技术领域Technical Field
本发明涉及新生儿监护技术领域，具体为一种智能新生儿呼吸监测系统。The invention relates to the technical field of neonatal monitoring, and in particular to an intelligent neonatal respiratory monitoring system.
背景技术Background technique
新生儿监护是指对出生后28天内的婴儿进行医疗、护理和观察的过程，以确保他们的健康和安全，包括体温监测：确保新生儿处于适中的温度环境中；心率和呼吸监测：使用脉搏氧饱和度仪和其他设备监测新生儿的心跳和呼吸；血糖监测：确保新生儿的血糖水平在正常范围内。Neonatal care refers to the process of medical treatment, care and observation of infants within 28 days after birth to ensure their health and safety, including temperature monitoring: ensuring that the newborn is in a moderate temperature environment; heart rate and respiratory monitoring: using pulse oximeters and other equipment to monitor the heartbeat and breathing of the newborn; blood sugar monitoring: ensuring that the newborn's blood sugar level is within the normal range.
公开号为CN109276380A的申请公开了一种用于新生儿智能监护的智能婴儿床包括主控模块、射频模块、稳压控制模块、数据存储模块、数据采集处理模块、报警模块、床体操作盘以及床体调节装置，数据采集处理模块采集到的数据传送给主控模块，主控模块将接收到的数据传送给射频模块和数据存储模块，射频模块通过射频电路及天线，将采集到的数据发送至服务器形成实时体征数据，最终所述实时体征数据通过医院展示系统、app、微信等展示给医护人员和父母，数据自动进入电子病历，异常状态及时报警。The application with publication number CN109276380A discloses a smart baby bed for intelligent monitoring of newborns, including a main control module, a radio frequency module, a voltage stabilization control module, a data storage module, a data acquisition and processing module, an alarm module, a bed operating panel and a bed adjustment device. The data collected by the data acquisition and processing module is transmitted to the main control module, and the main control module transmits the received data to the radio frequency module and the data storage module. The radio frequency module sends the collected data to the server through the radio frequency circuit and antenna to form real-time vital sign data. Finally, the real-time vital sign data is displayed to medical staff and parents through the hospital display system, app, WeChat, etc. The data automatically enters the electronic medical record, and an abnormal state alarm is promptly issued.
在对新生儿进行智能监护过程中，一般基于对应新生儿产生的相应监测数值，来评定其新生儿是否存在相关问题，但原始的此类监测方式，较为大众化，因每个新生儿所产生的数值标准以及相应情况均不一致，若采用过往的监测方式，虽然也可监测出相关的问题，但很容易错过最佳的处理时机，其发现速率可能并不精准。In the process of intelligent monitoring of newborns, it is generally based on the corresponding monitoring values generated by the corresponding newborns to assess whether the newborns have relevant problems. However, this original monitoring method is more popular. Because the numerical standards and corresponding conditions generated by each newborn are inconsistent, if the past monitoring method is used, although relevant problems can be monitored, it is easy to miss the best time for treatment, and the detection rate may not be accurate.
发明内容Summary of the invention
针对现有技术的不足，本发明提供了一种智能新生儿呼吸监测系统，解决了采用过往的监测方式，虽然也可监测出相关的问题，但很容易错过最佳的处理时机，其发现速率可能并不精准的问题。In view of the deficiencies of the prior art, the present invention provides an intelligent neonatal respiratory monitoring system, which solves the problem that although the previous monitoring method can also monitor related problems, it is easy to miss the best time to deal with it, and its detection rate may not be accurate.
为实现以上目的，本发明通过以下技术方案予以实现：一种智能新生儿呼吸监测系统，包括：To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent neonatal respiratory monitoring system, comprising:
数值监测端，对新生儿的呼吸进行监测，并将所监测的呼吸幅度数值传输至波形生成端内；The numerical monitoring end monitors the breathing of the newborn and transmits the monitored breathing amplitude value to the waveform generating end;
预警端，对实时监测的呼吸幅度进行预警判定，当实时监测的呼吸幅度超出对应的预警范围时，发出预警；The early warning end makes an early warning judgment on the breathing amplitude monitored in real time, and issues an early warning when the breathing amplitude monitored in real time exceeds the corresponding early warning range;
波形生成端，基于不同时刻所产生的相关呼吸幅度，实时生成其呼吸波形变化曲线，并将所生成的呼吸波形变化曲线传输至波形分析端或波形特征判定端内；The waveform generating end generates a breathing waveform change curve in real time based on the relevant breathing amplitudes generated at different times, and transmits the generated breathing waveform change curve to the waveform analyzing end or the waveform feature determining end;
波形分析端，基于呼吸波形变化曲线的初始时刻，确定一组识别周期，对此识别周期内所产生的呼吸波形进行分析，来确定本新生儿的相关呼吸特征以及特征区间，包括：The waveform analysis end determines a set of identification cycles based on the initial moment of the respiratory waveform change curve, and analyzes the respiratory waveform generated within this identification cycle to determine the relevant respiratory characteristics and characteristic intervals of the newborn, including:
