Surgical robots represent one of the important diagnostic and treatment methods in the field of surgery. In recent years, artificial intelligence (AI) has been increasingly used in the field of surgical medicine, especially in the field of robotic-assisted surgery. This article reviews the common modes of AI in surgical robotics, enumerates the surgical robots available in the market, and summarizes some difficulties and challenges in the application of AI in surgical robotics through literature reviews, website visits and investor press releases analysis of target companies.
Artificial Intelligence ; Robotic Surgical Procedures ; Robotics ; Humans

Medical robotic arm often encounters multi-source and nonlinear errors during the calibration process, making it difficult for traditional mathematical modeling methods to fully characterize system error features, thereby limiting further improvement in calibration accuracy. In this study, a robotic arm parameter error identification model is established, and a calibration method based on an adaptive long short-term memory (ALSTM) neural network is proposed. The method incorporates a particle swarm optimization (PSO) algorithm to optimize the weights of each layer of the LSTM neural network, enabling more effective fitting of robotic arm kinematic errors and ultimately yielding more accurate Denavit-Hartenberg (D-H) parameters. To validate the proposed approach, 110 sets of experimental data are collected using the HSR-JR680 robotic arm calibration system. Experimental results demonstrate that the ALSTM model reduces the root mean square error (RMSE) by 23.07%-80.39% compared to traditional calibration methods, and shortens the convergence time by 32.44% compared to a standard LSTM model. The optimized D-H parameters obtained meet the high-precision calibration requirements of medical robotic arm, confirming the effectiveness of the proposed method.
Calibration ; Neural Networks, Computer ; Algorithms ; Robotics ; Robotic Surgical Procedures ; Models, Theoretical

With the continuous progress of medical technology, the application of stereotactic surgical robots in the field of neurosurgical operations has become increasingly extensive and important. This paper focuses on the registration principle of ultra-wideband positioning technology in stereotactic surgical robots during neurosurgical operations. It elaborates in detail on the processes of positioning and navigation, and illustrates different registration algorithms with examples. In addition, this paper looks ahead to the future development directions of ultra-wideband positioning technology in surgical robots, aiming to provide references for further development of surgical robots.
Neurosurgical Procedures/instrumentation* ; Robotic Surgical Procedures/methods* ; Algorithms ; Robotics/methods*

The peripheral pulmonary lesions are located far from the central airway and close to the pleura, so it is a challenge for clinical diagnosis of their nature through biopsy. Therefore, the Ion robot-assisted bronchoscopy system which has started its commercialization in China is proposed to diagnose and treat peripheral pulmonary lesions. The Ion system can be used for navigation, registration, biopsy and treatment. In this paper, the structural principle of the Ion system is expounded, and its technical advantages such as shape perception, slender catheter and flexible operation are summarized. It represents the latest development direction of the diagnosis and treatment of peripheral pulmonary lesions. Then, the clinical application and development status of the Ion system are analyzed and discussed in detail. Finally, the development trend of the robot-assisted bronchoscopy system is prospected, which provides new ideas for realizing the "integrated and one-stop" diagnosis and treatment services for peripheral pulmonary lesions based on this system.
Bronchoscopy/instrumentation* ; Humans ; Robotics ; Robotic Surgical Procedures

OBJECTIVES: To synthesize a temperature-responsive multimodal motion microrobot (MMMR) using temperature and magnetic field-assisted microfluidic droplet technology to achieve targeted drug delivery and controlled drug release. METHODS: Microfluidic droplet technology was utilized to synthesize the MMMR by mixing gelatin with magnetic microparticles. The microrobot possessed a magnetic anisotropy structure to allow its navigation and targeted drug release by controlling the temperature field and magnetic field. In the experiment, the MMMR was controlled to move in a wide range along a preset path by rotating a uniform magnetic field, and the local circular motion was driven by a planar rotating gradient magnetic field of different frequencies. The MMMR was loaded with simulated drugs, which were released in response to laser heating. RESULTS: Driven by a rotating magnetic field, the MMMR achieved linear motion following a predefined path. The planar gradient rotating magnetic field controlled circular motion of the MMMR with an adjustable radius, utilizing the centrifugal force generated by rotation. The drug-loaded MMMR successfully reached the target location under magnetic guidance, where the gelatin matrix was melted using laser heating for accurate drug release, after which the remaining magnetic particles were removed using magnetic field. CONCLUSIONS The MMMR possesses multimodal motion capabilities to enable precise navigation along a predefined path and dynamic regulation of drug release within the target area, thus having great potential for a wide range of biomedical applications.
Drug Delivery Systems/methods* ; Temperature ; Drug Liberation ; Magnetic Fields ; Robotics ; Gelatin/chemistry* ; Delayed-Action Preparations ; Microfluidics ; Motion

During transfer tasks, the dual-arm nursing-care robot require a human-robot mechanics model to determine the balance region to support the patient safely and stably. Previous studies utilized human-robot two-dimensional static equilibrium models, ignoring the human body volume and muscle torques, which decreased model accuracy and confined the robot ability to adjust the patient's posture in three-dimensional spatial. Therefore, this study proposes a three-dimensional spatial mechanics modeling method based on individualized human musculoskeletal multibody dynamics. Firstly, based on the mechanical features of dual-arm support, this study constructed a foundational three-dimensional human-robot mechanics model including body posture, contact position and body force. With the computed tomography data from subjects, a three-dimensional femur-pelvis-sacrum model was reconstructed, and the individualized musculoskeletal dynamics was analyzed using the ergonomics software, which derived the human joint forces and completed the mechanic model. Then, this study established a dual-arm robot transfer platform to conduct subject transfer experiments, showing that the constructed mechanics model possessed higher accuracy than previous methods. In summary, this study provides a three-dimensional human-robot mechanics model adapting to individual transfers, which has potential application in various scenarios such as nursing-care and rehabilitating robots.
Humans ; Robotics ; Biomechanical Phenomena ; Posture ; Imaging, Three-Dimensional ; Nursing Care

