Latest ArticlesProposes the construction of an intelligent scheduling system for medical technology, utilizing a data integration platform to optimize queuing order. The system aims to shorten patients' waiting times and enhance the efficiency of tests and examinations, ultimately improving the quality of medical services and the experience for patients.
This study utilizes Sybase PowerBuilder development tools in conjunction with MS SQL Server as the backend database. It adopts a Client/Server (C/S) architecture mode and is based on a data integration platform. Following the Web Service interface mode and adhering to XML standards, we aim to construct an intelligent scheduling system for medical technology, including infrastructure layer, data resource layer, platform application layer, data interaction layer, access control layer, application system layer and terminal access layer. This intelligent scheduling system is designed to fulfill business requirements while maintaining principles of stability, efficiency, convenience, and intelligence, and is seamlessly integrated with the hospital's internal data integration platform.
The system mainly consists of five functional: the front desk registration module, the examination room call module, the waiting area terminal module, the intelligent rule setting module, and the data query and statistics module. The practical application of the system has a significant impact, evidenced by improved registration times and user satisfaction compared to the period before the system's implementation. Statistically significant differences were observed (t=103.678, P<0.001; χ2=7.307, P<0.05), indicating that the system effectively reduces patient waiting times and improves physicians' work efficiency.
The medical intelligent scheduling system developed in this study enhances work efficiency and patient satisfaction by optimizing the processes of testing and examination. Furthermore, it offers a novel strategy for the development of smart hospitals.
Laser-induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique that generates plasma by focusing pulsed laser on a sample and then analyzes the emitted light spectrum to obtain the composition and content of the substance. Due to its advantages such as in-situ detection, low sample pretreatment requirements, and simultaneous detection of multiple elements, it has shown great potential in the biomedical field. Principal component analysis (PCA), as a classic dimensionality reduction technique, retains the main features of LIBS spectral data while eliminating redundant variables in the spectral data, significantly improving the classification efficiency of the model. This paper reviews the research status and latest progress of LIBS technology combined with PCA in biomedical applications in recent years. It focuses on summarizing the application of such technologies and methods in disease diagnosis, drug analysis, forensic science and other related fields. It provides suggestions for future development from the perspectives of algorithm optimization, development of portable devices, and promotion of multi-technology integration, providing a reference for achieving precise medical treatment and real-time monitoring, and offering support for medical research and clinical applications.
In the current development of acupuncture and moxibustion, there are problems such as traditional teaching methods, low efficiency, difficult quantification of technology and long training cycle of talents. This paper discusses the application value of virtual reality, augmented reality, mixed reality and biomechanical cross technology in acupuncture and moxibustion teaching and clinical practice, focusing on the analysis of acupuncture and moxibustion interactive power and application characteristic technology.
Selecting the relevant researches at home and abroad in recent ten years, the force feedback, characteristic technique and function realization of acupuncture auxiliary system were summarized and distinguished.
Virtual reality, augmented reality and mixed reality were closely combined with biomechanical feedback when applied to acupuncture assistance, and their respective technologies were focused on realizing functions such as acupuncture knowledge assisted memory, acupuncture point positioning, acupuncture training, etc., but there were some problems such as the limitation of edge computing power, insufficient precision of force feedback model, and insufficient functional integration.
Continuous optimization should be carried out in the direction of force feedback refinement, algorithm lightweight and multi-scene integration, and intelligent transformation of acupuncture and moxibustion teaching and clinical practice should be promoted by combining with large language model.
Physical rehabilitation training plays a crucial role in the recovery of hand function for patients after stroke. Currently, the hand rehabilitation training for stroke patients is mainly carried out by rehabilitation physicians. Hand rehabilitation robots can effectively alleviate the shortage of rehabilitation medical resources and reduce the workload of rehabilitation physicians. Their rehabilitation effects have been confirmed in clinical trials, but there is still room for improvement in terms of reliability and intelligence. This paper starts with the physiological structure of the human hand and the movement characteristics of the hand after stroke to introduce the rehabilitation needs of stroke patients. Then, it classifies the existing hand rehabilitation robots based on their structural forms and driving methods, elaborates on their application scenarios and features in detail, and summarizes typical control strategies and the evaluation standards for hand motor ability after stroke. Finally, it analyzes the existing problems of hand rehabilitation robots and looks forward to their development trends.
As a novel human-computer interaction paradigm that breaks through traditional neural pathways, the brain-computer interface (BCI) enables direct control of external devices by decoding central nervous system activities, demonstrating significant application value in the fields of neurorehabilitation and functional compensation. Functional near-infrared spectroscopy (fNIRS) detects changes in blood oxygen concentration in activated brain regions in real time, providing objective indicators of functional changes in the cerebral cortex. Therefore, the fNIRS-BCI technology, with its non-invasive nature, high spatiotemporal resolution, and strong resistance to motion interference, overcomes the limitations of traditional electroencephalogram (EEG) being easily affected by electromyographic artifacts, and has become a new monitoring tool in the field of neurorehabilitation. With algorithmic innovations and hardware iterations, its applications will expand from medical scenarios to education, entertainment, industry, and other fields. This article systematically expounds the current application status and challenges of the fNIRS-BCI technology system in areas such as motor rehabilitation, cognitive intervention, and communication for the severely ill, aiming to provide a theoretical framework for the clinical transformation of fNIRS-BCI technology in neurorehabilitation and suggest new development directions for personalized neural regulation and brain-peripheral coordinated rehabilitation.