基于初始时刻，往后确定一组识别周期T，其中T为预设值，对本识别周期T内所产生的呼吸波形段进行确认，将所确认的呼吸波形段标定为待定分析段；Based on the initial moment, a set of identification cycles T is determined in the future, where T is a preset value, and the respiratory waveform segments generated within the current identification cycle T are confirmed, and the confirmed respiratory waveform segments are marked as pending analysis segments;
依次确认待定分析段内所出现的相关点，其相关点前端线段走向趋势向上，后端线段走向趋势向下，对相邻相关点之间的线段特征进行分析，其分析方式为：将相邻相关点对应线段的第一个相关点所对应的呼吸幅度标定为H1，将第二个相关点所对应的呼吸幅度标定为H2，再将两个相关点之间的时间间隔标定为JG，采用FX＝|H1-H2|×C1+JG×C2确定其对应相关点之间的分析值FX，其中C1以及C2均为预设的固定系数因子，再依据从前至后对不同线段的分析值FX进行依次确认，并生成其分析值排序序列{FX1、FX2、……、FXn}；Confirm the relevant points appearing in the pending analysis segment in sequence, the trend of the front segment of the relevant point is upward, and the trend of the rear segment is downward, and analyze the line segment characteristics between adjacent relevant points. The analysis method is: calibrate the breathing amplitude corresponding to the first relevant point of the line segment corresponding to the adjacent relevant point as H1, calibrate the breathing amplitude corresponding to the second relevant point as H2, and then calibrate the time interval between the two relevant points as JG, and use FX=|H1-H2|×C1+JG×C2 to determine the analysis value FX between the corresponding relevant points, where C1 and C2 are both preset fixed coefficient factors, and then confirm the analysis values FX of different line segments from front to back in sequence, and generate their analysis value sorting sequence {FX1, FX2, ..., FXn};
将分析值排序序列内对应的排序值进行方差处理，优先从第一组分析值FX1开始，逐步往后确认相关的分析值，来确定其方差值Fc，当Fc≤Y1时，其中Y1为预设值，则再次确定后续的分析值，当所确认的方差值Fc＞Y1时，则将所添加的分析值标定为异常值，并将异常值前端的若干组分析值标定为同类值，将同类值所对应的线段标定为同类段，再从异常值开始，往后确认其分析值，并确定其方差值Fc，采用相同的方式，对本待定分析段内所出现的同类段进行依次确认，并将同类段之间的相关线段标定为波动段；The corresponding sorted values in the sorted sequence of the analysis values are processed with variance, starting with the first group of analysis values FX1, and then confirming the related analysis values step by step to determine their variance values Fc. When Fc≤Y1, where Y1 is a preset value, the subsequent analysis values are determined again. When the confirmed variance value Fc＞Y1, the added analysis value is marked as an abnormal value, and several groups of analysis values in front of the abnormal value are marked as similar values, and the line segments corresponding to the similar values are marked as similar segments. Starting from the abnormal value, its analysis value is confirmed backward, and its variance value Fc is determined. In the same way, the similar segments appearing in the pending analysis segment are confirmed in turn, and the related line segments between the similar segments are marked as fluctuation segments.
基于所确认的同类段以及波动段，从中选取对应分析值的最大值以及最小值，并依据所确认的最大值以及最小值，生成属于同类段的平稳区间，再基于波动段所产生的最大值以及最小值，生成属于波动段的波动区间，并将平稳区间以及波动区间传输至波动特征判定端内；Based on the confirmed similar segments and fluctuating segments, the maximum value and the minimum value of the corresponding analysis value are selected, and based on the confirmed maximum value and the minimum value, a stable interval belonging to the similar segment is generated, and based on the maximum value and the minimum value generated by the fluctuating segment, a fluctuating interval belonging to the fluctuating segment is generated, and the stable interval and the fluctuating interval are transmitted to the fluctuation feature determination end;
波动特征判定端，对识别周期T后所产生的呼吸波形变化曲线进行数值分析，确定相应的波动特征，将所确定的波动特征与相关的特征区间进行比对，基于比对结果，生成不同的处理信号；包括：The fluctuation feature determination end performs numerical analysis on the respiratory waveform change curve generated after the identification period T, determines the corresponding fluctuation feature, compares the determined fluctuation feature with the relevant feature interval, and generates different processing signals based on the comparison result; including:
特征区间包括波动区间和平稳区间，再对识别周期T后对应呼吸波形变化曲线后续所产生的分析值Fk进行确认，并确认所产生的分析值Fk的所属区间，其中k代表后续不同相关点之间的线段；The characteristic interval includes a fluctuation interval and a stable interval, and then the analysis value Fk generated by the corresponding respiratory waveform change curve after the identification period T is confirmed, and the interval to which the generated analysis value Fk belongs is confirmed, where k represents the line segment between different subsequent related points;