Traditional manual testing of ventilator performance is labor-intensive, time-consuming, and prone to errors in data recording, making it difficult to meet the current demands for testing efficiency in the development and manufacturing of ventilators. Therefore, in this study we designed an automated testing system for essential performance parameters of ventilators. The system mainly comprises a ventilator airflow analyzer, an automated switch module for simulated lungs, and a test control platform. Under the control of testing software, this system can perform automated tests of critical performance parameters of ventilators and generate a final test report. To validate the effectiveness of the designed system, tests were conducted on two different brands of ventilators under four different operating conditions, comparing tidal volume, oxygen concentration, and positive end expiratory pressure accuracy using both the automated testing system and traditional manual methods. Bland-Altman statistical analysis indicated good consistency between the accuracy of automated tests and manual tests for all respiratory parameters. In terms of testing efficiency, the automated testing system required approximately one-third of the time needed for manual testing. These results demonstrate that the designed automated testing system provides a novel approach and means for quality inspection and measurement calibration of ventilators, showing broad application prospects.
Ventilators, Mechanical/standards* ; Equipment Design ; Humans ; Automation

To solve the safety problems caused by the restriction of interaction space and the singular configuration of rehabilitation robot in terminal traction upper limb rehabilitation training, a trajectory planning and tracking control scheme for rehabilitation training is proposed. The human-robot safe interaction space was obtained based on kinematics modeling and rehabilitation theory, and the training trajectory was planned based on the occupational therapy in rehabilitation medicine. The singular configuration of the rehabilitation robot in the interaction space was avoided by exponential adaptive damped least square method. Then, a nonlinear controller for the upper limb rehabilitation robot was designed based on the backstepping control method. Radial basis function neural network was used to approximate the robot model information online to achieve model-free control. The stability of the controller was proved by Lyapunov stability theory. Experimental results demonstrate the effectiveness and superiority of the proposed singular avoidance control scheme.
Humans ; Upper Extremity ; Robotics/methods* ; Biomechanical Phenomena ; Neural Networks, Computer ; Traction/methods* ; Algorithms

The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine and intelligent care. However, the artificial intelligent medical device sector still faces significant challenges, such as data privacy protection and algorithm reliability. This study, based on invention patent analysis, revealed the technological innovation trends in the field of artificial intelligent medical devices from aspects such as patent application time trends, hot topics, regional distribution, and innovation players. The results showed that global invention patent applications had remained active, with technological innovations primarily focused on medical image processing, physiological signal processing, surgical robots, brain-computer interfaces, and intelligent physiological parameter monitoring technologies. The United States and China led the world in the number of invention patent applications. Major international medical device giants, such as Philips, Siemens, General Electric, and Medtronic, were at the forefront of global technological innovation, with significant advantages in patent application volumes and international market presence. Chinese universities and research institutes, such as Zhejiang University, Tianjin University, and the Shenzhen Institute of Advanced Technology, had demonstrated notable technological innovation, with a relatively high number of patent applications. However, their overseas market expansion remained limited. This study provides a comprehensive overview of the technological innovation trends in the artificial intelligent medical device field and offers valuable information support for industry development from an informatics perspective.
Artificial Intelligence ; Patents as Topic ; Humans ; Inventions ; China ; Brain-Computer Interfaces ; Telemedicine ; Equipment and Supplies ; Robotics ; Algorithms

OBJECTIVE: To explore the advantages and effectiveness of the independently developed intelligent orthopedic robot-assisted distal locking of femoral intramedullary nails. METHODS: Thirty-two adult cadaveric femur specimens were randomly divided into two groups, with 16 specimens in each group. The experimental group used the intelligent orthopedic robot to assist in the distal locking of femoral intramedullary nail holes, while the control group used the traditional method of manual locking under X-ray fluoroscopy. The locking time, fluoroscopy times, and the success rate of first locking were recorded and compared between the two groups. RESULTS: The locking time of the experimental group was (273.94±38.67) seconds, which was shorter than that of the control group [(378.38±152.72) seconds], and number of fluoroscopies was (4.56±0.81) times, which was less than that of the control group [(8.00±3.98) times]. The differences were significant [ MD=73.054 (-37.187, 85.813), P=0.049; MD=1.969 (-1.437, 2.563), P=0.002]. The first locking success rate of the experimental group was 100% (16/16), which was significantly higher than that of the control group (68.75%, 11/16) ( P=0.043). CONCLUSION The efficiency of distal locking of femoral intramedullary nails assisted by the intelligent orthopedic robot is significantly higher than that of the traditional manual locking method under fluoroscopy, as it can markedly reduce the time required for distal locking of femoral intramedullary nails, decrease intraoperative radiation exposure, and increase the success rate of locking.
Humans ; Fracture Fixation, Intramedullary/instrumentation* ; Bone Nails ; Fluoroscopy ; Femur/diagnostic imaging* ; Femoral Fractures/surgery* ; Robotic Surgical Procedures/instrumentation* ; Cadaver ; Adult ; Robotics ; Male