging (MRI) images were processed through a medical imaging control system to construct a detailed digital 3D knee joint model. A finite element analysis was used to verify the model to ensure the accuracy of its structure and mechanical properties. An improved radial basis function was used to fit the pressure during the entire sit-to-stand conversion process to reduce the computational workload, with an error of less than 5%. In addition, a small-target human key point recognition network was developed to analyze the image sequences captured by the camera. The knee joint angle and the knee joint pressure distribution during the sit-to-stand conversion process were mapped to a three-dimensional interactive platform to form a digital twin system. (3) Results: The system can effectively capture the biomechanical behavior of the knee joint during movement and shows high accuracy in joint angle tracking and structure simulation. (4) Conclusions: This study provides an accurate and comprehensive method for analyzing the biomechanical characteristics of the knee joint during the movement of the elderly, laying a solid foundation for clinical rehabilitation research and the design of assistive devices in the field of rehabilitation medicine.

To address the issues of low efficiency and difficult localization in search and rescue, a dual-layer task planning algorithm based on UAVs-human cooperation for search and rescue is proposed, which mainly includes the search layer for UAVs and the execution layer for rescuers. Firstly, in the search layer, to solve the problems of uneven task allocation and redundant coverage paths of heterogeneous UAVs, a coverage path optimization based on cluster algorithm (CPOC) is adopted. It applies the K-means algorithm with the proportional constraint to allocate the appropriate task-area for each UAV, and uses the non-redundant exact cellular decomposition method to achieve more efficient planning of the subregion coverage paths, meanwhile, those paths are connected by the Min-Max Ant System. Secondly, in the execution layer, the Rapidly-exploring Random Tree star with dynamic guidance mechanism (DG-RRT*) is introduced to improve the performance of path planning for rescuers in the indoor environment. By comparing the different levels of the target locations, this mechanism guides the RRT to explore purposefully to avoid the algorithm being trapped in the local optimum. Finally, compared with the classical algorithm, the total task time of CPOC in the two examples is reduced by 7.3 % and 27.8 % respectively. DG-RRT* can obtain the effective solution in a shorter time under the premise of ensuring the optimal path length. The results indicate that our algorithm can improve the efficiency of search and rescue route planning as well as the accuracy of the solutions.

Recently, there has been increased attention on the treatment of cartilage repair. Overall, we constructed PHBVHHx-COL, a composite hydrogel of PHBVHHx-co-PEG and collagen, and evaluated its cartilage repair efficacy through in vitro and in vivo studies using hydrogel loaded with peripheral blood-derived mesenchymal stem cells (PBMSCs). Rheological properties and compressive mechanical properties of the hydrogels were systematically evaluated. The cytocompatibility of the hydrogels was evaluated using the Cell Counting Kit-8 test, live/dead staining, scratch test, and transwell test. The effect of chondrogenic differentiation of PBMSCs on hydrogels was evaluated using immunofluorescence staining and reverse transcription-polymerase chain reaction. Furthermore, the in vivo cartilage repair ability of the hydrogels was confirmed following in situ injections in rabbit chondral defect models. Finally, the induced polarization of the hydrogel scaffold on macrophages was explored by the expression of CD86 and CD206. In vitro experimental results confirmed that PHBVHHx-COL-gel led to better cell migration, proliferation, and chondrogenic differentiation than PHBVHHx-PEG and COL hydrogels. Hematoxylin and eosin staining indicated that the tissue of the repaired area in the PHBVHHx-COL group was nearly in fusion with the surrounding normal tissue and the reconstruction of subchondral bone was good. Safranin-O staining and COL-2 immunohistochemistry indicated that the tissue of the repaired area in the PHBVHHx-COL group had more cartilage-specific matrix secretion. The PHBVHHx-COL group exhibited more M2 macrophage infiltration and less M1 macrophage presentation than the other groups. This study demonstrated that PHBVHHx-COL scaffolds loaded with PBMSCs significantly promoted the repair of cartilage injury through immune regulation by M2 polarization and could be potential candidates for cartilage tissue engineering.

The issue of aging population has become a severe problem that restricts global development. Thus, the development of bathing robots for the elderly is of great significance for the national strategy of actively addressing population aging. However, there is a lack of systematic review and analysis for the elderly bathing aids and robots, and the trend of the future development is also unclear. Therefore, by reviewing the relevant literature, this paper systematically analyzes the technical characteristics and usage scenarios of the lying, sitting and auxiliary posture, based on the bathing methods, bathing modes, and post bath care, which can clarify the current research status of bathing aids and robots for the elderly. Meanwhile, from the perspectives of the structural design, motion control and information intelligence, the key technologies and existing problems of bathing aids and robots are elaborated, and the relevant technical system is sorted out. Finally, based on the future of technological elderly care and the elderly bathing needs, the development trend of elderly bathing aids and robots is prospected, and the reference and suggestions for its research and development is provided, which has positive research significance.

This paper develops a networked stool and pee management system integrating Internet of Things technology to tackle the challenges associated with fecal care for bedridden elderly individuals. The system is designed to facilitate comprehensive management encompassing bowel dysfunction assessment, rehabilitation training, and cleaning care. Utilizing the MQTT protocol, the research encompasses the system’s architectural design, software development, and application validation, with the objective of enhancing elderly care quality. Following an ethical review, the system will soon enter the clinical trial phase.