当Fk∈平稳区间时，产生平稳信号并通过展示端展示；When Fk ∈ stable interval, a stable signal is generated and displayed through the display terminal;
当Fk∈波动区间时，产生波动信号并通过展示端展示；When Fk ∈ the fluctuation interval, a fluctuation signal is generated and displayed through the display terminal;
当平稳区间＜Fk＜波动区间时，产生介入信号，并通过展示端展示，外部医护人员基于此介入信号，判定是否需要将此部分分析值Fk填补至波动区间内，来扩大对应波动区间的相应范围；When the stable interval < Fk < the fluctuation interval, an intervention signal is generated and displayed through the display terminal. Based on this intervention signal, external medical staff determine whether it is necessary to fill this part of the analysis value Fk into the fluctuation interval to expand the corresponding range of the corresponding fluctuation interval;
还包括：Also includes:
当Fk＜平稳区间时，将本时刻所出现的分析值标定为异常值，并对后续连续出现的五组分析值进行确定，并将所确定的分析值排序为：F1、F2、F3、F4、F5以及F6，其中F1为本时刻所标定的异常值，在所确定的分析值排序序列中，当后一组分析值小于前一组分析值，则产生一组赋值“-1”，若后一组分析值不小于前一组分析值，则产生一组赋值“0”，确定赋值序列；When Fk < stable interval, the analysis value appearing at this moment is marked as an abnormal value, and the five groups of analysis values appearing successively are determined, and the determined analysis values are sorted as: F1, F2, F3, F4, F5 and F6, where F1 is the abnormal value marked at this moment. In the determined analysis value sorting sequence, when the latter group of analysis values is less than the former group of analysis values, a group of assignments "-1" is generated; if the latter group of analysis values is not less than the former group of analysis values, a group of assignments "0" is generated to determine the assignment sequence;
当Fk＞波动区间时，将本时刻所出现的分析值标定为异常值，并对后续连续出现的五组分析值进行确定，并将所确定的分析值排序为：B1、B2、B3、B4、B5以及B6，其中B1为本时刻所标定的异常值，在所确定的分析值排序序列中，当后一组分析值大于前一组分析值，则产生一组赋值“1”，若后一组分析值不大于前一组分析值，则产生一组赋值“0”；When Fk > fluctuation range, the analysis value appearing at this moment is marked as an abnormal value, and the five groups of analysis values appearing successively are determined, and the determined analysis values are sorted as: B1, B2, B3, B4, B5 and B6, where B1 is the abnormal value marked at this moment. In the determined analysis value sorting sequence, when the latter group of analysis values is greater than the former group of analysis values, a group of assignments "1" is generated; if the latter group of analysis values is not greater than the former group of analysis values, a group of assignments "0" is generated;
基于所产生的赋值序列确定赋值总和，再锁定赋值总和的绝对值JD，若JD≥Y2，其中Y2为预设值，则直接生成预警信号，且控制预警端直接产生相关警报，警示外部相关人员，反之，则继续监视比对；Determine the total value of the generated value sequence, and then lock the absolute value JD of the total value of the value. If JD≥Y2, where Y2 is a preset value, directly generate an early warning signal, and control the early warning terminal to directly generate a relevant alarm to warn relevant external personnel. Otherwise, continue to monitor and compare.
还包括另一组比对方式：Another set of comparisons is included:
当Fk＜平稳区间时，确定后续连续出现的分析值并锁定相关的分析值排序序列，将后一组分析值标定为Fh，将前一组分析值标定为Fq，当(Fq÷2)＜Fh＜Fq，则产生一组赋值“-1”，当Fh≤(Fq÷2)时，则产生一组赋值“-2”，反之，则产生赋值“0”，确定赋值序列；When Fk < stable interval, determine the subsequent continuous analysis values and lock the related analysis value sorting sequence, mark the latter group of analysis values as Fh, and mark the former group of analysis values as Fq. When (Fq÷2)＜Fh＜Fq, a group of assignments "-1" is generated. When Fh≤(Fq÷2), a group of assignments "-2" is generated. Otherwise, an assignment "0" is generated to determine the assignment sequence.
当Fk＞波动区间时，确定后续连续出现的分析值并锁定相关的分析值排序序列，将后一组分析值标定为Bh，将前一组分析值标定为Bq，当2Bq＞Bh＞Bq，则产生一组赋值“1”，当Bh≥2Bq时，则产生一组赋值“2”，反之，则产生赋值“0”，确定赋值序列；When Fk > fluctuation interval, determine the subsequent consecutive analysis values and lock the related analysis value sorting sequence, mark the latter group of analysis values as Bh, and mark the former group of analysis values as Bq. When 2Bq>Bh>Bq, a group of assignments "1" is generated. When Bh≥2Bq, a group of assignments "2" is generated. Otherwise, an assignment "0" is generated to determine the assignment sequence.
基于所产生的赋值序列确定赋值总和，再锁定赋值总和的绝对值JD，若JD≥Y2，其中Y2为预设值，则直接生成预警信号，且控制预警端直接产生相关警报，警示外部相关人员，反之，则继续监视比对。The total value of the assignments is determined based on the generated sequence of assignments, and then the absolute value JD of the total value of the assignments is locked. If JD≥Y2, where Y2 is a preset value, a warning signal is directly generated, and the control warning terminal directly generates a relevant alarm to alert relevant external personnel. Otherwise, monitoring and comparison will continue.
