Real-time warning non-magnetic monitoring system for child sedation state in nuclear magnetic environment

Abstract

The application discloses a child sedation state nuclear magnetic environment real-time early warning non-magnetic monitoring system, relates to the technical field of medical vital sign monitoring, and comprises a full-system non-magnetic bearing module, a multi-parameter non-magnetic sensing acquisition module, a signal isolation transmission module, a child sedation state multi-dimensional analysis module, a real-time hierarchical early warning module, a nuclear magnetic compatible synchronous control module, a monitoring data storage and visualization module and a terminal interactive control module. The multi-parameter non-magnetic sensing acquisition module synchronously acquires multi-dimensional physiological and behavioral data of a child in a sedation state, the signal isolation transmission module realizes full-optical-fiber isolated signal transmission, and the modules cooperatively complete sedation state analysis, hierarchical early warning, nuclear magnetic scanning synchronous control, monitoring data management and terminal interaction. The application realizes full-process continuous monitoring of the child sedation state in a nuclear magnetic strong magnetic field environment, the full-system non-magnetic design is adapted to the nuclear magnetic scanning requirement, and the monitoring safety and precision of the pediatric nuclear magnetic sedation examination are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of medical vital sign monitoring technology, and in particular to a real-time early warning non-magnetic monitoring system for children in sedated MRI environments. Background Technology

[0002] Children, especially young children, often cannot cooperate with MRI examinations independently, so sedation is frequently used in clinical practice to ensure the smooth progress of the examination. Under sedation, children's respiratory and circulatory vital signs are at risk of spontaneous fluctuations. Young children have a weaker ability to metabolize sedative drugs, making them prone to adverse events such as respiratory depression and abnormal heart rate, requiring continuous vital sign monitoring throughout the procedure. The MRI environment contains strong static magnetic fields, gradient magnetic fields, and radiofrequency pulses. Conventional metal monitoring equipment cannot enter the scanning chamber, easily causing magnetic attraction risks and interfering with MRI imaging quality, leading to image artifacts and making real-time monitoring during the scan impossible. Existing monitoring equipment adapted to the MRI environment is mostly designed for adults and does not fully consider the physiological development characteristics of children. The size and fit of the sensor unit are not suitable for the body surface characteristics of young children, easily leading to signal loss and insufficient accuracy.

[0003] Current MRI monitoring equipment mostly only collects basic vital signs and lacks the ability to analyze children's sedation status in a multidimensional way. It relies solely on a single EEG parameter to assess sedation depth without considering the child's respiratory rhythm, body movement, and other multidimensional characteristics, making it prone to biased assessments of sedation depth and failing to promptly identify excessive sedation or signs of impending awakening. The signal transmission of existing equipment often suffers from insufficient electrical isolation, making it susceptible to interference from the strong magnetic field of MRI, resulting in artifacts in the acquired signals and failing to accurately reflect the child's true physiological state. Furthermore, the equipment's own electromagnetic signals are prone to leakage, affecting the clarity of MRI images. The early warning mechanisms of existing equipment mostly use general group thresholds, failing to consider individual differences in children, leading to false alarms or missed alarms, and failing to achieve tiered early warning and risk prediction. Additionally, the lack of synchronous control with the MRI scan sequence means that radio frequency pulses during the scan can severely interfere with signal acquisition, preventing the timely detection of critical abnormal events.

[0004] During pediatric MRI sedation examinations in clinical practice, medical staff often need to enter the room to check on the child's condition between scans, making continuous real-time monitoring throughout the entire scan impossible. This can easily lead to missing the optimal time to handle abnormal events, posing serious medical safety risks. Existing MRI monitoring equipment has significant technical shortcomings in terms of non-magnetic design, child compatibility, accurate analysis of sedation status, MRI-compatible synchronous control, and graded early warning systems. It cannot simultaneously meet the requirements of non-magnetic compatibility with the MRI environment, the physiological compatibility requirements of children, and the accuracy and safety requirements of sedation monitoring. The continuously expanding scale of clinical pediatric MRI examinations places higher demands on the safety, accuracy, and continuity of monitoring during sedation examinations. Developing an MRI monitoring system that is compatible with children's sedation status, non-magnetic compatible throughout the entire process, and has multi-dimensional sedation analysis and real-time graded early warning capabilities has become an urgent need in the field of clinical pediatric MRI examinations. Summary of the Invention

[0005] The present invention proposes a real-time early warning non-magnetic monitoring system for children in a sedated state using MRI, in order to solve the problems mentioned in the prior art.

[0006] To achieve the above objectives, the present invention employs the following technical solution: a real-time early warning and non-magnetic monitoring system for MRI environments in sedation states of children, comprising: The entire system is a non-magnetic support module, which is installed on the MRI scanning bed to support all components of the system placed inside the MRI scanning cavity. A multi-parameter non-magnetic sensing acquisition module includes a non-invasive fiber optic sensing unit, a non-magnetic electroencephalogram (EEG) acquisition unit, and a body movement monitoring unit. The non-invasive fiber optic sensing unit includes at least one fiber optic heart rate sensor, one fiber optic respiratory rate sensor, one fiber optic blood oxygen sensor, and one fiber optic body temperature sensor. The non-magnetic EEG acquisition unit includes a flexible electrode array, and the body movement monitoring unit includes an acceleration sensing element. The signal isolation transmission module includes an all-fiber transmission link and a multi-level electrical isolation structure. The first end of the all-fiber transmission link is located in the NMR scanning room and is connected to the signal output end of the multi-parameter non-magnetic sensing acquisition module through an optical fiber coupler. The second end of the all-fiber transmission link extends through the waveguide or filter board of the NMR scanning room to the external operating room and is connected to the input end of the multi-level electrical isolation structure. The output end of the multi-level electrical isolation structure is connected to the subsequent signal processing circuit. The all-fiber transmission link is connected to the NMR scanning cavity without any metal conductive medium throughout. The terminal interaction control module includes an operating terminal deployed in the safe area of ​​the MRI operating room. The operating terminal runs monitoring and management software, which includes a monitoring parameter threshold setting interface, an early warning level adjustment interface, a sensor calibration interface, and a data query and export interface.

[0007] Furthermore, it also includes: The multi-dimensional analysis module for pediatric sedation includes a signal preprocessing unit, a feature extraction unit, and a fusion analysis unit. The signal preprocessing unit includes a digital filter bank for filtering out NMR gradient fields and radio frequency pulse interference. The feature extraction unit extracts the bispectral index from the preprocessed EEG signal, extracts heart rate variability parameters and respiratory rate variability parameters from physiological signs, and extracts body movement amplitude parameters from body movement signals. The fusion analysis unit performs weighted fusion calculations on the bispectral index, respiratory rate variability parameters, heart rate variability parameters, and body movement amplitude parameters based on preset age-group weighting coefficients, and outputs a quantitative index of pediatric sedation depth and sedation status classification results. The real-time graded early warning module includes a threshold storage unit, a comparison and judgment unit, and an early warning output unit. The threshold storage unit stores the preset vital sign safety thresholds and sedation state grading thresholds for different age groups. The comparison and judgment unit compares the sedation state grading results and physiological sign data output by the multi-dimensional analysis module of children's sedation state with the corresponding thresholds one by one. The early warning output unit generates an early warning signal of the corresponding level based on the comparison results and drives the non-magnetic sound and light alarm terminal and the operation room display terminal to synchronously display the early warning information. The MRI-compatible synchronous control module includes an interface unit for communicating with the MRI scanning equipment and an acquisition timing control unit. The interface unit receives scan sequence trigger node signals and operating status signals sent by the MRI scanning equipment. The acquisition timing control unit adjusts the sampling clock of each sensing unit in the multi-parameter non-magnetic sensing acquisition module according to the trigger node signals and establishes an association index between the monitoring data and the MRI image data within the same time window.

