Hospitals worldwide recognise the importance of data and digital transformation in healthcare. We traced a smart hospital's data-driven journey to build an artificial intelligence and digital ecosystem (AIDE) to achieve healthcare excellence. We measured the impact of data and digital transformation on patient care and hospital operations, identifying key success factors, challenges, and opportunities. The use of data analytics and data science, robotic process automation, AI, cloud computing, Medical Internet of Things and robotics were stand-out areas for a hospital's data-driven journey. In the future, the adoption of a robust AI governance framework, enterprise risk management system, AI assurance and AI literacy are critical for success. Hospitals must adopt a digital-ready, digital-first strategy to build a thriving healthcare system and innovate care for tomorrow.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Hospitals ; Cloud Computing ; Robotics ; Internet of Things ; Data Science

OBJECTIVE: To observe the clinical efficacy of heat-sensitive moxibustion robot for improving the depressive state of methamphetamine addicts during withdrawal period. METHODS: A total of 60 patients with methamphetamine addiction accompanied with depressive state were randomly divided into an observation group (40 cases, 4 cases dropped out) and a control group (20 cases, 2 cases dropped out). The control group received routine health education and addiction treatment in compulsory isolation drug rehabilitation center. On the basis of the treatment in the control group, in the observation group, the heat-sensitive moxibustion robot was used to locate sensitive points at the Shenque (CV8) and Danzhong (CV17), and dual-point sparrow-pecking moxibustion was delivered for 60 min per session. The moxibustion therapy was performed 4 times in the 1st week, 3 times in the 2nd and 3rd weeks respectively, and 2 times in the 4th week, for 12 times totally. The scores of Hamilton depression scale (HAMD), self-rating depression scale (SDS), visual analogue scale (VAS) for drug craving, Hamilton anxiety scale (HAMA), self-rating anxiety scale (SAS), and Pittsburgh sleep quality index (PSQI) were observed before treatment, at the end of the 2nd and 4th weeks of treatment, and 4 weeks after the treatment completion (follow-up) in the two groups. RESULTS: At each time point after treatment, in the observation group, the HAMD, VAS, HAMA and PSQI scores were decreased compared with those before treatment (P<0.01, P<0.001); at the end of the 4th week of treatment and in follow-up, the SDS and SAS scores were decreased compared with those before treatment (P<0.001, P<0.01). Compared before treatment, there were no significant differences in the above scores at each time point after treatment in the control group (P>0.05). In the observation group, at each time point after treatment, the HAMD and VAS scores were lower than those in the control group (P<0.01, P<0.001, P<0.05); at the end of the 4th week of treatment and in follow-up, the SDS and HAMA scores were lower than those in the control group (P<0.05, P<0.001); at the end of the 4th week of treatment, the PSQI score was lower than that in the control group (P<0.01). CONCLUSION Heat-sensitive moxibustion robot effectively improves depression, anxiety and sleep quality, and reduces drug craving in methamphetamine addicts during withdrawal period.
Humans ; Moxibustion/methods* ; Male ; Adult ; Female ; Methamphetamine/adverse effects* ; Depression/therapy* ; Middle Aged ; Robotics ; Young Adult ; Amphetamine-Related Disorders/psychology* ; Acupuncture Points ; Substance Withdrawal Syndrome/psychology*

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

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

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