CN116158751A - Dyspnea sensing measurement method, system, storage medium and measurement instrument - Google Patents

Dyspnea sensing measurement method, system, storage medium and measurement instrument Download PDF

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CN116158751A
CN116158751A CN202211531184.5A CN202211531184A CN116158751A CN 116158751 A CN116158751 A CN 116158751A CN 202211531184 A CN202211531184 A CN 202211531184A CN 116158751 A CN116158751 A CN 116158751A
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resistance
dyspnea
breathing
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sensing
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黄克武
宋杰
尹茜
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Beijing Chaoyang Hospital
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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Abstract

The invention discloses a method for measuring dyspnea perception a system, a storage medium and a dyspnea sensing tester, a method for determining dyspnea perception comprising the steps of: collecting dyspnea sensing data in a load resistance breathing test, the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person; constructing a resistance load breathing model according to the dyspnea sensing data; personal information of the detected person is input to the resistance load breathing model, obtaining a matched load resistance breathing mode; and acquiring dyspnea sensing information of the detected person by adopting the matched load resistance breathing mode. According to the method for measuring dyspnea sensing of the embodiment of the invention, according to the personal information of the detected person, the load resistance breathing mode corresponding to the detected person is matched, so that the dyspnea sensing information of the detected person is rapidly and accurately obtained.

Description

Dyspnea sensing measurement method, system, storage medium and measurement instrument
Technical Field
The invention belongs to the technical fields of software engineering, big data, distributed storage, calculation and the like, and particularly relates to a dyspnea sensing measurement method, a dyspnea sensing measurement system, a storage medium and a dyspnea sensing measurement instrument.
Background
Dyspnea is a common and afflicting symptom of heart lung and neuromuscular disease, sensory information from the respiratory system activates cortical areas of the brain, creating a sensation of dyspnea. The degree of dyspnea is determined by the subjective experience of the individual, and the evaluation of the degree of dyspnea depends on the individual's perception of dyspnea (Perception of dyspnea, POD). The perception of dyspnea may affect the judgment of the condition of the patient to be examined who is suffering from such diseases as heart lung and nervous system. If the detected person senses the dyspnea slowly, the symptom change can not be found in time, and diagnosis and treatment are possibly insufficient or untimely, or serious acute exacerbation occurs; dyspnea oversensing may result in frequent medical visits and overdose.
Dyspnea requires quantification as well as other sensations of pain, and various laboratory methods are currently developed to assess the perception of dyspnea. These methods are all performed on different levels of stimulation by the subject, who uses different numbers or scales for testing based on the perceived stimulation level.
Although the measurement modes of dyspnea sensing in industry are various, various measurement methods have no unified standard, and whether different measurement methods are suitable for different testees or not has no clear standard, the testees can only judge the dyspnea sensing degree of the testees according to industry experience, and when the judgment is carried out, a large error exists, so that the requirement of accurately measuring the dyspnea sensing degree of the testees is difficult to achieve.
Disclosure of Invention
In view of the above, the invention provides a dyspnea sensing measurement method, a system, a storage medium and a dyspnea sensing measurement instrument, which can be matched with a proper detection method according to different conditions of a person to be detected to measure dyspnea sensing, and effectively ensure the measurement efficiency and accuracy of dyspnea sensing.
In order to solve the technical problems, in one aspect, the invention provides a method for measuring dyspnea sensing, comprising the following steps: collecting dyspnea sensing data in various load resistance breathing tests, wherein the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person; constructing a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises a plurality of load resistance breathing modes; inputting personal information of a detected person into the resistance load breathing model, and matching the corresponding load resistance breathing mode according to the personal information of the detected person; acquiring detection data of the detected person by adopting the matched load resistance breathing mode; and calculating dyspnea sensing information of the detected person according to the matched load resistance breathing mode and the detection data.
According to one embodiment of the present invention, the resistance information includes: at least one of a resistance loading mode, a resistance value, a resistance rising mode, and a resistance occurrence sequence.
According to one embodiment of the invention, the resistance loading mode includes at least one of an inhalation resistance mode, an exhalation resistance mode, and a respiratory diphasic resistance mode.
According to one embodiment of the invention, the resistance value is set in the form of specific data or in the form of a percentage of maximum respiratory muscle force when the resistance value is set.
According to one embodiment of the present invention, when the resistance-increasing mode is set, a manual resistance setting mode or a random resistance mode is adopted.