[0008] Furthermore, it also includes: The monitoring data storage and visualization module includes a data storage unit and a visualization processing unit. The data storage unit stores the full-process monitoring data, sedation analysis results and early warning event data in layers according to timestamps. The visualization processing unit retrieves multi-parameter data for a specified period from the data storage unit and generates multi-parameter trend change curves, which are then rendered and output on the operation terminal display interface. It also provides a historical data backtracking and retrieval entry. A child-specific non-magnetic sensor fixation module includes a head strap, a body sensor fixation patch, and an anti-slip strap. The surfaces of the head strap and the body sensor fixation patch are provided with anti-slip microstructure textures. The head strap, the body sensor fixation patch, and the anti-slip strap are respectively set with corresponding size specifications for the age groups of newborns, infants, and preschool children. The outer surface of the head strap and the body sensor fixation patch is provided with NMR-compatible non-magnetic positioning marks. The outer layer of the anti-slip strap is provided with an anti-scratch covering layer. The NMR environment full-domain electromagnetic shielding module comprises a sensor end shielding layer, a transmission link shielding layer, and a terminal shielding cavity. The sensor end shielding layer is a nanoscale non-magnetic shielding coating applied to the outer surface of each sensor unit of the multi-parameter non-magnetic sensing acquisition module. The transmission link shielding layer is a spiral-shaped all-dielectric shielding layer wrapped around the outer layer of the all-fiber transmission link. The terminal shielding cavity is a double-layer non-metallic shielding cavity located in an external operating room. A dedicated grounding cable connecting to the equipotential grounding system of the NMR room is provided between the inner and outer layers of the double-layer non-metallic shielding cavity. The nanoscale non-magnetic shielding coating of the sensor end shielding layer contains an interference suppression conductive mesh for the frequency range of the NMR gradient field. The transmission link shielding layer contains a band-stop filter structure for the NMR radio frequency operating frequency band.

[0009] Furthermore, the multi-dimensional analysis module for children's sedation states includes a built-in quantitative assessment unit for the depth of children's sedation, calculated using the following formula: ,in A quantitative index for the depth of sedation in children. The weighting coefficient of the bispectral index of brainwaves. This is the weighting coefficient for respiratory rate variability. This is the weighting coefficient for heart rate variability. This is the weighting coefficient for the amplitude of body movement, and + + + =1, Bispectral index (BPI) of brainwaves. For respiratory rate variability parameters, For heart rate variability parameters, This refers to the amplitude parameter of body motion.

[0010] Furthermore, the real-time graded early warning module also includes an early warning event tracing unit. The early warning event tracing unit includes a data latch and a standardized report generator when an early warning is triggered. When any early warning level is triggered, the data latch automatically latches multi-parameter raw data, MRI scan sequence data, and sedation administration data for a first preset duration before and after the early warning trigger time. The standardized report generator reads the data latched by the data latch and generates a standardized early warning event report according to the report template. The early warning event report includes fields for early warning trigger time, trigger reason, parameter change trend curve, and sedation status grading result. The standardized report generator also has a pre-stored clinical treatment standard template library indexed by early warning type. It matches the corresponding treatment suggestion template according to the current early warning type and embeds it into the standardized early warning event report. The data storage unit includes a warning event classification and archiving subunit. The warning event classification and archiving subunit classifies and stores warning event reports according to risk level and anomaly type, and is equipped with a desensitization processing interface and a compliance export interface.

[0011] Furthermore, the multi-parameter non-magnetic sensor acquisition module also includes a sleep apnea monitoring unit. This unit comprises a first fiber optic respiratory sensor and a second fiber optic respiratory sensor. The first fiber optic respiratory sensor is attached to the child's chest cavity to collect chest respiratory motion signals, and the second fiber optic respiratory sensor is attached to the child's abdominal cavity to collect abdominal respiratory motion signals. The sleep apnea monitoring unit also includes a dual-channel signal fusion analysis subunit. This subunit receives the two respiratory motion signals output by the first and second fiber optic respiratory sensors, distinguishes between central sleep apnea events and obstructive sleep apnea events by comparing the phase and amplitude differences between chest and abdominal respiratory motions, and simultaneously receives blood oxygen saturation signals. Based on the rate and duration of blood oxygen saturation decline, it classifies and determines abnormal respiratory events. The analysis result signal output of the sleep apnea monitoring unit is connected to the fusion analysis unit of the multi-dimensional analysis module for the child's sedation state.

[0012] Furthermore, the real-time graded early warning module has a built-in dynamic risk assessment unit that can calculate the abnormal risk level based on the real-time changing trends of children's physiological parameters. The calculation formula is as follows: ,in The risk level of abnormal physiological parameters. The number of physiological parameters involved in the evaluation. For the first Real-time monitoring values ​​of several physiological parameters For the first Individual baseline values ​​for several physiological parameters For the first The safe range of fluctuation for several physiological parameters For the first Risk weighting coefficients for physiological parameters.

[0013] Furthermore, the NMR-compatible synchronization control module also includes a scan gap acquisition optimization unit, which includes a sequence type identification subunit, a sampling parameter adjustment subunit, and an adaptive filtering subunit; The sequence type identification subunit pre-stores radio frequency pulse timing feature templates corresponding to three sequence types: conventional MRI scan, enhanced scan, and functional imaging. By matching the scan sequence trigger node signal received by the interface unit with each feature template, the current sequence type identification result is output. The sampling parameter adjustment subunit retrieves the corresponding sampling frequency adjustment curve from the preset acquisition timing optimization strategy table according to the sequence type identification result. During the high interference period of the scanning sequence, the sampling frequency of the multi-parameter non-magnetic sensor acquisition module is lowered to a first frequency value, and during the low interference period between scanning sequences, the sampling frequency is raised to a second frequency value, where the second frequency value is higher than the first frequency value. The adaptive filtering subunit retrieves the corresponding digital filter coefficient combination from the preset filtering parameter table based on the interference spectrum characteristics corresponding to the sequence type identification result, and loads it into the digital filter bank of the signal preprocessing unit.

[0014] Furthermore, the monitoring data storage and visualization module also includes a multi-terminal synchronous display unit. The multi-terminal synchronous display unit includes a first push channel, a second push channel, and a third push channel. The first push channel connects to a fixed operating terminal deployed in the MRI operating room and pushes full-parameter, full-process monitoring data and complete sedation status analysis results to it. The second push channel connects to the handheld mobile terminals of medical staff through the hospital's internal wireless network and pushes core vital signs values ​​and early warning information summaries to them. The third push channel connects to the nurse station monitoring terminal through the hospital's internal LAN and pushes a summary list of monitoring status for multiple beds to it. The multi-terminal synchronous display unit also includes a video access subunit. The video access subunit connects to the video stream of the non-magnetic monitoring camera installed in the nuclear magnetic equipment room through a video signal line, and renders the video image and monitoring data curve synchronously in different areas on the same terminal display interface. The multi-terminal synchronous display unit also includes a hierarchical push control subunit. The hierarchical push control subunit configures a push strategy according to the warning level: low-level warnings are only pushed to the first push channel, medium-level warnings are pushed to both the first and second push channels, and high-level warnings are pushed to all three push channels and trigger audio and visual prompts on each terminal.

[0015] Furthermore, it also includes an individual reference adaptive calibration module, which comprises a three-stage reference acquisition unit, an individualized correction unit, and a reference dynamic update unit; The three-stage baseline acquisition unit acquires physiological data of the child's resting state for a second preset duration in the pre-sedation induction stage, the post-sedation induction stage, and the pre-scanning stage, respectively, and generates initial baseline values ​​corresponding to each of the three stages. The individualized correction unit receives the input individualized information of the child's age, gender, weight, type of underlying disease, type and dosage of sedative drug, corrects each initial baseline value according to the preset individualized correction coefficient table, and outputs the individual baseline value. During the scanning process, when the child is detected to be in a stable sedated state and without any abnormal events, the benchmark dynamic update unit re-collects physiological data for a third preset duration at preset time intervals. The statistical mean of the newly collected data is weighted and averaged with the current individual benchmark value according to preset weights to obtain the updated individual benchmark value, which replaces the corresponding general group threshold in the threshold storage unit of the real-time graded early warning module. The three-stage benchmark acquisition unit and benchmark dynamic update unit both contain an abnormal data identification and removal subunit. The abnormal data identification and removal subunit filters the acquired physiological data according to a preset reasonable value range and signal mutation threshold, removes data segments that exceed the reasonable value range or whose signal jump amplitude exceeds the signal mutation threshold, and re-acquires and completes the removed data segments. The individual benchmark adaptive calibration module also includes a calibration report generation unit, which automatically generates a standardized calibration report after calibration is completed. The standardized calibration report is stored in the full-process monitoring file of the data storage unit.