本发明提供了一种智能新生儿呼吸监测系统。与现有技术相比具备以下The present invention provides an intelligent neonatal respiratory monitoring system. Compared with the prior art, it has the following advantages:
有益效果：Beneficial effects:
本发明通过限定监视周期，来确定其对应新生儿的相关呼吸特征，再依次此呼吸特征作为后续监测评判的相应标准，以此来提升本智能监护系统的实用性，因每个不同的新生儿均存在不同的呼吸习惯或不同的呼吸特征，若采用统一的评判标准可能会造成数值评判的不及时或不准确，故采用数值监测确定相关线段的方式，依次确定对应的区间，来确定相关的判定信号；The present invention determines the relevant respiratory characteristics of the corresponding newborn by limiting the monitoring cycle, and then uses the respiratory characteristics as the corresponding standard for subsequent monitoring and judgment, so as to improve the practicality of the intelligent monitoring system. Because each newborn has different breathing habits or different respiratory characteristics, if a unified judgment standard is used, it may cause untimely or inaccurate numerical judgment. Therefore, the method of determining the relevant line segments by numerical monitoring is adopted, and the corresponding intervals are determined in turn to determine the relevant judgment signal;
后续，基于对应新生儿所产生的相关特征值，基于比对结果产生对应的比对信号，并供外部人员查看，此种方式，便可对每个不同新生儿的呼吸变化情况进行确认，并及时预警，基于对应的赋值序列，来识别其异常程度，以此来保障其对应新生儿的安全。Subsequently, based on the relevant characteristic values generated by the corresponding newborns, corresponding comparison signals are generated based on the comparison results and are available for external personnel to view. In this way, the respiratory changes of each newborn can be confirmed, and timely warnings can be issued. Based on the corresponding assignment sequence, the degree of abnormality can be identified to ensure the safety of the corresponding newborns.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明原理框架示意图；Fig. 1 is a schematic diagram of the principle framework of the present invention;
图2为本发明呼吸幅度变化波形示意图。FIG. 2 is a schematic diagram of a waveform showing a change in breathing amplitude according to the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
实施例一Embodiment 1
请参阅图1，本申请提供了一种智能新生儿呼吸监测系统，包括数值监测端、预警端、波形生成端、波形分析端以及波形特征判定端和展示端，其中，数值监测端分别与预警端或波形生成端输入节点电性连接，且波形生成端分别与波形分析端或波形特征判定端输入节点电性连接，且波形分析端与波形特征判定端输入节点电性连接，且波形特征判定端分别与展示端或预警端输入节点电性连接；Please refer to FIG1 . The present application provides an intelligent neonatal respiratory monitoring system, including a numerical monitoring terminal, an early warning terminal, a waveform generating terminal, a waveform analyzing terminal, a waveform feature determining terminal, and a display terminal, wherein the numerical monitoring terminal is electrically connected to the early warning terminal or the waveform generating terminal input node, and the waveform generating terminal is electrically connected to the waveform analyzing terminal or the waveform feature determining terminal input node, and the waveform analyzing terminal is electrically connected to the waveform feature determining terminal input node, and the waveform feature determining terminal is electrically connected to the display terminal or the early warning terminal input node;
其中，数值监测端，对新生儿的呼吸进行监测，并将所监测的呼吸幅度数值传输至波形生成端内，监护仪在新生儿胸部两个心电图电极之间通电，以测定阻抗呼吸，而该电流是无害的高频电流，在呼气和吸气时，随着胸部的扩张和收缩，电极之间的电阻(阻抗)也会随之变化，监护仪可以从阻抗变化中确认出相关的呼吸幅度；Among them, the numerical monitoring end monitors the breathing of the newborn and transmits the monitored breathing amplitude value to the waveform generation end. The monitor energizes between the two electrocardiogram electrodes on the chest of the newborn to measure the impedance breathing. The current is a harmless high-frequency current. When exhaling and inhaling, as the chest expands and contracts, the resistance (impedance) between the electrodes will also change. The monitor can confirm the relevant breathing amplitude from the impedance change;
其中，预警端，对实时监测的呼吸幅度进行预警判定，当实时监测的呼吸幅度超出对应的预警范围时，发出预警，警示相关人员，其中，进行预警判定的具体方式包括：Among them, the early warning end performs early warning judgment on the breathing amplitude monitored in real time. When the breathing amplitude monitored in real time exceeds the corresponding early warning range, an early warning is issued to alert relevant personnel. Among them, the specific methods of performing early warning judgment include:
将呼吸幅度标定为HXi，其中i代表不同的时刻，将呼吸幅度HXi与预设的预警范围进行比对，当HXi∈预警范围时，则不进行任何处理，当预警范围时，则直接产生相关警报，警示外部相关人员，代表此类呼吸幅度明显超出对应的预警范围，存在相关的预警风险，就需要及时处理，此类情况属于特别危级的情况，就发生相关的报警警报，来进行人员警示。The breathing amplitude is calibrated as HXi , where i represents different moments. The breathing amplitude HXi is compared with the preset warning range. When HXi ∈ the warning range, no processing is performed. When the breathing amplitude exceeds the warning range, an alarm will be generated to warn relevant external personnel. This means that the breathing amplitude obviously exceeds the corresponding warning range and there is a relevant warning risk, which needs to be dealt with in time. If the situation is particularly dangerous, a relevant alarm will be issued to warn personnel.
其中，波形生成端，基于不同时刻所产生的相关呼吸幅度，实时生成其呼吸波形变化曲线，并将所生成的呼吸波形变化曲线传输至波形分析端或波形特征判定端内，其中，实时生成其呼吸波形变化曲线的具体方式包括：The waveform generating end generates a breathing waveform change curve in real time based on the relevant breathing amplitudes generated at different times, and transmits the generated breathing waveform change curve to the waveform analyzing end or the waveform feature determining end. The specific method of generating the breathing waveform change curve in real time includes:
基于不同时刻所产生的不同相关呼吸幅度，以时间线为横向坐标轴，以对应不同时刻所对应的呼吸幅度作为竖直坐标轴，依据不同时刻所对应的不同数值确定不同的点位，并在二维坐标系内确定其呼吸波形变化曲线，并将所确定的呼吸波形变化曲线传输至波形分析端或波形特征判定端内；Based on the different related breathing amplitudes generated at different moments, the timeline is used as the horizontal coordinate axis, and the breathing amplitudes corresponding to different moments are used as the vertical coordinate axis. Different points are determined according to different values corresponding to different moments, and the breathing waveform change curve is determined in the two-dimensional coordinate system, and the determined breathing waveform change curve is transmitted to the waveform analysis end or the waveform feature determination end;
具体的，不同时刻对应不同的呼吸幅度，便可在二维坐标系内确定对应的点位，再将对应的点位进行互连，确定其相关的呼吸波形变化曲线，其呼吸波形变化曲线便可充分展现其对应新生儿的相关呼吸情况。Specifically, different breathing amplitudes correspond to different moments, and the corresponding points can be determined in the two-dimensional coordinate system. The corresponding points are then interconnected to determine the relevant breathing waveform change curve, which can fully demonstrate the relevant breathing conditions of the corresponding newborn.