According to one embodiment of the invention, the evaluation information of the detected person adopts a direct scoring mode or an indirect scoring mode, wherein a VAS scale or a Borg scale is adopted in the direct scoring mode, and the evaluation information is obtained according to a respiratory muscle strength measurement result in the indirect scoring mode.
According to one embodiment of the invention, the personal information includes at least one of gender, birth date, height, weight, and disease information.
In a second aspect, embodiments of the present invention provide an assay system for dyspnea sensing comprising: the information acquisition module can acquire dyspnea sensing data in various load resistance breathing tests, wherein the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person; the model construction module is used for constructing a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises a plurality of load resistance breathing modes; the input module can input personal information of a detected person to the resistance load breathing model; the matching module is used for matching the corresponding load resistance breathing mode from the resistance load breathing model according to the personal information of the detected person; the detection module is used for acquiring detection data of the detected person and calculating dyspnea sensing information of the detected person according to the detection data.
In a third aspect, embodiments of the present invention provide a computer storage medium comprising one or more computer instructions which, when executed, implement a method as described in any of the preceding claims.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including a memory for storing one or more computer instructions and a processor for invoking and executing the one or more computer instructions to implement a method as described in any preceding claim.
According to the method for measuring dyspnea sensing, provided by the embodiment of the invention, the load resistance breathing model containing a plurality of measuring methods is generated by collecting the measuring data of a plurality of measuring methods in advance, and when a detected person is detected, the matched load resistance breathing model can be selected to detect the detected person according to the actual situation of the detected person or the requirements of clinical research, so that the dyspnea sensing data of the detected person can be quickly and accurately obtained.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flow chart of a method of determining dyspnea sensing according to an embodiment of the invention;
FIG. 2 is a flow chart of a method of determining dyspnea sensing according to yet another embodiment of the invention;
FIG. 3 is a schematic representation of the Borg scale;
FIG. 4 is a schematic representation of a VAS scale;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the invention.
Reference numerals:
an electronic device 300;
a memory 310; an operating system 311; an application 312;
a processor 320; a network interface 330; an input device 340; a hard disk 350; and a display device 360.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
In the description of the present 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", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, features defining "first", "second" may include one or more such features, either explicitly or implicitly. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
A method for determining dyspnea sensing according to an embodiment of the invention will be described in detail with reference to the accompanying drawings.
As shown in fig. 1 and 2, the method for measuring dyspnea sensing according to an embodiment of the invention comprises the following steps:
and collecting dyspnea sensing data in various load resistance breathing tests, wherein the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person.
And constructing a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises a plurality of load resistance breathing modes.
And inputting personal information of the detected person into the resistance load breathing model, and matching the corresponding load resistance breathing mode according to the personal information of the detected person.
And acquiring detection data of the detected person by adopting the matched load resistance breathing mode.
And calculating dyspnea sensing information of the detected person according to the matched load resistance breathing mode and the detection data.
In other words, before the detection of the person to be detected, the method for detecting dyspnea sensing according to the embodiment of the present invention needs to collect the dyspnea sensing data in various load resistance breathing tests, for example, personal information of the person to be detected, resistance information input by the person to be detected during the detection, and person to be detected evaluation information obtained by the person to be detected under the corresponding resistance information, that is, the dyspnea sensing data of the person to be detected, and so on, and collect and store these data in a suitable storage medium.
When sample data is collected, a certain respiratory resistance can be set for a test instrument for detecting dyspnea sensing, so that a person to be detected breathes under the resistance, and the person to be detected generates a dyspnea sensing, which is a test method for simulating a dyspnea laborious sensing in the dyspnea sensing. In resistance-loaded breathing, the subject's inspiratory (or expiratory) gases activate the chest and neck muscles, subjecting them to great pressure, and thus a mismatch in respiratory muscle oxygenation and utilization occurs, thereby causing the subject to experience a feeling of dyspnea. At present, a plurality of methods for detecting dyspnea sensing exist, and the common detection methods are as follows according to different dyspnea sensing detection instruments and dyspnea gauges:
in the first method, the ascending order of the inspiratory resistance load of the breath measuring instrument is regulated to be 0, 5, 10, 20 and 30cm of water, the first two breaths of each gear are the detection of the non-resistance respiration, and the last four breaths are used for setting the ascending order of 25%,50%,75% and 100% of the resistance load. Each resistance takes 6 effective breaths, and the rest time is 1 minute between the two resistances. The Borg breath was used immediately at a rest time of 1 minute the dyspnea scale scores dyspnea sensations.