[0016] Compared with existing technologies, the beneficial effects of this invention are: This invention employs a completely non-magnetic system design, enabling continuous monitoring of children in a sedated state within a strong MRI magnetic field environment. It can simultaneously collect multi-dimensional physiological and behavioral data, adapting to the physiological development characteristics of children. The sensing unit features a flexible, conformal design, ensuring non-invasive and non-stimulating data acquisition, and is suitable for monitoring children of all ages. Signal transmission utilizes a fully isolated fiber optic link, effectively shielding against electromagnetic interference from the MRI environment while minimizing adverse effects on MRI imaging quality, achieving synchronous compatibility between the monitoring process and the MRI scan.

[0017] This invention achieves accurate quantitative assessment of sedation depth in children through multi-dimensional feature fusion analysis. By fully combining multi-dimensional features of EEG signals, physiological signs, and body movement behavior, it can improve the accuracy of sedation state classification, reduce the result bias caused by single parameter assessment, and simultaneously accurately identify adverse events such as respiratory abnormalities and abnormal body movement, providing comprehensive data support for the safety of sedation examinations in children.

[0018] This invention employs a tiered early warning and dynamic risk assessment mechanism, which can accurately identify abnormal states based on individual child baseline values, optimize the timing and accuracy of early warning triggers, reduce missed and false alarms, and enable simultaneous push of early warning information to multiple terminals, ensuring that medical staff can obtain abnormal information in a timely manner and take appropriate measures, thereby improving the medical safety of pediatric MRI sedation examinations.

[0019] This invention employs an MRI-compatible synchronous control design, enabling it to optimize acquisition timing in conjunction with MRI scanning equipment. This reduces interference from MRI scan pulses on signal acquisition, ensuring the accuracy and integrity of critical physiological data. The system also features full-process monitoring data storage, visualization, and traceability capabilities, allowing for multi-terminal synchronous monitoring and hierarchical access control, adapting to various clinical scenarios. The system significantly improves overall pediatric suitability, MRI compatibility, monitoring accuracy, and safety protection, making it widely applicable to the clinical monitoring needs of pediatric MRI sedation examinations. Attached Figure Description

[0020] Figure 1 This is a schematic block diagram of the non-magnetic monitoring system for real-time early warning of MRI environment in children under sedation proposed in this invention; Figure 2 Grouped bar charts comparing signal acquisition stability rates in children of different age groups; Figure 3 A grouped bar chart comparing the accuracy of sedation depth assessment in children at different stages of sedation; Figure 4 A bar chart comparing the accuracy of early warnings for different types of abnormal events; Figure 5 Line graph comparing the effective signal acquisition rate under different NMR scanning sequences; Figure 6 A bar chart comparing the incidence of imaging artifacts under different field strength NMR equipment. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0023] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0024] Reference Figures 1 to 6 A real-time early warning and non-magnetic monitoring system for children in sedation MRI environment, comprising: The entire system is a non-magnetic support module made of non-metallic, non-magnetic material, containing no ferromagnetic substances. Its structural dimensions are adapted to the mounting position of the MRI scanning bed. This support module is installed on the MRI scanning bed to support all components of the system placed inside the MRI scanning cavity. The multi-parameter non-magnetic sensing acquisition module has a flexible, conforming surface at the acquisition end of each sensing unit that is adapted to the characteristics of a child's body surface. The non-invasive fiber optic sensing unit includes at least one fiber optic heart rate sensor, one fiber optic respiratory rate sensor, one fiber optic blood oxygen sensor, and one fiber optic body temperature sensor. The non-magnetic EEG acquisition unit includes a flexible electrode array, and the body movement monitoring unit includes an acceleration sensing element. The signal isolation transmission module includes an all-fiber transmission link and a multi-level electrical isolation structure. The first end of the all-fiber transmission link is located in the NMR scanning room and is connected to the signal output end of the multi-parameter non-magnetic sensing acquisition module through an optical fiber coupler. The second end of the all-fiber transmission link extends through the waveguide or filter board of the NMR scanning room to the external operating room and is connected to the input end of the multi-level electrical isolation structure. The output end of the multi-level electrical isolation structure is connected to the subsequent signal processing circuit. The all-fiber transmission link is connected to the NMR scanning cavity without any metal conductive medium throughout. The multi-dimensional analysis module for pediatric sedation includes a signal preprocessing unit, a feature extraction unit, and a fusion analysis unit. The signal preprocessing unit includes a digital filter bank for filtering out NMR gradient fields and radio frequency pulse interference. The feature extraction unit extracts the bispectral index from the preprocessed EEG signal, extracts heart rate variability parameters and respiratory rate variability parameters from physiological signs, and extracts body movement amplitude parameters from body movement signals. The fusion analysis unit performs weighted fusion calculations on the bispectral index, respiratory rate variability parameters, heart rate variability parameters, and body movement amplitude parameters based on preset age-group weighting coefficients, and outputs a quantitative index of pediatric sedation depth and sedation status classification results. The real-time graded early warning module includes a threshold storage unit, a comparison and judgment unit, and an early warning output unit. The threshold storage unit stores the preset vital sign safety thresholds and sedation state grading thresholds for different age groups. The comparison and judgment unit compares the sedation state grading results and physiological sign data output by the multi-dimensional analysis module of children's sedation state with the corresponding thresholds one by one. The early warning output unit generates an early warning signal of the corresponding level based on the comparison results and drives the non-magnetic sound and light alarm terminal and the operation room display terminal to synchronously display the early warning information. The MRI-compatible synchronous control module includes an interface unit for communicating with the MRI scanning equipment and an acquisition timing control unit. The interface unit receives scanning sequence trigger node signals and operating status signals sent by the MRI scanning equipment. The acquisition timing control unit adjusts the sampling clock of each sensing unit in the multi-parameter non-magnetic sensing acquisition module according to the trigger node signals and establishes an association index between the monitoring data and the MRI image data within the same time window. The monitoring data storage and visualization module includes a data storage unit and a visualization processing unit. The data storage unit stores the full-process monitoring data, sedation analysis results and early warning event data in layers according to timestamps. The visualization processing unit retrieves multi-parameter data for a specified period from the data storage unit and generates multi-parameter trend change curves, which are then rendered and output on the operation terminal display interface. It also provides a historical data backtracking and retrieval entry. The terminal interaction control module includes an operating terminal deployed in the safe area of ​​the MRI operating room. The operating terminal runs monitoring and management software, which includes a monitoring parameter threshold setting interface, an early warning level adjustment interface, a sensor calibration interface, and a data query and export interface.

[0025] This invention also includes a child-specific non-magnetic sensor fixation module, which is made of medical-grade flexible non-magnetic low-sensitivity material. It comprises a head strap, a surface sensor fixation patch, and an anti-slip strap. The surfaces of the head strap and the surface sensor fixation patch have anti-slip microstructure textures. The head strap, surface sensor fixation patch, and anti-slip strap are designed with corresponding sizes for newborns, infants, and preschool children. The head strap, surface sensor fixation patch, and anti-slip strap are detachably and integrally connected to the various sensor units of the multi-parameter non-magnetic sensor acquisition module via non-magnetic buckles or Velcro. The outer surface of the head strap and the surface sensor fixation patch has MRI-compatible non-magnetic positioning markers. The outer layer of the anti-slip strap has an anti-scratch covering layer to reduce the risk of sensor unit displacement and detachment caused by agitation during the child's sedation and recovery period, while maintaining the scanning imaging quality of the MRI equipment throughout the process.

[0026] This invention also includes a global electromagnetic shielding module for the nuclear magnetic resonance (NMR) environment. This module comprises a sensor-end shielding layer, a transmission link shielding layer, and a terminal shielding cavity. The sensor-end shielding layer is a nanoscale non-magnetic shielding coating applied to the outer surface of each sensor unit of the multi-parameter non-magnetic sensing acquisition module. The transmission link shielding layer is a spiral-shaped all-dielectric shielding layer wrapped around the outer layer of the all-fiber transmission link. The terminal shielding cavity is a double-layer non-metallic shielding cavity located in the external operating room. A dedicated grounding cable connecting to the equipotential grounding system of the NMR room is provided between the inner and outer layers of the double-layer non-metallic shielding cavity. The nanoscale non-magnetic shielding coating of the sensor-end shielding layer contains an interference-suppressing conductive mesh for the NMR gradient field frequency range. The transmission link shielding layer has a band-stop filter structure for the NMR radio frequency operating frequency band, shielding only the interference frequency band without affecting the normal operating frequency band of the NMR equipment. This further reduces the interference of NMR radio frequency pulses and gradient field changes on the acquisition of monitoring signals, while simultaneously blocking the leakage of the system's own electromagnetic signals, ensuring the uniformity and clarity of NMR imaging throughout the process.

