With the accelerating pace of work and life in modern society, sleep disorders have become an increasingly prevalent issue. Brain-computer interface (BCI), as an emerging technological tool, offers new possibilities for the diagnosis and treatment of sleep disorders.

To analyze and summarize the application of BCI in sleep disorders in recent years and explore its clinical value in the diagnosis and treatment of sleep disorders.

Literature searches were conducted using the search terms “brain-computer interface”, “electroencephalogram”, “sleep”, “sleep disorders”, “sleep monitoring”, and “sleep intervention” both on the PubMed and China National Knowledge Infrastructure (CNKI) database. The search period spanned from January 2015 to August 2025. The initial search yielded 678 documents. After strict screening and manual addition of 2 more, a total of 34 relevant documents were finally included.

BCI technology is revolutionizing the diagnosis and treatment of sleep disorders by leveraging high-precision EEG signal analysis and intelligent algorithms. Multimodal deep learning models enable BCI systems to achieve high accuracy in sleep-stage classification, while closed-loop auditory, visual, and electrical stimulation systems significantly improve sleep quality. However, core challenges persist, including hardware-side signal noise interference, limited algorithmic generalizability, constraints in device portability, and ethical and privacy concerns, alongside the need for clinical standardization.

Future research should focus on breakthroughs in the synergy of “materials-algorithms-hardware”, enhancing the maturity of multimodal closed-loop intervention systems, establishing standardized clinical validation protocols, and developing robust ethical and safety frameworks. These efforts are expected to advance the further development of BCI technology in the field of sleep disorder research.

To compare the functional connections and topological properties of brain networks under subjects' active, imaginary and passive hand clenching tasks based on electroencephalography technology, in order to explore new methods for brain-computer interfaces to analyze movement intentions to assist in hemiplegia rehabilitation.

The study included 15 healthy adult subjects and 19 stroke patients. The subjects collected real-time EEG in three task modes: active movement, motor imagination and passive movement. Functional connection analysis was used to compare the strength of task-state brain network functional connections between stroke groups and healthy controls; graph theory was used to compare changes in brain network topological properties between groups.

Functional connectivity analysis showed significant interactions between the stroke group and healthy controls in the frontal, parietal, and occipital lobes. The sensorimotor network of stroke patients showed higher connection strength than that of healthy subjects. Brain network graph theory analysis showed that the clustering coefficient of the stroke group was significantly lower than that of the healthy control group, the characteristic path length was generally higher than that of the healthy control group, and the small-world coefficient was significantly lower than that of the healthy control group.

The recovery of upper limb function in stroke patients is related to the compensatory adjustment of brain network functional connections, which specifically includes strengthening the connection strength of the sensorimotor network related to the patient's movement sensation and the high-level motor cortex such as the fronto-parietal network. Graph theory analysis shows that the brain after stroke has a lower clustering coefficient and a longer characteristic path length, verifying that the structure and function of the brain network are destroyed after stroke, the global efficiency is significantly reduced, the information transmission efficiency decreases, and a transformation to a random network is observed in the resting state brain network.

To explore the clinical efficacy and brain mechanism of repetitive transcranial magnetic stimulation (rTMS) based on structural preservation in treating upper limb motor dysfunction after stroke.

Motor evoked potential (MEP) elicitation was used as the evaluation index of structural preservation. A total of 60 stroke patients with upper limb motor dysfunction and absent MEP were enrolled. They were randomly divided into the contralateral high-frequency group, contralateral low-frequency group, ipsilateral high-frequency group, and sham stimulation group using the random number table and double-blind method. Before and after the experiment, the upper limb Fugl-Meyer assessment (UL-FMA), functional independence measure (FIM), and functional near-infrared spectroscopy (fNIRS) were performed.

There were no statistically significant differences in general data, pre-treatment UL-FMA scores, FIM scores, or mean oxyhemoglobin (HbO) concentration in the region of interest among the groups (P>0.05). After treatment, the UL-FMA scores of each group were significantly different from those before treatment (P<0.05), and the contralateral high-frequency group showed a statistically significant difference compared with the sham stimulation group (P<0.05). The FIM scores of each group were significantly different from those before treatment (P<0.05), but there was no statistically significant difference among the four groups (P>0.05). Compared with the sham stimulation group, the changes in HbO activation before and after treatment in the contralateral high-frequency group were mainly located in the ipsilateral premotor cortex (PMC), supplementary motor area (SMA), and frontal eye field (FEF), with statistically significant differences (P<0.05).