其中，波形分析端，基于呼吸波形变化曲线的初始时刻，确定一组识别周期，对此识别周期内所产生的呼吸波形进行分析，来确定本新生儿的相关呼吸特征，并将所确定的相关呼吸特征传输至波形特征判定端内，其中，确定相关呼吸特征的具体方式包括：The waveform analysis end determines a set of identification cycles based on the initial moment of the respiratory waveform change curve, analyzes the respiratory waveform generated in the identification cycle to determine the relevant respiratory characteristics of the newborn, and transmits the determined relevant respiratory characteristics to the waveform feature determination end. The specific method of determining the relevant respiratory characteristics includes:
基于初始时刻，往后确定一组识别周期T，其中T为预设值，其具体取值由操作人员根据经验拟定，对本识别周期T内所产生的呼吸波形段进行确认，将所确认的呼吸波形段标定为待定分析段；Based on the initial moment, a set of identification cycles T is determined in the future, where T is a preset value, and its specific value is determined by the operator based on experience. The respiratory waveform segment generated within the current identification cycle T is confirmed, and the confirmed respiratory waveform segment is marked as the pending analysis segment;
依次确认待定分析段内所出现的相关点，其相关点前端线段走向趋势向上，后端线段走向趋势向下，其相关点如图2所示进行确认，对相邻相关点之间的线段特征进行分析，其分析方式为：将相邻相关点对应线段的第一个相关点所对应的呼吸幅度标定为H1，将第二个相关点所对应的呼吸幅度标定为H2，再将两个相关点之间的时间间隔标定为JG，采用FX＝|H1-H2|×C1+JG×C2确定其对应相关点之间的分析值FX，其中C1以及C2均为预设的固定系数因子，其具体取值由操作人员根据经验拟定，再依据从前至后对不同线段的分析值FX进行依次确认，并生成其分析值排序序列{FX1、FX2、……、FXn}；Confirm the related points appearing in the pending analysis segment in sequence, the trend of the front line segment of the related point is upward, and the trend of the rear line segment is downward. The related points are confirmed as shown in FIG2, and the line segment characteristics between adjacent related points are analyzed. The analysis method is as follows: the breathing amplitude corresponding to the first related point of the line segment corresponding to the adjacent related point is calibrated as H1, and the breathing amplitude corresponding to the second related point is calibrated as H2, and then the time interval between the two related points is calibrated as JG, and the analysis value FX between the corresponding related points is determined by FX=|H1-H2|×C1+JG×C2, wherein C1 and C2 are both preset fixed coefficient factors, and their specific values are determined by the operator according to experience, and then the analysis values FX of different line segments are confirmed in sequence from front to back, and the analysis value sorting sequence {FX1, FX2, ..., FXn} is generated;
将分析值排序序列内对应的排序值进行方差处理，优先从第一组分析值FX1开始，逐步往后确认相关的分析值，来确定其方差值Fc，当Fc≤Y1时，其中Y1为预设值，其具体取值由操作人员根据经验拟定，则再次确定后续的分析值，当所确认的方差值Fc＞Y1时，则将所添加的分析值标定为异常值，并将异常值前端的若干组分析值标定为同类值，将同类值所对应的线段标定为同类段，再从异常值开始，往后确认其分析值，并确定其方差值Fc，采用相同的方式，对本待定分析段内所出现的同类段进行依次确认，并将同类段之间的相关线段标定为波动段(其中相关线段不属于同类段)，如图2所示，其圆心到第一组横向虚线之间为一组同类段，第一组横向虚线与第二组横向虚线之间的线段为波动段，其波动情况与前后的线段区别较大，故就属于一个变动的波动段，第二组横向虚线与第三组横向虚线之间为第二组同类段，第三组横向虚线与第四组横向虚线之间为第二组波动段，第四组横向虚线至后续结尾段为同类段；The corresponding sorted values in the sorted sequence of the analysis values are processed with variance, starting with the first group of analysis values FX1, and then confirming the related analysis values step by step to determine their variance values Fc. When Fc≤Y1, where Y1 is a preset value, and its specific value is determined by the operator based on experience, the subsequent analysis values are determined again. When the confirmed variance value Fc＞Y1, the added analysis value is marked as an abnormal value, and several groups of analysis values at the front of the abnormal value are marked as similar values, and the line segments corresponding to the similar values are marked as similar segments. Starting from the abnormal value, confirm its analysis value and determine its variance value Fc. The same In this way, the similar segments appearing in the pending analysis segment are confirmed in turn, and the related line segments between the similar segments are marked as fluctuation segments (where the related line segments do not belong to the same segment). As shown in FIG2 , the segment from the center of the circle to the first group of horizontal dotted lines is a group of similar segments, the segment between the first group of horizontal dotted lines and the second group of horizontal dotted lines is a fluctuation segment, and its fluctuation is quite different from the previous and next line segments, so it belongs to a fluctuating segment with a change, the segment between the second group of horizontal dotted lines and the third group of horizontal dotted lines is the second group of similar segments, the segment between the third group of horizontal dotted lines and the fourth group of horizontal dotted lines is the second group of fluctuation segments, and the segment from the fourth group of horizontal dotted lines to the subsequent end is a similar segment;