This paper investigates an impedance-based iterative learning sliding mode control scheme for robot-assisted bathing, taking into consideration scenarios with unknown model parameters. Initially, the utilization of impedance control is not confined to merely adjusting the desired trajectory but is also instrumental in ensuring active compliance control during the robot-assisted bathing procedure. Furthermore, an iterative learning control (ILC) is devised to estimate the iteration-invariant dynamic parameters, which are intricate and challenging to precisely ascertain in practical applications. To mitigate the effect of divergent initial conditions in ILC, a trajectory reconstruction method is introduced, thus ensuring the convergence of tracking errors even when starting from random initial states. Moreover, an adaptive sliding mode control mechanism is proposed to counteract non-parametric external disturbances and the torque generated through human-machine interaction during the bathing process. The convergence of the double closed-loop system in both the time and iterative domains is demonstrated through the application of the composite energy function method. Eventually, the efficacy and superiority of the control strategy outlined in this paper are jointly verified through co-simulation employing MATLAB and ADAMS.

Sub-millimeter insertion tasks are indispensable tasks in intelligent manufacturing and aerospace unmanned assembly. To date, traditional methods based on visual positioning and force perception rely on establishing contact state models, which exhibit poor robustness. Meanwhile, reinforcement learning-based methods need a larger exploration space, leading to low learning efficiency. This paper proposed PEPL, a two-stage insertion method combining visual positioning and Primitives Learning. Firstly, a visual positioning method based on Siamese networks is used for pose estimation, narrowing down the reinforcement learning workspace. Next, leveraging the pose estimation results as prior knowledge, the reinforcement learning insertion algorithm based on primitive learning completes the final insertion process. Additionally, the design of a hybrid action space enhances the algorithm’s learning efficiency and facilitates its transferability to other objects. Extensive experiments have demonstrated the effectiveness of the two-stage paradigm. Furthermore, experiments conducted on real robots have confirmed that PEPL can achieve a high success rate in completing sub-millimeter insertion tasks. In summary, the proposed PEPL meets the requirements for sub-millimeter precision assembly and ensures the algorithm’s efficiency and robustness.

Leveraging the instability in bistable structures to rapidly release the stored energy is often observed in nature to improve survival and reproduction. Bistable actuators have endowed soft grippers with superior performances such as fast response and self-lock ability. However, current bistable grippers are merely determined by their structural parameters in the design processes, and their grasping modes are usually restricted. In this article, we propose a novel type of reprogrammable bistable actuators. We introduce the design, modeling, and verification of the actuators. The results show that when reprogrammed to its ultrasensitive state with a minimal energy barrier, the trigger force required to induce the fast snap-through can be reduced to less than 0.005 times of its maximum value. In this process, only a minimal energy of 0.001 mJ was needed to trigger the fast energy release of 13.1 mJ. To demonstrate the advances and uniqueness of the proposed actuator, we also prototyped multiple grippers for multimodal, fast, and ultrasensitive grasping. In the ultrasensitive state, the gripper was able to respond to the contact of the swimming fish and capture it in 0.18 s. This work broadens the frontiers of bistable actuators in the design of functional robotic grippers.

Flexible flat cable (FFC) detection is the premise of robot 3C assembly and is challenging because FFCs are often non-axis aligned with arbitrary orientations having cluttered surroundings. However, to date, the traditional robotic object detection methods mainly regress the object horizontal bounding box, in which the size and aspect ratios do not reflect the actual shape of the target object and hardly separate the FFCs in dense. In this paper, rotated object detection was introduced into FFC detection, and a YOLO-based arbitrary-oriented FFC detection method named YOLOOD was proposed. Firstly, oriented bounding boxes are used to reflect the object’s physical size and angle information and better separate the FFCs from the dense background. Secondly, the circular smooth label angular classification algorithm is adopted to obtain the angle information of FFCs. Finally, the head point regression branch is introduced to distinguish between the head and the tail of the FFC and expand the range of FFC detection angle to [ 0^∘, 360^∘) . The proposed YOLOOD can reach the detection performance with an average precision of 90.82

骨折复位及畸形矫正机器人对于人体肢体功能的重建具有积极的意义,其轨迹规划的质量直接影响着术后的效果和机器人的实用性,然而目前系统的轨迹规划研究分析较少.简述了骨折复位及畸形矫正机器人国内外发展现状,分析了断骨复位、重建轨迹规划的关键技术和共性问题,从轨迹规划的发展历程、分类以及求解方法三个方面对骨折复位及畸形矫正机器人的轨迹规划研究进展和关键技术进行了综述,并就目前存在的问题和未来发展趋势进行了总结分析,以期为骨折复位及畸形矫正机器人的轨迹规划提供参考和建议,具有积极的研究意义.

相对于传统的矫形鞋垫制作方法,3D打印矫形鞋垫具有集约高效的特点,但目前在设计、打印、材料等方面仍存在一些问题,且缺乏系统的研究综述.以矫形鞋垫的制作方法为切入点,综述了 3D打印矫形鞋垫的打印工艺、打印材料及研究现状,分析了目前3D打印矫形鞋垫研究存在的问题,并结合矫形鞋垫性能的提升和现代科学技术的发展,预测了 3D打印矫形鞋垫的未来发展趋势.