Method 2, the ascending order of the inspiratory resistance load of the breath test apparatus was adjusted to be 0, 10%, 20%, 30% MIP (maximum inspiratory muscle force), respectively. Each stage of the resistance increasing respiration is 6 times, and the two stages of the resistance have a rest for 1 minute. Dyspnea sensations were scored immediately at rest time of 1 minute using the Borg dyspnea scale.
Method 3, inspiratory resistance loads of 0, 5, 10, 20 and 30cmH2O of the breath measuring apparatus were adjusted to randomly appear, and each constant resistance was breathed for 1 minute, and rest for 1 minute between the two resistances. Dyspnea sensations were scored immediately at rest time of 1 minute using the Borg dyspnea scale.
Method 4, the inspiratory resistance load of the breath-measuring apparatus was adjusted to randomly appear as 0, 10%, 20%, 30% MIP (maximum inspiratory muscle force), each constant resistance breathes for 1 minute, and the two resistance steps rest for 1 minute. Dyspnea sensations were scored immediately at rest time of 1 minute using the Borg dyspnea scale.
After the relevant data of a plurality of dyspnea measurement methods are collected, modeling and calculating the relevant information of the dyspnea sensing data to obtain a resistance load breathing model comprising a plurality of resistance load breathing modes, wherein each resistance load breathing mode respectively comprises personal information of a detected person and measurement data corresponding to the detected person, and corresponding relational expression or relational function is obtained according to the personal information of the detected person and the measurement data corresponding to the detected person.
After the resistive load breathing model is constructed, the model can be used for detecting the person to be detected. When the resistance load breathing model is used for detecting a detected person, personal information of the detected person can be input into the resistance load breathing model, and the resistance load breathing model can be matched with resistance load breathing modes corresponding to the personal information of the detected person according to the personal information of the detected person, wherein different resistance load breathing modes have different resistance adjusting mechanisms.
Then, the detection data of the detected person can be obtained according to the resistance load breathing mode matched with the resistance load breathing model, namely, the detected person can feed back corresponding parameters according to the resistance load breathing mode set by the detection instrument, and the resistance load breathing model can calculate dyspnea sensing information corresponding to the parameters according to the corresponding resistance load breathing mode.
Therefore, according to the method for measuring dyspnea sensing, provided by the embodiment of the invention, by collecting measurement data of a plurality of measurement methods in advance and generating the load resistance breathing model comprising the plurality of measurement methods, when a detected person is detected, the matched load resistance breathing model can be selected to detect the detected person according to the actual condition of the detected person or the requirement of clinical research, so that the dyspnea sensing data of the detected person can be quickly and accurately obtained.
According to one embodiment of the present invention, the resistance information includes: at least one of a resistance loading mode, a resistance value, a resistance rising mode and a resistance appearance sequence, resistance information can be correspondingly adjusted according to different dyspnea measuring instruments, and the comprehensive collection of detection data of different detected persons is improved by setting different resistance information, so that the accuracy of dyspnea sensing information of the detected persons is improved.
In some embodiments of the invention, the resistive loading mode includes at least one of an inhalation resistive mode, an exhalation resistive mode, and a respiratory biphasic resistive mode. That is, in the load resistance breath test, a plurality of mode settings may be selected, for example, an inhalation resistance mode, an exhalation resistance mode, or a respiratory diphasic resistance mode may be selected for the load test.
According to one embodiment of the invention, when setting the resistance value, the resistance value is set in the form of specific data or in the form of a percentage of maximum respiratory muscle force. Wherein the adjustable range of respiratory resistance is 0-100 cmH 2 O, a fixed numerical resistance, or a fixed MIP (MEP) percent resistance, may be selected.
In some embodiments of the present invention, the resistance-increasing mode is set manually or by random resistance. For example, when the resistance-increase mode is selected, both constant resistance and incremental-increase resistance modes may be selected. The order of occurrence of the resistances may be ascending in ascending order from small to large in the set resistances, or the set resistances may occur in random order.