其数值处理方式可以理解为：其序列为：{1、1.2、2、2.1、2.2、2.1、2.15、0.8、0.75、0.85、0.84、0.82}，其分析值的表现形式如上所示，由此可见，第一组分析值与第二组分析值按照方差处理方式为同类段，当第三组分析值介入此方差处理时，前三组数值所产生的对应方差就偏离来原始的判定方式，那么第三组数值就是异常值，那么第一组以及第二组数值所对应的线段为同类段，第二组数值至第三组数值之间为波动段，第三组数值到第七组数值之间为同类段，后续又可确定一组波动段以及后续相关的同类段，依此类推，便可对后续所出现的同类段以及波动段进行依次确认；Its numerical processing method can be understood as follows: its sequence is: {1, 1.2, 2, 2.1, 2.2, 2.1, 2.15, 0.8, 0.75, 0.85, 0.84, 0.82}, and its analysis value is expressed as shown above. It can be seen that the first group of analysis values and the second group of analysis values are similar segments according to the variance processing method. When the third group of analysis values intervenes in this variance processing, the corresponding variances generated by the first three groups of values deviate from the original judgment method, then the third group of values is an outlier, then the line segments corresponding to the first and second groups of values are similar segments, the second group of values to the third group of values are the fluctuation segments, the third group of values to the seventh group of values are the similar segments, and subsequently a group of fluctuation segments and subsequent related similar segments can be determined, and so on, the subsequent similar segments and fluctuation segments can be confirmed in turn;
基于所确认的同类段以及波动段，从中选取对应分析值的最大值以及最小值，并依据所确认的最大值以及最小值，生成属于同类段的平稳区间，再基于波动段所产生的最大值以及最小值，生成属于波动段的波动区间，并将平稳区间以及波动区间传输至波动特征判定端内；Based on the confirmed similar segments and fluctuating segments, the maximum value and the minimum value of the corresponding analysis value are selected, and based on the confirmed maximum value and the minimum value, a stable interval belonging to the similar segment is generated, and based on the maximum value and the minimum value generated by the fluctuating segment, a fluctuating interval belonging to the fluctuating segment is generated, and the stable interval and the fluctuating interval are transmitted to the fluctuation feature determination end;
具体的，此处根据其对应波形所产生的相关特征，来确定对应新生儿的呼吸变化情况，来确定一个相对的监测区间，基于此监测区间对后续新生儿所产生的呼吸参数来进行判定或预警，以此来提升本智能监护系统的实用性，因每个不同的新生儿均存在不同的呼吸习惯或不同的呼吸特征，若采用统一的评判标准可能会造成数值评判的不及时或不准确，故采用数值监测确定相关线段的方式，依次确定对应的区间，来确定相关的判定信号。Specifically, here, the respiratory changes of the corresponding newborn are determined according to the relevant characteristics generated by the corresponding waveform, and a relative monitoring interval is determined. Based on this monitoring interval, the respiratory parameters generated by the subsequent newborn are judged or warned, so as to improve the practicality of this intelligent monitoring system. Because each newborn has different breathing habits or different breathing characteristics, if a unified evaluation standard is used, it may cause untimely or inaccurate numerical evaluation. Therefore, the method of determining the relevant line segments by numerical monitoring is adopted, and the corresponding intervals are determined in turn to determine the relevant judgment signals.
其中，波动特征判定端，对识别周期T后所产生的呼吸波形变化曲线进行数值分析，确定相应的波动特征，将所确定的波动特征与相关的特征区间进行比对，基于比对结果，生成不同的处理信号，其中，进行比对的具体方式包括：The fluctuation feature determination end performs numerical analysis on the respiratory waveform change curve generated after the identification period T, determines the corresponding fluctuation feature, compares the determined fluctuation feature with the relevant feature interval, and generates different processing signals based on the comparison result. The specific method of performing the comparison includes:
其中特征区间包括波动区间和平稳区间，再对识别周期T后对应呼吸波形变化曲线后续所产生的分析值Fk进行确认，并确认所产生的分析值Fk的所属区间，其中k代表后续不同相关点之间的线段；The characteristic interval includes a fluctuation interval and a stable interval, and then the analysis value Fk generated by the corresponding respiratory waveform change curve after the identification period T is confirmed, and the interval to which the generated analysis value Fk belongs is confirmed, where k represents the line segment between different subsequent related points;
当Fk∈平稳区间时，产生平稳信号并通过展示端展示；When Fk ∈ stable interval, a stable signal is generated and displayed through the display terminal;
当Fk∈波动区间时，产生波动信号并通过展示端展示；When Fk ∈ the fluctuation interval, a fluctuation signal is generated and displayed through the display terminal;
当平稳区间＜Fk＜波动区间时，产生介入信号，并通过展示端展示，外部医护人员基于此介入信号，判定是否需要将此部分分析值Fk填补至波动区间内，来扩大对应波动区间的相应范围，其判定范围是否需要扩大由外部医护人员自行确定；When the stable interval < Fk < the fluctuation interval, an intervention signal is generated and displayed through the display terminal. Based on this intervention signal, external medical staff determine whether it is necessary to fill this part of the analysis value Fk into the fluctuation interval to expand the corresponding range of the corresponding fluctuation interval. Whether the determination range needs to be expanded is determined by the external medical staff.