[0027] In this invention, the multi-dimensional analysis module for children's sedation states incorporates a quantitative assessment unit for the depth of sedation in children. It generates a quantitative index for the depth of sedation in children through weighted fusion calculation of multiple feature parameters. The calculation formula is as follows: ,in A quantitative index for the depth of sedation in children. The weighting coefficient of the bispectral index of brainwaves. This is the weighting coefficient for respiratory rate variability. This is the weighting coefficient for heart rate variability. This is the weighting coefficient for the amplitude of body movement, and + + + =1, Bispectral index (BPI) of brainwaves. For respiratory rate variability parameters, For heart rate variability parameters, For body movement amplitude parameters, the module has a built-in library of age-group weighted coefficient presets, which sets differentiated initial weight values ​​for newborns, infants, and preschool children. The weight allocation can be adaptively adjusted according to the type of sedative drug and the administration method. Simultaneously, a built-in signal artifact filtering algorithm is incorporated to remove abnormal signal fragments caused by MRI interference. The fusion and quantification of multi-dimensional physiological and behavioral characteristics can improve the accuracy of sedation depth assessment in children, reduce the result bias caused by assessment of a single EEG parameter, and adapt to the physiological development characteristics of children.

[0028] In this invention, the real-time graded early warning module further includes an early warning event tracing unit. The early warning event tracing unit includes a data latch and a standardized report generator when an early warning is triggered. When any early warning level is triggered, the data latch automatically latches multi-parameter raw data, MRI scan sequence data, and sedation administration data for a first preset duration before and after the early warning trigger time. The standardized report generator reads the data latched by the data latch and generates a standardized early warning event report according to the report template. The early warning event report includes fields for early warning trigger time, trigger reason, parameter change trend curve, and sedation status grading result. The standardized report generator also has a pre-stored clinical treatment standard template library indexed by early warning type. It matches the corresponding treatment suggestion template according to the current early warning type and embeds it into the standardized early warning event report. The data storage unit includes a warning event classification and archiving subunit. The warning event classification and archiving subunit classifies and stores warning event reports according to risk level and anomaly type, and is equipped with a desensitization processing interface and a compliance export interface.

[0029] In this invention, the multi-parameter non-magnetic sensor acquisition module further includes a sleep apnea monitoring unit. The sleep apnea monitoring unit includes a first fiber optic respiratory sensor and a second fiber optic respiratory sensor. The first fiber optic respiratory sensor is attached to the child's chest cavity to collect chest respiratory motion signals, and the second fiber optic respiratory sensor is attached to the child's abdominal cavity to collect abdominal respiratory motion signals. The sleep apnea monitoring unit also includes a dual-channel signal fusion analysis subunit. This subunit receives the two respiratory motion signals output by the first and second fiber optic respiratory sensors, distinguishes between central sleep apnea events and obstructive sleep apnea events by comparing the phase and amplitude differences of chest and abdominal respiratory motions, and simultaneously receives blood oxygen saturation signals. It then grades the respiratory abnormality event based on the rate and duration of blood oxygen saturation decline. The analysis result signal output of the sleep apnea monitoring unit is connected to the fusion analysis unit of the child's sedation state multi-dimensional analysis module.

[0030] In this invention, the real-time graded early warning module has a built-in dynamic risk assessment unit, which can calculate the abnormal risk level based on the real-time changing trend of children's physiological parameters. The calculation formula is as follows: ,in The risk level of abnormal physiological parameters. The number of physiological parameters involved in the evaluation. For the first Real-time monitoring values ​​of several physiological parameters For the first Individual baseline values ​​for several physiological parameters For the first The safe range of fluctuation for several physiological parameters For the first The risk weight coefficients for various physiological parameters can be adaptively adjusted based on the child's age, weight, sedative drug dosage, and underlying medical conditions. A sliding window algorithm is used to predict the trend of continuous risk level changes, identify potential physiological abnormalities in advance, and link the risk assessment results with the MRI scan process. In a high-risk state, a prompt signal to pause the scan is sent to the MRI equipment. At the same time, risk level change nodes are marked on the monitoring data trend curve to achieve continuous quantitative assessment of risk levels, optimize the timing and accuracy of early warning triggers, and reduce the problems of missed and false alarms.

[0031] In this invention, the NMR-compatible synchronization control module further includes a scan gap acquisition optimization unit, which includes a sequence type identification subunit, a sampling parameter adjustment subunit, and an adaptive filtering subunit. The sequence type identification subunit pre-stores radio frequency pulse timing feature templates corresponding to three sequence types: conventional MRI scan, enhanced scan, and functional imaging. By matching the scan sequence trigger node signal received by the interface unit with each feature template, the current sequence type identification result is output. The sampling parameter adjustment subunit retrieves the corresponding sampling frequency adjustment curve from the preset acquisition timing optimization strategy table according to the sequence type identification result. During the high interference period of the scanning sequence, the sampling frequency of the multi-parameter non-magnetic sensor acquisition module is lowered to a first frequency value, and during the low interference period between scanning sequences, the sampling frequency is raised to a second frequency value, where the second frequency value is higher than the first frequency value. The adaptive filtering subunit retrieves the corresponding digital filter coefficient combination from the preset filtering parameter table based on the interference spectrum characteristics corresponding to the sequence type identification result, and loads it into the digital filter bank of the signal preprocessing unit.

[0032] In this invention, the monitoring data storage and visualization module further includes a multi-terminal synchronous display unit. The multi-terminal synchronous display unit includes a first push channel, a second push channel, and a third push channel. The first push channel is connected to a fixed operating terminal deployed in the MRI operating room, pushing full-parameter, full-process monitoring data and complete sedation status analysis results to it. The second push channel is connected to a handheld mobile terminal of medical staff through the hospital's internal wireless network, pushing core vital sign values ​​and early warning information summaries to it. The third push channel is connected to a monitoring terminal at the nurse station through the hospital's internal LAN, pushing a summary list of monitoring status for multiple beds to it. The multi-terminal synchronous display unit also includes a video access subunit. The video access subunit connects to the video stream of the non-magnetic monitoring camera installed in the nuclear magnetic equipment room through a video signal line, and renders the video image and monitoring data curve synchronously in different areas on the same terminal display interface. The multi-terminal synchronous display unit also includes a hierarchical push control subunit. The hierarchical push control subunit configures a push strategy according to the warning level: low-level warnings are only pushed to the first push channel, medium-level warnings are pushed to both the first and second push channels, and high-level warnings are pushed to all three push channels and trigger audio and visual prompts on each terminal.

[0033] This invention also includes an individual benchmark adaptive calibration module, which comprises a three-stage benchmark acquisition unit, an individualized correction unit, and a benchmark dynamic update unit. The three-stage baseline acquisition unit acquires physiological data of the child's resting state for a second preset duration in the pre-sedation induction stage, the post-sedation induction stage, and the pre-scanning stage, respectively, and generates initial baseline values ​​corresponding to each of the three stages. The individualized correction unit receives the input individualized information of the child's age, gender, weight, type of underlying disease, type and dosage of sedative drug, corrects each initial baseline value according to the preset individualized correction coefficient table, and outputs the individual baseline value. During the scanning process, when the child is detected to be in a stable sedated state and without any abnormal events, the benchmark dynamic update unit re-collects physiological data for a third preset duration at preset time intervals. The statistical mean of the newly collected data is weighted and averaged with the current individual benchmark value according to preset weights to obtain the updated individual benchmark value, which replaces the corresponding general group threshold in the threshold storage unit of the real-time graded early warning module. The three-stage benchmark acquisition unit and benchmark dynamic update unit both contain an abnormal data identification and removal subunit. The abnormal data identification and removal subunit filters the acquired physiological data according to a preset reasonable value range and signal mutation threshold, removes data segments that exceed the reasonable value range or whose signal jump amplitude exceeds the signal mutation threshold, and re-acquires and completes the removed data segments. The individual benchmark adaptive calibration module also includes a calibration report generation unit, which automatically generates a standardized calibration report after calibration is completed. The standardized calibration report is stored in the full-process monitoring file of the data storage unit.

[0034] The following two examples further illustrate the specific implementation of this system: Example 1: Application of sedation in plain MRI scans of the brain in preschool children This embodiment is applied to a sedation examination scenario for a 3-year-old preschool child's cranial MRI scan. The child weighed 15kg, had no underlying diseases, and was sedated using an oral sedation regimen. The system monitors the child's vital signs and provides risk warnings throughout the sedation process, fully covering all functional modules and technical features of the system.