According to one embodiment of the invention, the evaluation information of the detected person adopts a direct scoring mode or an indirect scoring mode. Among them, a VAS (visual analog) scale or a Borg scale is used in the direct scoring method, that is, after resistance-load breathing is performed, the feeling of dyspnea needs to be evaluated. Wherein, visual analog quantity is adopted in the evaluation methodThe scale (VAS) and the Borg dyspnea score scale are widely applied, and the dyspnea perception of a detected person can be quantified through scale scoring. Specifically, as shown in fig. 3, the Borg scale may set the following problems: "do you feel dyspnea now? Please note the most conforming numbers in the table below. 0 represents no dyspnea or fatigue at all, 10 represents dyspnea or fatigue severe to extreme ", and is asked once after each resistance breath, e.g. at 5cmH 2 O、10cmH 2 O、20cmH 2 O、30cmH 2 O, etc. As shown in FIG. 4, the VAS scale is composed of a horizontal line 10cm long, and the descriptions of the severity of dyspnea are arranged at different positions on the line, and the distance between one end of the scale (no dyspnea end) and the mark point of the tested person is measured to represent the score of dyspnea of the tested person. Wherein, 0cm:0 minutes, no dyspnea; 1cm-3cm:1 minute to 3 minutes, slight dyspnea does not affect work and life; 4cm-6cm: 4-6 minutes, moderate dyspnea, work influence, and life influence are avoided; 7cm-10cm: 7-10 minutes, severe dyspnea, severe pain, and influence on work and life.
In the indirect scoring method, evaluation information is obtained based on the respiratory muscle strength measurement result. Specifically, on the evaluation scale, two methods of the VAS scale and the Borg scale can be selected. The measurement may be displayed directly as a scale score or as a mean of scores, or as a linear equation: the slope of linear regression between the dyspnea score calculated by Borg (VAS) =y+a% MIP (MEP) and the percentage of maximum inspiratory (or expiratory) muscle force set for inspiratory (or expiratory) resistance. Wherein MIP is maximum inspiratory muscle strength, MEP is maximum expiratory muscle strength, the percentage of inspiratory (or expiratory) resistance to the maximum inspiratory (or expiratory) muscle strength is set as an independent variable by a statistical method of linear regression among SPSS 25.0 software, the Borg (VAS) dyspnea score is a dependent variable, and a slope a representing the sensitivity of the subject to the perception of changes in external respiratory resistance and an intercept y representing the underlying dyspnea condition of the subject are calculated.
Optionally, when resistance load breathes, can adopt automatic timing and intelligent voice prompt mode, have easy and simple to handle, intelligence, be favorable to guaranteeing advantages such as accuracy of grading.
Optionally, the method for measuring dyspnea sensing further comprises a data storage step, wherein data such as an expiration flow rate, an inspiration flow rate, an expiration volume, an inspiration volume and the like when the detected person performs resistance load respiration can be stored, so that the method can serve both clinic and scientific research, and has the advantages of convenience, time saving and flexibility in the aspect of testing of dyspnea sensing.
In some embodiments of the invention, the personal information includes at least one of gender, date of birth, height, weight, and disease information. The method for measuring the dyspnea sensing of the invention can be used for the detected patients with diseases such as heart lung, nervous system and the like, and can also be applied to healthy people, thereby expanding the group of the dyspnea sensing, realizing the acquisition of related data of the dyspnea sensing of large-scale people and expanding the data set for constructing a resistance load breathing model.
Therefore, by calculating the personal information of the detected person and the detection data, the correlation between the personal information of the detected person and the detection data can be found, so that the resistance load breathing mode matched with the detected person can be quickly and accurately selected according to the personal information of the detected person, and the accuracy of dyspnea sensing detection of the detected person is improved.
In some embodiments of the invention, the resistance information is obtained by a dynamically variable airflow resistance instrument. That is, the existing apparatus for testing dyspnea can be used to perform a clinical load resistance breathing test to measure dyspnea perception. In the embodiment, the device for testing the dyspnea has the advantages of being convenient to carry, convenient to operate beside a sickbed and the like by combining with the existing device for testing the dyspnea.
The existing instrument for testing dyspnea can be a dynamic variable airflow resistance instrument, the area of a variable flow hole of a breathing valve of the instrument is changed in one breath according to the breathing flow rate, and the controllable variable can be pressure or breathing flow rate. When in operation, the MCU processor of the instrument commands the motor to drive the gear to enlarge or reduce the area of the threshold door to the corresponding impedance position, so that the resistance can be overcome by acting when re-inhaling, and the purpose of applying the inhalation resistance load is achieved. In the present invention, either a fixed resistance value or a fixed percentage of the maximum inhalation/exhalation muscle force resistance may be set.
The invention provides a dyspnea sensing measurement system which comprises an information acquisition module, a model building module, an input module, a matching module and a detection module. The instrument comprising the dyspnea sensing measurement system may be a dyspnea sensing measurement instrument.