The aim of this study is to provide technical support and reference basis for the research on the mechanism of cerebral small vessel hemorrhage and treatment methods through small animal Magnetic Resonance Imaging (MRI) sequences. This will facilitate in - depth exploration of the nature of the disease, optimization of treatment strategies, and promotion of the development of new treatment methods.
In this study, 5 C57 mice overexpressing the mutant sites of PIK3CA and MAP3K3 (p.I441M) were taken as the research objects. Imaging was carried out using different sequences of 7.0T small - animal nuclear magnetic resonance, such as T1WI, T2WI, SWI, DTI, and ASL. Parameter setting and image acquisition were performed, and the scanning results were statistically analyzed in terms of indicators such as the number of lesions, lesion area, and signal - to - noise ratio.
SWI shows excellent performance in the detection of the number, size, and signal - to - noise ratio of lesions (P<0.05). T2WI shows lesions more clearly than T1WI (P<0.05). DTI and ASL provide micro - structure and blood perfusion information respectively.
The comprehensive application of multiple sequences is helpful for a comprehensive assessment of pathological characteristics
To explore the influencing factors and action mechanisms of the tensile properties of rubber gloves, and provide a scientific basis for their design, production, and use.
Rubber glove samples from the same batch produced in June 2023 within the expiration date were selected. After cutting and conditioning, defective products were removed. According to the ISO 37 standard, type 2 dumbbell - shaped specimens were used. Multiple devices were employed, and methods such as contact extensometers and manual non - contact measurement were adopted. Three inspectors conducted independent tests, and one inspector carried out equipment comparison. Additionally, loose - clamping and pre - tension - clamping tests were performed with reference to relevant standards. Statistical analysis was conducted using
The initial test length error will lead to a deviation in elongation at break, such as a 2mm error resulting in an 11% deviation. The results of the holding method were higher than those of the manual method (P<0.05). The deviation of test data of different equipment was less than 5% (P>0.05). The 0.15N pretension can reduce the error, and the elongation at break is low when the loose clamping is 0.5N.
Factors such as the initial test length, measurement methods, equipment, and pre - tension significantly affect the tensile properties of rubber gloves. These factors need to be strictly controlled during production and inspection.
Fall risk assessment is of significant importance in the elderly population as falls constitute a primary cause of injuries and fatalities among the elderly. This paper comprehensively outlines the commonly used algorithms and classification features in fall risk assessment tools constructed using machine learning techniques. By comparing the performance of these models on real-world datasets, it delves into the strengths and weaknesses of various algorithms and their applicable scenarios. The article provides detailed insights into the data prepossessing steps and model construction processes commonly employed in each model, offering a comprehensive comparison. In conclusion, the paper summarizes the current shortcomings in research and anticipates potential directions for future developments in this field.
To analyze the impact of the improved defect management mode applied by the disinfection and supply center on the occurrence of wet packets after pressure steam sterilization.
A retrospective analysis was performed on the sterilization conditions of 155,272 sterilization kits performed by pressure steam sterilization in the Wuxi No.2 Chinese Medicine Hospital sterilization supply center from January 2024 to December 2024. The sterilization conditions were divided into control group (from January 2024 to June 2024, n=77636) and observation group (from July 2024 to December 2024) before and after the implementation of the defect management improvement mode. n=77636), the control group implemented the conventional management mode, and the observation group implemented the defect management improvement mode. The pass rate of each process of pressure steam sterilization, the quality of wet packet management and the occurrence of wet packet were compared between the two groups.
The pass rate of pressure steam sterilization processes such as packaging, loading, sterilization and unloading in the observation group was higher than that in the control group, and the difference was statistically significant (P<0.05). The scores and total scores of the four dimensions of exterminator packaging, loading and unloading management, sterilization management and wet bag record management in the observation group were higher than those in the control group, with statistical significance (P<0.05). The incidence of wet bag in observation group was lower than that in control group, and the difference was statistically significant (P<0.05).
The application of defect management improvement mode in central sterile supply department can improve the qualified rate of pressure steam sterilization and the quality of wet package management, so as to effectively reduce the occurrence of wet package.
To explore the effect of lower limb exoskeleton robot combined with wireless neuromuscular electrical stimulation training on the balance ability of stroke patients. Method A retrospective analysis was conducted on the case data of 50 patients with hemiplegia after stroke admitted to Beijing Huasheng Rehabilitation Hospital from October 2023 to August 2024. The patients were divided into the observation group and the control group by the order of admission, with 25 cases in each group. The control group received conventional rehabilitation combined with lower limb exoskeleton robot training, while the observation group received additional wireless neuromuscular electrical stimulation training for 4 weeks on the basis of the control group. The National Institute of Health Stroke Scale (NIHSS), complication occurrence, Fugl-Meyer Assessment (FMA) of motor balance function, and Stroke-Specific Quality of Life Scale (SS-QOL) were compared between the two groups.
After the intervention, the NIHSS score of the observation group was significantly lower than that of the control group, with a statistically significant difference (P<0.05). The total complication rate of the observation group was lower than that of the control group, with a statistically significant difference (P<0.05). After the intervention, the Fugl-Meyer score of the observation group was higher than that of the control group, with a statistically significant difference (P<0.05). After the intervention, the SS-QOL score of the observation group was higher than that of the control group, with a statistically significant difference (P<0.05).
The combination of lower limb exoskeleton robots and radio stimulation training is a promising rehabilitation method for stroke patients, which can improve limb dysfunction, enhance balance and daily living abilities, reduce dependence on others in daily life, and improve their quality of life in post-stroke hemiplegic patients.
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