In severe stroke patients with absent MEP, contralateral high-frequency repetitive transcranial magnetic stimulation (rTMS) yields greater improvements in upper limb motor function (UL-FMA) and induces stronger activation of specific ipsilateral brain regions (PMC, SMA, FEF) compared to sham stimulation. Nevertheless, its efficacy relative to contralateral low-frequency and ipsilateral high-frequency rTMS warrants further validation through larger-scale studies.

To explore the effects and mechanisms of high-frequency repetitive transcranial magnetic stimulation (rTMS) targeting the contralesional primary motor cortex (cM1) or the contralesional dorsal premotor cortex (cPMd) on upper limb motor function in patients with severe stroke, based on the compensation model theory. The study utilized functional near infrared spectroscopy (fNIRS) to analyze the characteristics of brain network reorganization.

This study recruited 23 patients with first-onset stroke within a disease course of 3～12 months and conducted a randomized single-blind controlled experiment. Participants were randomly assigned to the cM1 group, cPMd group, and the control group (sham stimulation group). The cM1 group received stimulation at 5 Hz, 100% resting motor threshold (rMT), with 1 000 pulses per session. The cPMd group received stimulation at 5 Hz, 100% rMT, with 1 000 pulses per session. The treatment was administered once daily, five days per week, for a total of two weeks. Participants underwent Fugl-Meyer assessment of upper extremity function (FMA-UE) and resting-state fNIRS detection before and after the intervention. The regions of interest (ROIs) for fNIRS were located in the bilateral Brodmann areas 4 (BA4) and 6 (BA6), with the resting-state fNIRS focusing on the changes in functional connectivities (FC) between these ROIs.

There were no significant statistical differences in the baseline FMA-UE scores among the three groups (P>0.05). Compared with pre-intervention, the results after two weeks of intervention showed that the FMA-UE scores in the cM1 group and the cPMd group significantly increased (P<0.05). The intergroup comparison revealed that the change in FMA-UE scores in the cM1 group was significantly different from that in the control group (P=0.007). For the resting-state fNIRS results, the FC between the left BA4 and right BA4 (LBA4-RBA4) in the cM1 group was significantly greater than that in the cPMd group (P=0.046), and the FC between LBA4 and RBA4 in the control group was significantly greater than that in the cPMd group (P=0.011). No other significant differences were found.

High-frequency rTMS targeting cM1 and cPMd based on the compensation model theory can improve upper limb motor function in patients with upper limb motor dysfunction after severe stroke, with clinical feasibility and safety. The rTMS treatment targeting the cM1 area significantly enhances the interhemispheric functional connectivity of the motor cortex, thereby improving upper limb motor function in patients with severe stroke. Moreover, cM1 appears to be more advantageous than cPMd in promoting functional recovery in patients with upper limb motor dysfunction after severe stroke.

To evaluate the performance of 450 ventilators in use in Zhejiang Province by systematically assessing the pass rates of core parameters across different brands and analyzing the correlation between service life and performance, thereby providing evidence for precise quality control and scientific maintenance.

In accordance with GB 9706.212—2020 and JJF 1234—2018, five key parameters (tidal volume, mandatory ventilation frequency, FiO₂, inspiratory pressure level, and PEEP) were tested using a Fluke VT650 gas flow analyzer. Descriptive statistics and Spearman rank correlation analysis were employed for systematic comparison and correlation analysis from the dimensions of brand type and service life.

The overall pass rate of the 450 ventilators was 58.67% (264/450). Significant disparities were observed in the pass rates of core parameters among brands: Imported Brand 2 had the highest overall pass rate (70.48%), while Domestic Brand 2 had the lowest (0.00%). Tidal volume exhibited the most notable variation in pass rates among brands (0%～90.75%), identified as the primary weakness of domestic devices. Correlation analysis between service life and performance revealed that Imported Brand 2 maintained stable performance with no significant correlation to service life (ρ=-0.094, P=0.157). In contrast, Imported Brand 1 (ρ=-0.382, P=0.001) and Imported Brand 3 (ρ=-0.446, P<0.001) showed significant negative correlations, while Domestic Brand 1 also demonstrated a weak negative correlation (ρ=-0.215, P=0.035).