[0035] The entire system's non-magnetic support module is made entirely of non-metallic polyetheretherketone (PEEK) material. Its overall structure is compatible with the mounting position of the MRI scanning bed. All components have undergone MRI compatibility testing, contain no ferromagnetic materials, and can be directly fixed to the side of the scanning bed without affecting the normal scanning operation of the MRI equipment. The multi-parameter non-magnetic sensor acquisition module is also made entirely of non-metallic, non-magnetic materials. Non-invasive fiber optic sensor units are attached to the child's precordial region, fingertips, and axillary region to simultaneously collect heart rate, blood oxygen saturation, core body temperature, and respiratory rate data. The non-magnetic EEG acquisition unit uses flexible electrodes attached to preset positions on the child's head to collect EEG signals. The body movement monitoring unit is integrated into the fixed structure to collect the child's body movement displacement data. The apnea monitoring unit uses a dual-path fiber optic sensor design, attached to the child's chest and abdominal cavities respectively to collect respiratory movement signals. All sensor units employ a flexible, conforming design to the child's body surface characteristics, ensuring a non-invasive and non-irritating acquisition process.

[0036] The child-specific non-magnetic sensor fixation module is made of medical-grade flexible, non-magnetic, and low-sensitivity material, matching the body size of children aged 3 years. It includes a head fixation strap, a surface sensor fixation patch, and an anti-slip strap structure. The fixation strap and patch have anti-slip microstructures on their surfaces and adopt an integrated non-magnetic design with the sensor units, which can stably fix each sensor unit in the acquisition position without pressure or restraint during the fixation process, adapting to changes in body position during sedation. The module surface has NMR-compatible non-magnetic positioning marks and is equipped with an anti-scratch protection structure to meet the agitation prevention needs of children during the sedation recovery period. The NMR environment full-domain electromagnetic shielding module includes a nano-level non-magnetic shielding coating at the sensor end, a spiral all-dielectric shielding layer for the transmission link, and a double-layer non-metallic shielding cavity at the terminal. It adopts a graded shielding structure design, adapting to the dedicated grounding path of the equipotential system design of the NMR room, setting up a dedicated interference suppression structure for changes in the NMR gradient field, and implementing a band-stop shielding design for the NMR radio frequency operating frequency band, shielding only the interference frequency band without affecting the normal operating frequency band of the NMR equipment.

[0037] The signal isolation transmission module adopts an all-fiber optic transmission link with a total length of 30 meters. Combined with a multi-level electrical isolation structure, it achieves unidirectional isolated signal transmission between the MRI scanning room and external operations. No metal conductive medium is connected to the MRI scanning cavity throughout the transmission process, shielding the strong magnetic field and radio frequency pulses from interfering with the acquired signals, while simultaneously preventing the leakage of the system's own electromagnetic signals. The multi-dimensional analysis module for pediatric sedation includes a built-in sedation depth analysis algorithm optimized for children. It incorporates a pre-set library of age-group weight coefficients, matching the initial weight values ​​for 3-year-old children. The weight allocation is adaptively adjusted based on the type of oral sedative medication. Simultaneously, a built-in signal artifact filtering algorithm removes abnormal signal fragments caused by MRI interference. It performs feature extraction and fusion analysis on the acquired EEG signals and physiological signs data, accurately identifying the grading results of the child's sedation state and simultaneously capturing characteristic signals of abnormal body movement and respiratory rhythm.

[0038] The individual baseline adaptive calibration module collects physiological data of children at rest for a preset duration in three stages: before sedation induction, after sedation induction, and before scanning. It generates a dynamically changing individual baseline and, combined with the child's age, gender, weight, and type and dosage of sedative medication, performs individualized corrections to the baseline value. A dynamic update mechanism for the baseline value is set up so that when the child is in a stable sedated state and there are no abnormalities during scanning, the baseline value is updated at preset intervals to accommodate normal fluctuations in physiological parameters caused by changes in sedation depth. During the calibration process, it automatically identifies and removes abnormal data caused by body movement and electromagnetic interference, and completes valid data collection again. After calibration, a standardized calibration report is automatically generated and synchronously stored in the full-process archive of monitoring data, replacing the general population threshold update to the real-time graded early warning module.

[0039] The MRI-compatible synchronous control module establishes a communication connection with the MRI scanning equipment, acquires the trigger nodes and operating status of the MRI plain scan sequence, and synchronously controls the acquisition timing of the sensor acquisition module. The scan gap acquisition optimization unit automatically identifies the MRI plain scan sequence type and matches the corresponding acquisition timing optimization strategy. According to the gap period of the MRI scan sequence, it adjusts the sampling frequency and acquisition power of the sensor acquisition module, reduces the sampling frequency during the high interference period of the scan sequence, and increases the sampling frequency during the low interference period of the scan gap. Simultaneously, based on the interference characteristics of the current scan sequence, it adaptively adjusts the digital filtering parameters of the acquired signal to further filter out residual MRI interference. During the high interference period, it maintains continuous acquisition of core vital signs parameters without interruption, automatically identifies and repairs signal segments interfered with during the scan, and synchronously associates monitoring data and MRI image data.

[0040] The real-time graded early warning module pre-stores vital sign safety thresholds and sedation status grading thresholds suitable for children, and completes threshold adaptation using individual benchmark values. It has a built-in dynamic risk assessment unit that uses a sliding window algorithm to predict the trend of continuous risk level change curves, identify potential physiological abnormality risks in advance, and trigger the corresponding level of early warning based on the analysis results and threshold comparison results. The early warning signal is displayed synchronously through a non-magnetic audio-visual terminal and the operating room terminal, and supports graded push of early warning information. In high-risk situations, a prompt signal to pause scanning is sent to the MRI equipment. The early warning event tracing unit simultaneously latches multi-parameter raw data, MRI scan sequence data, and sedation administration data for a preset time before and after the early warning when the early warning is triggered, and automatically generates a standardized early warning event report, which fully records the early warning trigger time, triggering reason, parameter change trend, and sedation status grading result. Based on the early warning type, it automatically matches the clinical treatment guidelines to generate treatment suggestion templates, and supports medical staff to add treatment records and complete the association storage with the early warning report.

[0041] The monitoring data storage and visualization module stores real-time monitoring data, sedation analysis results, and early warning event data collected throughout the entire process, generating multi-parameter trend curves for visualization on the operating terminal. It supports full-process backtracking and retrieval of historical data. The multi-terminal synchronous display unit simultaneously pushes real-time monitoring data, sedation status analysis results, and early warning information to fixed terminals in the operating room, handheld mobile terminals for medical staff, and monitoring terminals at the nurse station. Differentiated display content is matched to the usage scenarios of different terminals, and a tiered push mechanism is set up for different levels of early warnings. High-level early warnings trigger simultaneous audio-visual prompts on multiple terminals. Parameter adjustment and data query operation logs are automatically retained for all terminals, and the operation permissions for different terminals adopt a tiered control mode. The terminal interaction control module is deployed in a secure area of ​​the MRI operating room, supporting medical staff in setting monitoring parameter thresholds, adjusting early warning levels, calibrating sensors, and querying and exporting data. The interactive interface is adapted to the operational needs of pediatric sedation monitoring.

[0042] Table 1 Comparison of core performance of this system with traditional MRI monitoring equipment Table 1 shows data from a clinical controlled trial of 120 preschool children undergoing MRI sedation, comparing the core performance of this system with traditional MRI monitoring equipment. Traditional equipment is primarily designed for adults, lacking adequate adaptation to children's physiological characteristics, exhibiting significant biases in sedation depth assessment, low recognition rates of respiratory abnormalities, susceptibility to interference from strong MRI magnetic fields leading to insufficient effective signal acquisition, and prone to MRI imaging artifacts, resulting in low accuracy in abnormality warnings. This system, optimized through technologies such as a child-specific non-magnetic design, multi-dimensional sedation state analysis, full-domain electromagnetic shielding, and individual baseline adaptive calibration, demonstrates significantly superior core performance compared to traditional equipment, fully meeting the clinical monitoring needs of pediatric MRI sedation examinations.

[0043] Example 2: Application of neonatal brain MRI with contrast enhancement and sedation examination This embodiment is applied to the sedation examination scenario of a 14-day-old newborn's cranial MRI enhanced scan. The newborn weighed 3.2kg and was diagnosed with hypoxic-ischemic encephalopathy. The clinical sedation was induced by intravenous sedation. This system monitors the vital signs and provides risk warnings for the newborn throughout the sedation process, fully covering all functional modules and technical features of the system.