Specifically, the information acquisition module can acquire dyspnea sensing data in a load resistance breathing test, the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person, and the model construction module constructs a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises various resistance load breathing modes. The input module can input personal information of a detected person to the resistance load breathing model, the matching module matches a corresponding load resistance breathing mode from the resistance load breathing model according to the personal information of the detected person, and the detection module can be used for acquiring detection data of the detected person and calculating dyspnea sensing information of the detected person according to the detection data.
The following describes in detail a measurement system for collecting dyspnea sensing data in a load resistance breath test in connection with specific embodiments.
Before a person to be detected is detected, the dyspnea sensing system according to the embodiment of the invention needs to collect dyspnea sensing data in various load resistance breathing tests, for example, personal information of the person to be detected, resistance information input by the person to be detected during detection, and person to be detected evaluation information obtained by the person to be detected under corresponding resistance information, namely, dyspnea sensing data of the person to be detected, and the like, and collect and store the data in a suitable storage medium.
After obtaining the related data of a plurality of dyspnea measurement methods, the model construction module models and calculates the related information of the dyspnea sensing data to obtain a resistance load breathing model containing a plurality of resistance load breathing modes, wherein each resistance load breathing mode respectively contains the personal information of the detected person and the measurement data corresponding to the detected person, and obtains a corresponding relational expression or a relational function according to the personal information of the detected person and the measurement data corresponding to the detected person.
The input module can be a plurality of carriers with input functions, such as a tablet computer, a mobile phone, a computer and other devices, and can input relevant personal information of a detected person. The operator inputs personal information of the detected person by the system operation end, wherein the personal information comprises basic information such as gender, birth date, height, weight, disease information and the like. The matching module can match the resistance load breathing modes corresponding to the personal information of the detected person according to the personal information of the detected person, and different resistance load breathing modes have different resistance adjustment mechanisms.
And when the detection module detects, the detection module enters a respiratory muscle strength measurement program according to the matched resistance load respiratory mode, and the maximum respiratory muscle strength is measured. The resistance load breathing mode is then selected, the options including: the drag loading mode, drag ramp mode, drag occurrence sequence, fixed numerical drag, or fixed MIP (MEP) percent drag are selected. The display form of dyspnea perception can be selected in the evaluation scale.
Clicking to start a test after selection, carrying out resistance load respiration by a tested person by holding the terminal, resting for 1 minute after each resistance respiration, displaying time countdown by the operation end, displaying a grading scale by the terminal, grading the feeling of just dyspnea by an intelligent voice prompt, and grading by clicking a scale option by the tested person.
Finally, after the test is completed according to the previous setting, the test is ended by clicking, and the terminal can generate a parameter report of each resistance load respiration and finally calculate the perceived value of the dyspnea.
Therefore, according to the dyspnea sensing system, the load resistance breathing model comprising a plurality of measuring methods is generated by collecting the measuring data of the plurality of measuring methods in advance, and when a detected person is detected, the matched load resistance breathing model can be selected according to the actual condition of the detected person or the requirement of clinical research to detect the detected person, so that the dyspnea sensing data of the detected person can be rapidly and accurately obtained.
In addition, the embodiment of the invention also provides a computer storage medium, which comprises one or more computer instructions, wherein the one or more computer instructions realize the dyspnea sensing measurement method when executed.
That is, the computer storage medium stores a computer program which, when executed by a processor, causing the processor to perform the method of determining dyspnea perception of any of the above.
As shown in fig. 5, an embodiment of the present invention provides an electronic device 300, including a memory 310 and a processor 320, where the memory 310 is configured to store one or more computer instructions, and the processor 320 is configured to invoke and execute the one or more computer instructions, thereby implementing any of the methods described above.
That is, the electronic device 300 includes: a processor 320 and a memory 310, in which memory 310 computer program instructions are stored which, when executed by the processor, cause the processor 320 to perform any of the methods described above.
Further, as shown in fig. 5, the electronic device 300 also includes a network interface 330, an input device 340, a hard disk 350, and a display device 360.
The interfaces and devices described above may be interconnected by a bus architecture. The bus architecture may be a bus and bridge that may include any number of interconnects. One or more Central Processing Units (CPUs), represented in particular by processor 320, and various circuits of one or more memories, represented by memory 310, are connected together. The bus architecture may also connect various other circuits together, such as peripheral devices, voltage regulators, and power management circuits. It is understood that a bus architecture is used to enable connected communications between these components. The bus architecture includes, in addition to a data bus, a power bus, a control bus, and a status signal bus, all of which are well known in the art and therefore will not be described in detail herein.
The network interface 330 may be connected to a network (e.g., the internet, a local area network, etc.), and may obtain relevant data from the network and store the relevant data in the hard disk 350.