进行比对的具体方式还包括：The specific methods of comparison also include:
当Fk＜平稳区间时，将本时刻所出现的分析值标定为异常值，并对后续连续出现的五组分析值进行确定，并将所确定的分析值排序为：F1、F2、F3、F4、F5以及F6，其中F1为本时刻所标定的异常值，在所确定的分析值排序序列中，当后一组分析值小于前一组分析值，则产生一组赋值“-1”，若后一组分析值不小于前一组分析值，则产生一组赋值“0”，例：当F2＜F1时，产生一组赋值-1，F3＜F2时，产生一组赋值-1，依此类推，对所产生的赋值序列进行确定，确定赋值序列；When Fk < stable interval, the analysis value appearing at this moment is marked as an abnormal value, and the five groups of analysis values appearing successively are determined, and the determined analysis values are sorted as: F1, F2, F3, F4, F5 and F6, where F1 is the abnormal value marked at this moment. In the determined analysis value sorting sequence, when the latter group of analysis values is less than the former group of analysis values, a group of assignments "-1" is generated, and if the latter group of analysis values is not less than the former group of analysis values, a group of assignments "0" is generated. For example, when F2 < F1, a group of assignments -1 is generated, and when F3 < F2, a group of assignments -1 is generated, and so on. The generated assignment sequence is determined to determine the assignment sequence;
当Fk＞波动区间时，将本时刻所出现的分析值标定为异常值，并对后续连续出现的五组分析值进行确定，并将所确定的分析值排序为：B1、B2、B3、B4、B5以及B6，其中B1为本时刻所标定的异常值，在所确定的分析值排序序列中，当后一组分析值大于前一组分析值，则产生一组赋值“1”，若后一组分析值不大于前一组分析值，则产生一组赋值“0”；When Fk > fluctuation range, the analysis value appearing at this moment is marked as an abnormal value, and the five groups of analysis values appearing successively are determined, and the determined analysis values are sorted as: B1, B2, B3, B4, B5 and B6, where B1 is the abnormal value marked at this moment. In the determined analysis value sorting sequence, when the latter group of analysis values is greater than the former group of analysis values, a group of assignments "1" is generated; if the latter group of analysis values is not greater than the former group of analysis values, a group of assignments "0" is generated;
基于所产生的赋值序列确定赋值总和，再锁定赋值总和的绝对值JD，若JD≥Y2，其中Y2为预设值，其具体取值由操作人员根据经验拟定，则直接生成预警信号，且控制预警端直接产生相关警报，警示外部相关人员，反之，则继续监视比对；Determine the total value of the generated value sequence, and then lock the absolute value JD of the total value of the value. If JD≥Y2, where Y2 is a preset value, and its specific value is determined by the operator based on experience, then directly generate an early warning signal, and the control early warning terminal directly generates a relevant alarm to warn relevant external personnel. Otherwise, continue to monitor and compare;
具体的，此种情况，代表对应的呼吸幅度变化的较为剧烈，要么就是呼吸幅度越来越大，要么就是呼吸幅度越来越低，均处于不正常的变化情况，就需要及时预警，使医护人员及时介入，便可保障其对应新生儿的安全。Specifically, this situation means that the corresponding breathing amplitude changes more dramatically, either the breathing amplitude is getting larger or smaller, both of which are abnormal changes. Timely warnings are needed so that medical staff can intervene in time to ensure the safety of the corresponding newborns.
实施例二Embodiment 2
本实施例作为实施一的进一步实施例，与实施例的不同点在于，本实施例还包括更进步的确定方式，主要针对于Fk＜平稳区间或Fk＞波动区间的情况，其具体内容如下：This embodiment is a further embodiment of the first embodiment. The difference from the first embodiment is that this embodiment also includes a more advanced determination method, mainly for the case where Fk <stable interval or Fk >fluctuation interval. The specific content is as follows:
进行比对的具体方式还包括：The specific methods of comparison also include:
当Fk＜平稳区间时，锁定相关的分析值排序序列，将后一组分析值标定为Fh，将前一组分析值标定为Fq(其中前一组分析值是相对于后一组分析值的前一组参数，如F1、F2、F3、F4、F5以及F6，F1是F2的前一组分析值，F2是F1的后一组分析值，其F2为F3的前一组分析值，F3为F2的后一组分析值，依此类推)，当(Fq÷2)＜Fh＜Fq，则产生一组赋值“-1”，当Fh≤(Fq÷2)时，则产生一组赋值“-2”，反之，则产生赋值“0”，确定赋值序列；When Fk < stable interval, lock the related analysis value sorting sequence, mark the next group of analysis values as Fh, mark the previous group of analysis values as Fq (where the previous group of analysis values is the previous group of parameters relative to the next group of analysis values, such as F1, F2, F3, F4, F5 and F6, F1 is the previous group of analysis values of F2, F2 is the next group of analysis values of F1, F2 is the previous group of analysis values of F3, F3 is the next group of analysis values of F2, and so on), when (Fq÷2)＜Fh＜Fq, a group of assignments "-1" is generated, when Fh≤(Fq÷2), a group of assignments "-2" is generated, otherwise, an assignment "0" is generated, and the assignment sequence is determined;
当Fk＞波动区间时，锁定相关的分析值排序序列，将后一组分析值标定为Bh，将前一组分析值标定为Bq，当2Bq＞Bh＞Bq，则产生一组赋值“1”，当Bh≥2Bq时，则产生一组赋值“2”，反之，则产生赋值“0”，确定赋值序列；When Fk > fluctuation range, lock the related analysis value sorting sequence, mark the latter group of analysis values as Bh, and mark the former group of analysis values as Bq. When 2Bq>Bh>Bq, a group of assignments "1" is generated. When Bh≥2Bq, a group of assignments "2" is generated. Otherwise, an assignment "0" is generated to determine the assignment sequence.