[0044] The entire system's non-magnetic load-bearing module is made of non-metallic medical-grade materials. The overall structure is adapted to the dedicated mounting position of the neonatal MRI scanning bed. All components have completed MRI compatibility and biosafety tests. They contain no ferromagnetic materials and can be directly fixed to the side of the scanning bed without affecting the newborn's positioning or the enhanced scanning operation of the MRI equipment. The multi-parameter non-magnetic sensor acquisition module is made of miniaturized, all-non-metallic, non-magnetic material, adapted to the body surface size of newborns. The non-invasive fiber optic sensor units are respectively attached to the newborn's precordial region, soles of the feet, and axillae to simultaneously collect heart rate, blood oxygen saturation, core body temperature, and respiratory rate data. The non-magnetic EEG acquisition unit uses miniature flexible electrodes attached to preset positions on the newborn's head to collect EEG signals. The body movement monitoring unit adopts a miniaturized design and is integrated into a fixed structure to collect the newborn's minute body movement displacement data. The apnea monitoring unit adopts a dual-path miniature fiber optic sensor design, respectively attached to the newborn's chest cavity and abdominal cavity to collect respiratory movement signals. All sensor units adopt an ultra-soft fit design to adapt to the delicate body surface characteristics of newborns, and the acquisition process is non-invasive and non-irritating.

[0045] The child-specific non-magnetic sensor fixation module is made of medical-grade ultra-soft, non-magnetic, and low-sensitivity material, matching the body size of newborns. It includes a newborn-specific head fixation strap, a surface sensor fixation patch, and an anti-displacement strap structure. The fixation strap and patch feature a breathable microporous design and are integrated with the sensor units using a non-magnetic design, stably fixing each sensor unit in the acquisition position without pressure or restraint, avoiding damage to the newborn's delicate skin. It adapts to the slight positional changes of newborns under sedation. The module surface is equipped with MRI-compatible non-magnetic positioning markers and a wraparound protective structure to prevent sensor unit displacement caused by newborn movement. The MRI environment full-domain electromagnetic shielding module includes a nano-level non-magnetic shielding coating at the sensor end, a spiral all-dielectric shielding layer for the transmission link, and a double-layer non-metallic shielding cavity at the terminal. It adopts a graded shielding structure design, with a dedicated grounding path adapted to the equipotential system design of MRI rooms. It features a dedicated interference suppression structure for gradient field changes in MRI enhancement scanning sequences and a band-stop shielding design for the MRI radio frequency operating band, shielding only the interference frequency band without affecting the normal operating frequency band of the MRI equipment.

[0046] The signal isolation transmission module adopts an all-fiber optic transmission link with a total length of 35 meters. Combined with a multi-level electrical isolation structure, it achieves unidirectional isolated signal transmission between the MRI scanning room and external operating rooms and the neonatal intensive care unit. No metal conductive media are connected to the MRI scanning cavity throughout the transmission process, shielding the strong magnetic field of the MRI and radio frequency pulses from interfering with the acquired signals, while simultaneously preventing the leakage of the system's own electromagnetic signals. The multi-dimensional analysis module for pediatric sedation status incorporates a sedation depth analysis algorithm optimized for the neonatal population. It includes a pre-set library of weight coefficients specific to newborns, matching their physiological development characteristics and adaptively adjusting weight allocation based on the type of intravenous sedation drug. Simultaneously, it incorporates a highly sensitive signal artifact filtering algorithm to eliminate abnormal signal fragments caused by MRI interference and subtle neonatal movements. It performs feature extraction and fusion analysis on the acquired EEG signals and physiological signs data to accurately identify the grading results of neonatal sedation status and simultaneously capture characteristic signals of apnea and abnormal respiratory rhythms.

[0047] The individual baseline adaptive calibration module collects neonatal resting state physiological data for a preset duration in three stages: before sedation induction, after sedation induction, and before scanning. It generates a dynamically changing individual baseline and, combined with the neonate's corrected gestational age, weight, underlying diseases, and the type and dosage of sedative drugs, performs individualized corrections to the baseline values. It sets up a more frequent dynamic update mechanism for the baseline values. When the neonate is in a stable sedated state and there are no abnormalities during the scanning process, the baseline values ​​are updated at shorter preset intervals to adapt to the rapid fluctuations in neonatal physiological parameters. During the calibration process, it automatically identifies and removes abnormal data caused by body movement and electromagnetic interference, and completes valid data acquisition again. After calibration, it automatically generates a standardized calibration report and stores it synchronously in the full-process monitoring data archive, replacing the general population threshold update to the real-time graded early warning module.

[0048] The MRI-compatible synchronous control module establishes a communication connection with the MRI scanning equipment, acquires the trigger nodes and operating status of the MRI-enhanced scanning sequence, and synchronously controls the acquisition timing of the sensor acquisition module. The scanning gap acquisition optimization unit automatically identifies different sequence types of MRI-enhanced scanning, matches the corresponding acquisition timing optimization strategy, and adjusts the sampling frequency and acquisition power of the sensor acquisition module according to the gap time of the MRI scanning sequence. The sampling frequency is reduced during the high interference period of the scanning sequence and increased during the low interference period of the scanning gap. Simultaneously, based on the interference characteristics of the current scanning sequence, the digital filtering parameters of the acquired signal are adaptively adjusted to further filter out residual MRI interference. During the high interference period, the continuous acquisition of core vital signs parameters is maintained without interruption. The module automatically identifies and repairs signal segments that are interfered with during the scanning process and synchronously associates monitoring data with MRI image data.

[0049] The real-time graded early warning module pre-stores vital sign safety thresholds and sedation status grading thresholds suitable for the neonatal population. It completes threshold adaptation using individual neonatal baseline values ​​and has a built-in dynamic risk assessment unit. Through a sliding window algorithm, it predicts the trend of continuous risk level change curves, identifies potential physiological abnormality risks in advance, and triggers corresponding level early warnings based on the analysis results and threshold comparison results. The early warning signal is simultaneously displayed through the non-magnetic audio-visual terminal, the operating room terminal, and the neonatal intensive care unit terminal. It supports graded push of early warning information. In high-risk situations, it sends a prompt signal to the MRI equipment to pause scanning. The early warning event tracing unit simultaneously latches multi-parameter raw data, MRI scan sequence data, and sedation administration data for a preset time before and after the early warning when the early warning is triggered. It automatically generates a standardized early warning event report, which fully records the early warning trigger time, triggering reason, parameter change trend, and sedation status grading result. Based on the early warning type, it automatically matches the neonatal clinical treatment guidelines to generate treatment suggestion templates and supports medical staff to add treatment records and link them with the early warning report for storage.

[0050] The monitoring data storage and visualization module stores real-time monitoring data, sedation analysis results, and early warning event data collected throughout the entire process, generating multi-parameter trend curves for visualization on the operating terminal. It supports full-process backtracking and retrieval of historical data. The multi-terminal synchronous display unit simultaneously pushes real-time monitoring data, sedation status analysis results, and early warning information to fixed terminals in the operating room, handheld mobile terminals for medical staff, and monitoring terminals in the neonatal intensive care unit. Differentiated display content is matched to the usage scenarios of different terminals, and a tiered push mechanism is set for different levels of early warnings. High-level early warnings trigger simultaneous audio-visual prompts on multiple terminals. Parameter adjustment and data query operation logs are automatically retained for all terminals, and the operation permissions for different terminals adopt a tiered control mode. The terminal interaction control module is deployed in the secure areas of the MRI operating room and the neonatal intensive care unit, supporting medical staff in setting monitoring parameter thresholds, adjusting early warning levels, calibrating sensors, and querying and exporting data. The interactive interface is adapted to the refined operational needs of neonatal sedation monitoring.

[0051] Table 2. Statistics on the monitoring performance of this system in children of different age groups. Table 2 shows data from clinical application statistics of 200 children of different ages undergoing MRI sedation examinations, covering the entire age range from newborns to preschool children. Existing MRI monitoring equipment is mostly only suitable for adults, exhibiting poor adaptability to the physiological characteristics of young children, especially newborns. It suffers from insufficient signal acquisition stability and significant deviations in sedation state recognition, failing to meet the monitoring needs of pediatrics across all age groups. This system, through age-group sensor design, weighted coefficient adaptation, and individualized benchmark calibration, maintains excellent monitoring performance across all age groups. Even for newborns with unique physiological characteristics, it achieves stable signal acquisition and accurate risk warnings. Its non-magnetic compatibility performance meets all standards, comprehensively covering the clinical monitoring needs of pediatric MRI examinations across all age groups.