The current overall performance of ventilators requires improvement, with tidal volume accuracy being a common technical bottleneck for domestic devices. Furthermore, performance degradation patterns over time vary significantly by brand. It is recommended to establish a differentiated quality control system focusing on tidal volume, incorporating service life and brand-specific characteristics, to enhance the clinical safety and whole-life-cycle management of ventilators.

To establish a comprehensive quality management system based on ISO 15189, performing calibration and post-calibration verification for the SYSMEX XN-3000 automated hematology analyzer system, ensuring compliance with routine laboratory testing requirements and ISO 15189 accreditation.

Following established calibration and post-calibration verification protocols for the SYSMEX XN-3000 automated hematology analyzer—based on WS/T 347—2024 Guidelines for Calibration of Blood Cell Analyzers, WS/T 406—2024 Quality Standards for Common Clinical Hematology Testing Items, CNAS-CL02: 2023 Accreditation Criteria for Quality and Competence of Medical Laboratories, CNAS-CL02-A001: 2023 Application Requirements for the Accreditation of Medical Laboratories and SYSMEX XN-3000 Instrument Operation Manua, the SYSMEX XN-3000 automated hematology analyzer was calibrated. Before calibration, it's necessary to confirm that the instrument's working environment and performance requirements comply with standards. Post-calibration verification was conducted for eight key hematological parameters: WBC, RBC, Hb, Hct, Plt, MCV, MCH, and MCHC. Verification methods included quality control testing and evaluation across different sampling modes.

The SYSMEX XN-3000 automated hematology analyzer passed calibration, and post-calibration validation was successful, confirming its suitability for clinical testing within the defined calibration interval.

The SYSMEX XN-3000 automated hematology analyzer met calibration standards and post-calibration verification requirements, fulfilling the demands of clinical hematology laboratories and satisfying the instrument calibration requirements for ISO 15189 accreditation.

To carry out Quality Control Circle (QCC) activities aiming to improve the standardized utilization rate of intravenous indwelling needles in Phase I clinical trials.

A total of 120 subjects enrolled in the trial from February 2 to 9, 2023, were assigned to the control group, with 144 blood sample collections performed. Separately, 134 subjects enrolled in the trial from August to October 2023 were assigned to the observation group, with 160 blood sample collections performed. QCC management tools (e.g., Pareto charts, fishbone diagrams) were used for root cause analysis to identify the causes of non-standard practices in the use of indwelling needles, and corresponding improvement measures were formulated and implemented. The standardized utilization rate of indwelling needles before and after the QCC activities was compared, and the application effect of the QCC activities was analyzed.

The standardized utilization rate of indwelling needles increased from 43.75% before the activities to 75.63% (χ²=32.23, P<0.05), with a target achievement rate of 105.49% and an improvement rate of 72.87%. In terms of intangible effects, the circle members' abilities in QCC technique application, teamwork, professional knowledge mastery, communication and coordination, sense of responsibility, and problem-solving capabilities were significantly improved.

Conducting QCC activities improved the standardized utilization rate of indwelling needles in Phase I clinical trials, ensured blood collection safety, enhanced nursing quality, and maintained a balance between subject protection and compliance with the research protocol.

To investigate the consistency between digital stethoscope technology and manual stethoscope in chronic obstructive pulmonary disease (COPD) patient monitoring scenarios.

This prospective diagnostic accuracy study employed non-random continuous sampling, collecting 1,953 valid lung sound recordings from COPD patients at the Department of Respiratory and Critical Care Medicine, Xinjiang Production and Construction Corps Hospital between November 2024 and May 2025. A multidimensional respiratory sound assessment scale was developed with standardized interpretation criteria. Clinical physicians evaluated digital lung sound characteristics while comparing artificial intelligence-powered digital auscultation results with physician assessments for consistency. Taking the clinical physician's listening results as the gold standard, the following indexes were calculated through the confusion matrix: accuracy, recall rate, false positive rate and precision, so as to evaluate the diagnostic consistency between digital stethoscope and manual stethoscope. This evaluation system assessed diagnostic consistency between digital stethoscope and manual stethoscope.