The input device 340 may receive various instructions entered by an operator, and to processor 320 for execution. The input device 340 may include a keyboard or pointing device (e.g., a mouse, a trackball, a touch pad, or a touch screen, among others).
The display device 360 may display results obtained by the processor 320 executing instructions.
The memory 310 is used for storing programs and data necessary for the operation of the operating system, and data such as intermediate results in the calculation process of the processor 320.
It will be appreciated that memory 310 in embodiments of the invention may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be Read Only Memory (ROM), programmable Read Only Memory (PROM), erasable Programmable Read Only Memory (EPROM), electrically Erasable Programmable Read Only Memory (EEPROM), or flash memory, among others. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. The memory 310 of the apparatus and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some implementations, the memory 310 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system 311 and applications 312.
The operating system 311 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application programs 312, including various application programs, such as a Browser (Browser) or the like, for implementing various application services. A program implementing the method of the embodiment of the present invention may be included in the application program 312.
The processor 320, when calling and executing the application program and the data stored in the memory 310, specifically, the program or the instruction stored in the application program 312, sends one of the first set and the second set to the node distributed by the other one of the first set and the second set, wherein the other one is stored in at least two nodes in a scattered manner; and performing intersection processing in a node-by-node manner according to the node distribution of the first set and the node distribution of the second set.
The method disclosed in the above embodiment of the present invention may be applied to the processor 320 or implemented by the processor 320. Processor 320 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 320. The processor 320 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, or discrete hardware components, which may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 310 and the processor 320 reads the information in the memory 310 and in combination with its hardware performs the steps of the method described above.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
In particular, the processor 320 is further configured to read the computer program and execute any of the methods described above.
In several embodiments provided herein, it should be understood that, the disclosed methods and apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may be physically included separately, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.
The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform part of the steps of the transceiving method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.

Claims (10)

1. A method for determining dyspnea perception, comprising the steps of:
collecting dyspnea sensing data in various load resistance breathing tests, wherein the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person;
constructing a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises a plurality of load resistance breathing modes;
inputting personal information of a detected person into the resistance load breathing model, and matching the corresponding load resistance breathing mode according to the personal information of the detected person;
acquiring detection data of the detected person by adopting the matched load resistance breathing mode;
and calculating dyspnea sensing information of the detected person according to the matched load resistance breathing mode and the detection data.
2. The method of claim 1, wherein the resistance information comprises: at least one of a resistance loading mode, a resistance value, a resistance rising mode, and a resistance occurrence sequence.
3. The method for determining dyspnea sensing according to claim 2, wherein the resistance loading mode comprises at least one of an inhalation resistance mode, an exhalation resistance mode, and a breathing biphasic resistance mode.
4. The method of claim 2, wherein the resistance value is set in the form of specific data or in the form of a percentage of maximum respiratory muscle force.
5. The method according to claim 2, wherein the resistance-increasing mode is set by manually setting a resistance system or by using a random resistance system.
6. The method according to claim 1, wherein the evaluation information of the subject is obtained by a direct scoring method in which a VAS scale or Borg scale is used or an indirect scoring method in which the evaluation information is obtained from a respiratory muscle strength measurement result.
7. The method of claim 1, wherein the personal information includes at least one of gender, date of birth, height, weight, and disease information.
8. A dyspnea sensing assay system comprising:
the information acquisition module can acquire dyspnea sensing data in various load resistance breathing tests, wherein the dyspnea sensing data comprises resistance information, personal information and evaluation information of a detected person;
the model construction module is used for constructing a resistance load breathing model according to the dyspnea sensing data, wherein the resistance load breathing model comprises a plurality of load resistance breathing modes;
the input module can input personal information of a detected person to the resistance load breathing model;
the matching module is used for matching the corresponding load resistance breathing mode from the resistance load breathing model according to the personal information of the detected person;
the detection module is used for acquiring detection data of the detected person and calculating dyspnea sensing information of the detected person according to the detection data.
9. A computer storage medium comprising one or more computer instructions which, when executed, implement the method of any of claims 1-7.
10. A dyspnea sensing tester comprises a memory and a processor, and is characterized in that,
the memory is used for storing one or more computer instructions;
the processor is configured to invoke and execute the one or more computer instructions to implement the method of any of claims 1-7.
CN202211531184.5A 2022-12-01 2022-12-01 Dyspnea sensing measurement method, system, storage medium and measurement instrument Pending CN116158751A (en)

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