[0052] Reference Figure 2 This system visually demonstrates the differences between this system and traditional equipment in terms of adaptability to children's physiological characteristics. Traditional MRI monitoring equipment is mostly designed for adults, and the sensor unit size, fit, and fixation method do not take into account the delicate skin and subtle movements of young children, especially newborns. This makes it prone to sensor unit displacement and signal acquisition interruption, and the stability rate decreases significantly with age, failing to meet the monitoring needs of pediatrics across all age groups. This system, through age-appropriate miniaturized flexible sensor design, anti-slip and breathable integrated fixation structure, and ultra-sensitive signal artifact filtering algorithm, maintains an extremely high signal acquisition stability rate across all age groups. Even for newborns with special physiological characteristics, the stability rate is close to 98%, ensuring the reliability and continuity of monitoring data throughout the entire process.

[0053] Reference Figure 3 This invention comprehensively covers all five core stages of sedation assessment. Traditional MRI monitoring equipment relies solely on a single EEG parameter to assess sedation depth. During the scanning process, interference from MRI radiofrequency pulses and gradient fields leads to severe EEG signal artifacts, significantly reducing assessment accuracy. Furthermore, it is insensitive to capturing changes in sedation status during induction and recovery phases, resulting in overall low accuracy. This invention's system utilizes a sedation depth analysis algorithm that integrates multi-dimensional physiological and behavioral characteristics, combined with MRI-compatible synchronous timing control and signal artifact filtering technology. It maintains extremely high assessment accuracy throughout the entire sedation process, even during the most disruptive scanning phase, without a significant decrease in accuracy. It can accurately capture dynamic changes in children's sedation status, providing reliable data support for clinical sedation management.

[0054] Reference Figure 4This invention covers the five most common safety risk events during pediatric sedation examinations. Traditional MRI monitoring equipment often uses fixed group thresholds to trigger warnings, which are poorly adapted to individual physiological differences in children, easily leading to missed and false alarms. This is especially true for highly insidious and rapidly progressing abnormalities such as apnea and pre-awakening symptoms, where the accuracy of warnings is severely insufficient, leaving insufficient time for clinical intervention. The system of this invention generates child-specific safety thresholds through an individual baseline adaptive calibration module. Combined with dynamic risk assessment and multi-dimensional feature recognition, it achieves high-accuracy warnings for all types of abnormal events. In particular, the accuracy of warnings for apnea and pre-awakening symptoms, where traditional equipment has significant weaknesses, is significantly improved. This allows for early identification of potential safety risks and greatly enhances the medical safety of pediatric MRI sedation examinations.

[0055] Reference Figure 5 This invention covers the five most commonly used scanning sequences in pediatric MRI examinations. Traditional MRI monitoring equipment lacks synchronous control with the MRI scanning equipment and is not optimized for the interference characteristics of different scanning sequences. As the interference intensity of the scanning sequence increases, the effective signal acquisition rate declines significantly. Under high-interference sequences such as functional imaging, the effective signal acquisition rate is less than 70%, making continuous and reliable monitoring impossible. The system of this invention, through an MRI-compatible synchronous control module, can automatically identify different scanning sequence types, match corresponding acquisition timing optimization strategies and filtering parameters, and, combined with a full-domain electromagnetic shielding design, significantly reduce the interference of MRI scanning pulses on signal acquisition. Even for high-interference functional imaging sequences, the effective signal acquisition rate is close to 98%, ensuring continuous and effective acquisition of monitoring signals under various scanning sequences, achieving uninterrupted monitoring throughout the scanning process.

[0056] Reference Figure 6 This invention covers mainstream clinical and research-grade MRI equipment. Traditional MRI monitoring equipment contains conductive metal media and has an imperfect non-magnetic design, making it prone to magnetic field homogeneity disruption in strong magnetic field environments, leading to artifacts in MRI imaging. Furthermore, the artifact rate increases significantly with increasing field strength, severely impacting the accuracy of image diagnosis and sometimes requiring repeated scans. The system of this invention employs a completely non-magnetic design, with no conductive metal media connected to the scanning cavity in the all-fiber signal transmission link. Combined with a full-domain electromagnetic shielding design to prevent electromagnetic signal leakage, the imaging artifact rate remains extremely low across various field strengths of MRI equipment. Even with a 7.0T high-field research device, the artifact rate is less than 1%, ensuring no impact on MRI imaging quality throughout the process. No adjustment to the scanning scheme is needed to avoid artifacts, making it fully compatible with the usage requirements of various clinical MRI equipment.

[0057] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A real-time early warning and non-magnetic monitoring system for children in a sedative state using an MRI environment, characterized in that, include: The entire system is a non-magnetic support module, which is installed on the MRI scanning bed to support all components of the system placed inside the MRI scanning cavity. A multi-parameter non-magnetic sensing acquisition module includes a non-invasive fiber optic sensing unit, a non-magnetic electroencephalogram (EEG) acquisition unit, and a body movement monitoring unit. The non-invasive fiber optic sensing unit includes at least one fiber optic heart rate sensor, one fiber optic respiratory rate sensor, one fiber optic blood oxygen sensor, and one fiber optic body temperature sensor. The non-magnetic EEG acquisition unit includes a flexible electrode array, and the body movement monitoring unit includes an acceleration sensing element. The signal isolation transmission module includes an all-fiber transmission link and a multi-level electrical isolation structure. The first end of the all-fiber transmission link is located in the NMR scanning room and is connected to the signal output end of the multi-parameter non-magnetic sensing acquisition module through an optical fiber coupler. The second end of the all-fiber transmission link extends through the waveguide or filter board of the NMR scanning room to the external operating room and is connected to the input end of the multi-level electrical isolation structure. The output end of the multi-level electrical isolation structure is connected to the subsequent signal processing circuit. The all-fiber transmission link is connected to the NMR scanning cavity without any metal conductive medium throughout. The terminal interaction control module includes an operating terminal deployed in the safe area of ​​the MRI operating room. The operating terminal runs monitoring and management software, which includes a monitoring parameter threshold setting interface, an early warning level adjustment interface, a sensor calibration interface, and a data query and export interface.

2. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, Also includes: The multi-dimensional analysis module for pediatric sedation includes a signal preprocessing unit, a feature extraction unit, and a fusion analysis unit. The signal preprocessing unit includes a digital filter bank for filtering out NMR gradient fields and radio frequency pulse interference. The feature extraction unit extracts the bispectral index from the preprocessed EEG signal, extracts heart rate variability parameters and respiratory rate variability parameters from physiological signs, and extracts body movement amplitude parameters from body movement signals. The fusion analysis unit performs weighted fusion calculations on the bispectral index, respiratory rate variability parameters, heart rate variability parameters, and body movement amplitude parameters based on preset age-group weighting coefficients, and outputs a quantitative index of pediatric sedation depth and sedation status classification results. The real-time graded early warning module includes a threshold storage unit, a comparison and judgment unit, and an early warning output unit. The threshold storage unit stores the preset vital sign safety thresholds and sedation state grading thresholds for different age groups. The comparison and judgment unit compares the sedation state grading results and physiological sign data output by the multi-dimensional analysis module of children's sedation state with the corresponding thresholds one by one. The early warning output unit generates an early warning signal of the corresponding level based on the comparison results and drives the non-magnetic sound and light alarm terminal and the operation room display terminal to synchronously display the early warning information. The MRI-compatible synchronous control module includes an interface unit for communicating with the MRI scanning equipment and an acquisition timing control unit. The interface unit receives scan sequence trigger node signals and operating status signals sent by the MRI scanning equipment. The acquisition timing control unit adjusts the sampling clock of each sensing unit in the multi-parameter non-magnetic sensing acquisition module according to the trigger node signals and establishes an association index between the monitoring data and the MRI image data within the same time window.

3. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, Also includes: The monitoring data storage and visualization module includes a data storage unit and a visualization processing unit. The data storage unit stores the full-process monitoring data, sedation analysis results and early warning event data in layers according to timestamps. The visualization processing unit retrieves multi-parameter data for a specified period from the data storage unit and generates multi-parameter trend change curves, which are then rendered and output on the operation terminal display interface. It also provides a historical data backtracking and retrieval entry. A child-specific non-magnetic sensor fixation module includes a head strap, a body sensor fixation patch, and an anti-slip strap. The surfaces of the head strap and the body sensor fixation patch are provided with anti-slip microstructure textures. The head strap, the body sensor fixation patch, and the anti-slip strap are respectively set with corresponding size specifications for the age groups of newborns, infants, and preschool children. The outer surface of the head strap and the body sensor fixation patch is provided with NMR-compatible non-magnetic positioning marks. The outer layer of the anti-slip strap is provided with an anti-scratch covering layer. The NMR environment full-domain electromagnetic shielding module comprises a sensor end shielding layer, a transmission link shielding layer, and a terminal shielding cavity. The sensor end shielding layer is a nanoscale non-magnetic shielding coating applied to the outer surface of each sensor unit of the multi-parameter non-magnetic sensing acquisition module. The transmission link shielding layer is a spiral-shaped all-dielectric shielding layer wrapped around the outer layer of the all-fiber transmission link. The terminal shielding cavity is a double-layer non-metallic shielding cavity located in an external operating room. A dedicated grounding cable connecting to the equipotential grounding system of the NMR room is provided between the inner and outer layers of the double-layer non-metallic shielding cavity. The nanoscale non-magnetic shielding coating of the sensor end shielding layer contains an interference suppression conductive mesh for the frequency range of the NMR gradient field. The transmission link shielding layer contains a band-stop filter structure for the NMR radio frequency operating frequency band.

4. The real-time early warning non-magnetic monitoring system for MRI environment in sedation state of children according to claim 1, characterized in that, The multi-dimensional analysis module for children's sedation states includes a built-in quantitative assessment unit for the depth of sedation in children, and the calculation formula is as follows: ,in A quantitative index for the depth of sedation in children. The weighting coefficient of the bispectral index of brainwaves. This is the weighting coefficient for respiratory rate variability. This is the weighting coefficient for heart rate variability. This is the weighting coefficient for the amplitude of body movement, and + + + =1, Bispectral index (BPI) of brainwaves. For respiratory rate variability parameters, For heart rate variability parameters, This refers to the amplitude parameter of body motion.

5. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, The real-time graded early warning module also includes an early warning event tracing unit. The early warning event tracing unit includes a data latch and a standardized report generator when an early warning is triggered. When any early warning level is triggered, the data latch automatically latches multi-parameter raw data, MRI scan sequence data, and sedation drug administration data for a first preset duration before and after the early warning trigger time. The standardized report generator reads the data latched by the data latch and generates a standardized early warning event report according to the report template. The early warning event report includes fields for early warning trigger time, trigger reason, parameter change trend curve, and sedation status grading result. The standardized report generator also has a pre-stored clinical treatment standard template library indexed by early warning type. It matches the corresponding treatment suggestion template according to the current early warning type and embeds it into the standardized early warning event report. The data storage unit includes a warning event classification and archiving subunit. The warning event classification and archiving subunit classifies and stores warning event reports according to risk level and anomaly type, and is equipped with a desensitization processing interface and a compliance export interface.

6. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, The multi-parameter non-magnetic sensor acquisition module also includes a sleep apnea monitoring unit. This unit comprises a first fiber optic respiratory sensor and a second fiber optic respiratory sensor. The first fiber optic respiratory sensor is attached to the child's chest cavity to collect chest respiratory motion signals, and the second fiber optic respiratory sensor is attached to the child's abdominal cavity to collect abdominal respiratory motion signals. The sleep apnea monitoring unit also includes a dual-channel signal fusion analysis subunit. This subunit receives the two respiratory motion signals output by the first and second fiber optic respiratory sensors, distinguishes between central sleep apnea events and obstructive sleep apnea events by comparing the phase and amplitude differences between chest and abdominal respiratory motions, and simultaneously receives blood oxygen saturation signals. Based on the rate and duration of blood oxygen saturation decline, it classifies and determines abnormal respiratory events. The analysis result signal output of the sleep apnea monitoring unit is connected to the fusion analysis unit of the multi-dimensional analysis module for the child's sedation state.

7. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, The real-time graded early warning module has a built-in dynamic risk assessment unit that can calculate the level of abnormal risk based on the real-time changing trends of children's physiological parameters. The calculation formula is as follows: ,in The risk level of abnormal physiological parameters. The number of physiological parameters involved in the evaluation. For the first Real-time monitoring values ​​of several physiological parameters For the first Individual baseline values ​​for several physiological parameters For the first The safe range of fluctuation for several physiological parameters For the first Risk weighting coefficients for physiological parameters.

8. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, The NMR-compatible synchronization control module also includes a scan gap acquisition optimization unit, which includes a sequence type identification subunit, a sampling parameter adjustment subunit, and an adaptive filtering subunit. The sequence type identification subunit pre-stores radio frequency pulse timing feature templates corresponding to three sequence types: conventional MRI scan, enhanced scan, and functional imaging. By matching the scan sequence trigger node signal received by the interface unit with each feature template, the current sequence type identification result is output. The sampling parameter adjustment subunit retrieves the corresponding sampling frequency adjustment curve from the preset acquisition timing optimization strategy table according to the sequence type identification result. During the high interference period of the scanning sequence, the sampling frequency of the multi-parameter non-magnetic sensor acquisition module is lowered to a first frequency value, and during the low interference period between scanning sequences, the sampling frequency is raised to a second frequency value, where the second frequency value is higher than the first frequency value. The adaptive filtering subunit retrieves the corresponding digital filter coefficient combination from the preset filtering parameter table based on the interference spectrum characteristics corresponding to the sequence type identification result, and loads it into the digital filter bank of the signal preprocessing unit.

9. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, The monitoring data storage and visualization module also includes a multi-terminal synchronous display unit. The multi-terminal synchronous display unit includes a first push channel, a second push channel, and a third push channel. The first push channel connects to a fixed operating terminal deployed in the MRI operating room and pushes full-parameter, full-process monitoring data and complete sedation status analysis results to it. The second push channel connects to the handheld mobile terminals of medical staff through the hospital's internal wireless network and pushes core vital signs values ​​and early warning information summaries to them. The third push channel connects to the nurse station monitoring terminal through the hospital's internal LAN and pushes a summary list of monitoring status for multiple beds to it. The multi-terminal synchronous display unit also includes a video access subunit. The video access subunit connects to the video stream of the non-magnetic monitoring camera installed in the nuclear magnetic equipment room through a video signal line, and renders the video image and monitoring data curve synchronously in different areas on the same terminal display interface. The multi-terminal synchronous display unit also includes a hierarchical push control subunit. The hierarchical push control subunit configures a push strategy according to the warning level: low-level warnings are only pushed to the first push channel, medium-level warnings are pushed to both the first and second push channels, and high-level warnings are pushed to all three push channels and trigger audio and visual prompts on each terminal.

10. The real-time early warning non-magnetic monitoring system for sedative children in MRI environment according to claim 1, characterized in that, It also includes an individual reference adaptive calibration module, which comprises a three-stage reference acquisition unit, an individualized correction unit, and a reference dynamic update unit; The three-stage baseline acquisition unit acquires physiological data of the child's resting state for a second preset duration in the pre-sedation induction stage, the post-sedation induction stage, and the pre-scanning stage, respectively, and generates initial baseline values ​​corresponding to each of the three stages. The individualized correction unit receives the input individualized information of the child's age, gender, weight, type of underlying disease, type and dosage of sedative drug, corrects each initial baseline value according to the preset individualized correction coefficient table, and outputs the individual baseline value. During the scanning process, when the child is detected to be in a stable sedated state and without any abnormal events, the benchmark dynamic update unit re-collects physiological data for a third preset duration at preset time intervals. The statistical mean of the newly collected data is weighted and averaged with the current individual benchmark value according to preset weights to obtain the updated individual benchmark value, which replaces the corresponding general group threshold in the threshold storage unit of the real-time graded early warning module. The three-stage benchmark acquisition unit and benchmark dynamic update unit both contain an abnormal data identification and removal subunit. The abnormal data identification and removal subunit filters the acquired physiological data according to a preset reasonable value range and signal mutation threshold, removes data segments that exceed the reasonable value range or whose signal jump amplitude exceeds the signal mutation threshold, and re-acquires and completes the removed data segments. The individual benchmark adaptive calibration module also includes a calibration report generation unit, which automatically generates a standardized calibration report after calibration is completed. The standardized calibration report is stored in the full-process monitoring file of the data storage unit.

Images