The accuracies of digital stethoscope and AI analysis in identifying normal lung sounds, coarse breath sounds, rales, dry rales, and wet rales were 99.39%, 99.59%, 99.18%, 99.00%, and 99.59% respectively; recall rates were 99.44%, 98.31%, 99.49%, 99.10%, and 98.71%; false positive rates were 0.760%, 0.125%, 1.025%, 1.059%, and 0.000%; precision rates were 99.11%, 99.43%, 98.48%, 96.49%, and 100.00%. Consistency tests showed that the Kappa values of digital stethoscope and AI analysis and clinicians' stethoscope judgment of normal lung sounds, coarse breath sounds, rales, dry rales and wet rales were 0.988, 0.984, 0.983, 0.972 and 0.992, respectively.

The digital stethoscope results showed a high degree of consistency with the manual stethoscope results in patients with COPD. Digital auscultation technology can alleviate the pressure on medical resources and reduce human errors through standardized analysis, and it is a key direction for the development of smart healthcare.

To analyze the detection effect of multislieces helieal CT (MSCT) on the imaging features of low lumbar disc herniation, including disc deformity, spinal cord degeneration, and dural sac compression.

A total of 66 patients with low lumbar disc herniation confirmed by pathological analysis in our hospital from March 2022 to March 2024 were selected as the research subjects. All patients underwent X-ray and MSCT examinations to analyze the detection situation and imaging features.

The detection rate of MSCT (98.48%) was higher than that of X-ray (87.88%), with a statistically significant difference (P<0.05). In the imaging feature examination, the detection rates of MSCT for disc deformity (96.88%), spinal cord degeneration (93.02%), nerve root compression (92.11%), dural sac compression (97.78%), calcification (98.08%), and gas accumulation (97.83%) were higher than those of X-ray (78.13%, 4.65%, 2.63%, 64.44%, 67.31%, 45.65%), with statistically significant differences (P<0.05). In the prediction of different degrees of degenerative changes in low lumbar disc herniation by MSCT imaging parameters, the sagittal flexion angles of the moderate and severe groups were (162.39±5.51)° and (171.83±8.78)°, respectively, which were higher than that of the mild group [(153.02±5.03)°]. The sagittal diameters of the dural sac of the moderate and severe groups were (10.97±0.84) and (7.52±0.52) mm, respectively, which were lower than that of the mild group [(15.83±1.06) mm], and the endplate flexion depths of the moderate and severe groups were (1.96±0.11) and (1.42±0.06) mm, respectively, which were lower than that of the mild group [(2.49±0.14) mm], with statistically significant differences (P<0.05).

MSCT technology can provide more accurate imaging features in the diagnosis of low lumbar disc herniation and can provide relevant reference basis for physicians to assess the degree of the disease.

Applying internet of things (IoT) technology in the construction of hospital medical equipment management information system, and constructing and applying an magnetic resonance imaging (MRI) examination appointment scheduling management system in a real hospital environment, in order to achieve a scientific MRI examination appointment scheduling method, comprehensively improve the efficiency of hospital medical equipment examination, shorten patient waiting time, and optimize resource allocation.

The system optimizes and integrates the existing medical equipment resources by using IoT technology, and combines the hospital's demands. It adopts a four-layer hierarchical architecture from bottom to top: data collection layer - data integration layer - application service layer - application business layer, to build an MRI examination appointment and scheduling management system. This system realizes core functions such as equipment usage efficiency analysis, patient appointment analysis, and scheduling record analysis. By comparing four indicators - the average daily working hours per MRI device, the average daily on-time hours per MRI device, the average daily number of patients served per MRI device, and the average interval time between examinations - before and after the system's launch, the application effect of the system is analyzed.

After the application of the system, the average daily number of patients served and average daily working hours per MRI device significantly increased, and the average interval time between examinations significantly decreased, with all differences being statistically significant (P<0.05). However, the difference in the average daily on-time hours per device was not statistically significant (P>0.05), indicating that the system has a promoting effect on improving the utilization efficiency of MRI devices.

After the system was applied, the service volume of MRI equipment were significantly improved, the average interval time between examinations was effectively shortened, and the utilization rate of hospital MRI equipment was significantly improved, This management strategy and optimization method not only provide scientific data support for hospital managers, but also provide effective and feasible management tools to enhance the social and economic benefits of hospitals, with broad application prospects and promotion value.