基于所产生的赋值序列确定赋值总和，再锁定赋值总和的绝对值JD，若JD≥Y2，其中Y2为预设值，其具体取值由操作人员根据经验拟定，则直接生成预警信号，且控制预警端直接产生相关警报，警示外部相关人员，反之，则继续监视比对；Determine the total value of the generated value sequence, and then lock the absolute value JD of the total value of the value. If JD≥Y2, where Y2 is a preset value, and its specific value is determined by the operator based on experience, then directly generate an early warning signal, and the control early warning terminal directly generates a relevant alarm to warn relevant external personnel. Otherwise, continue to monitor and compare;
具体的，此处之所以在实施例一的基础上，增加赋值2，因按照实施例1的相关比对方式，某一处变化幅度较大或变化幅度较小时，均是产生对应的赋值1，不足以展示其变化幅度的变化情况，其变化幅度越大，所产生的赋值应该越大，才能更加明显的体现异常情况，故实施例二的确定方式比实施例一的确定方式更为精准，所产生的预警信号更为提前，能达到更好的警示效果，从而保障本监护系统的监护效果。Specifically, the reason why the assignment 2 is added here on the basis of Example 1 is that according to the relevant comparison method of Example 1, when the change amplitude at a certain place is large or small, the corresponding assignment 1 is generated, which is not enough to show the change of its change amplitude. The larger the change amplitude, the larger the generated assignment should be, so that the abnormal situation can be more obviously reflected. Therefore, the determination method of Example 2 is more accurate than the determination method of Example 1, and the early warning signal generated is earlier, which can achieve better warning effect, thereby ensuring the monitoring effect of this monitoring system.
上述公式中的部分数据均是去其纲量进行数值计算，同时本说明书中未作详细描述的内容均属于本领域技术人员公知的现有技术。Some of the data in the above formulas are numerically calculated by removing their dimensions. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.
以上实施例仅用以说明本发明的技术方法而非限制，尽管参照较佳实施例对本发明进行了详细说明，本领域的普通技术人员应当理解，可以对本发明的技术方法进行修改或等同替换，而不脱离本发明技术方法的精神和范围。The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.
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| US20070135726A1 (en)* | 2005-12-08 | 2007-06-14 | Shenzhen Mindray Bio-Medical Electronics Co., Ltd. | Method for improving recognition rate of respiratory wave |
| US20130197386A1 (en)* | 2012-01-31 | 2013-08-01 | Medtronic, Inc. | Respiratory function detection |
| WO2015100909A1 (en)* | 2013-12-31 | 2015-07-09 | 深圳迈瑞生物医疗电子股份有限公司 | Monitor and method and device for automatically switching signals of a plurality of leads thereof |
| US20180110463A1 (en)* | 2015-05-04 | 2018-04-26 | Sealand Technology (Chengdu) Limited | Bio-impedence-based sleep breathing state signal acquisition device and monitoring system |
| JP2018130513A (en)* | 2017-02-15 | 2018-08-23 | 修 池田 | Respiration component extraction method |
| EP3695776A1 (en)* | 2019-02-13 | 2020-08-19 | Koninklijke Philips N.V. | A method and system for generating a respiration instability signal |
| CN112971743A (en)* | 2021-02-08 | 2021-06-18 | 南京泓鼎感知技术有限责任公司 | Non-contact neonatal respiration monitoring system, device and storage medium |
| CN113347917A (en)* | 2019-01-29 | 2021-09-03 | 皇家飞利浦有限公司 | Method and system for generating a respiratory alert |
| CN115089164A (en)* | 2022-06-23 | 2022-09-23 | 北京清雷科技有限公司 | Method, device and storage medium for extracting respiratory rate variability data |
| CN115517653A (en)* | 2022-08-18 | 2022-12-27 | 江苏人先医疗科技有限公司 | Respiration monitoring method, respiration monitor and storage medium |
| US20230095345A1 (en)* | 2021-09-30 | 2023-03-30 | Covidien Lp | Non-contact systems and methods for monitoring and addressing breathing events in neonates |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4365636A (en)* | 1981-06-19 | 1982-12-28 | Medicon, Inc. | Method of monitoring patient respiration and predicting apnea therefrom |
| US20070135726A1 (en)* | 2005-12-08 | 2007-06-14 | Shenzhen Mindray Bio-Medical Electronics Co., Ltd. | Method for improving recognition rate of respiratory wave |
| US20130197386A1 (en)* | 2012-01-31 | 2013-08-01 | Medtronic, Inc. | Respiratory function detection |
| WO2015100909A1 (en)* | 2013-12-31 | 2015-07-09 | 深圳迈瑞生物医疗电子股份有限公司 | Monitor and method and device for automatically switching signals of a plurality of leads thereof |
| US20180110463A1 (en)* | 2015-05-04 | 2018-04-26 | Sealand Technology (Chengdu) Limited | Bio-impedence-based sleep breathing state signal acquisition device and monitoring system |
| JP2018130513A (en)* | 2017-02-15 | 2018-08-23 | 修 池田 | Respiration component extraction method |
| CN113347917A (en)* | 2019-01-29 | 2021-09-03 | 皇家飞利浦有限公司 | Method and system for generating a respiratory alert |
| EP3695776A1 (en)* | 2019-02-13 | 2020-08-19 | Koninklijke Philips N.V. | A method and system for generating a respiration instability signal |
| CN112971743A (en)* | 2021-02-08 | 2021-06-18 | 南京泓鼎感知技术有限责任公司 | Non-contact neonatal respiration monitoring system, device and storage medium |
| US20230095345A1 (en)* | 2021-09-30 | 2023-03-30 | Covidien Lp | Non-contact systems and methods for monitoring and addressing breathing events in neonates |
| CN115089164A (en)* | 2022-06-23 | 2022-09-23 | 北京清雷科技有限公司 | Method, device and storage medium for extracting respiratory rate variability data |
| CN115517653A (en)* | 2022-08-18 | 2022-12-27 | 江苏人先医疗科技有限公司 | Respiration monitoring method, respiration monitor and storage medium |
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| CN118553427A (en)* | 2024-07-26 | 2024-08-27 | 苏州工业园区东诚智能网络技术有限公司 | A rehabilitation process tracking method and system |
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