CN113916617A - Intelligent bionic human respiratory tract multi-part inhaled gas sampling method - Google Patents
Intelligent bionic human respiratory tract multi-part inhaled gas sampling method Download PDFInfo
- Publication number
- CN113916617A CN113916617A CN202111055444.1A CN202111055444A CN113916617A CN 113916617 A CN113916617 A CN 113916617A CN 202111055444 A CN202111055444 A CN 202111055444A CN 113916617 A CN113916617 A CN 113916617A
- Authority
- CN
- China
- Prior art keywords
- respiratory tract
- parts
- human
- bionic
- gas
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 210000002345 respiratory system Anatomy 0.000 title claims abstract description 61
- 238000000034 method Methods 0.000 title claims abstract description 39
- 239000011664 nicotinic acid Substances 0.000 title claims abstract description 33
- 238000005070 sampling Methods 0.000 title claims abstract description 14
- 239000000126 substance Substances 0.000 claims abstract description 15
- 230000035790 physiological processes and functions Effects 0.000 claims abstract description 13
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 238000006243 chemical reaction Methods 0.000 claims abstract description 10
- 230000000694 effects Effects 0.000 claims abstract description 10
- 230000000241 respiratory effect Effects 0.000 claims abstract description 9
- 238000000018 DNA microarray Methods 0.000 claims abstract description 8
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 8
- 244000005700 microbiome Species 0.000 claims abstract description 8
- 238000005516 engineering process Methods 0.000 claims abstract description 7
- 230000000704 physical effect Effects 0.000 claims abstract description 4
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 29
- 210000000214 mouth Anatomy 0.000 claims description 9
- 210000003928 nasal cavity Anatomy 0.000 claims description 9
- 210000000621 bronchi Anatomy 0.000 claims description 6
- 238000004519 manufacturing process Methods 0.000 claims description 6
- 210000003800 pharynx Anatomy 0.000 claims description 6
- 210000003437 trachea Anatomy 0.000 claims description 6
- 210000003456 pulmonary alveoli Anatomy 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 abstract description 9
- 238000012360 testing method Methods 0.000 abstract description 5
- 230000036541 health Effects 0.000 abstract description 3
- 238000013461 design Methods 0.000 abstract description 2
- 241000700605 Viruses Species 0.000 description 5
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 230000007613 environmental effect Effects 0.000 description 4
- 230000035565 breathing frequency Effects 0.000 description 3
- 208000023504 respiratory system disease Diseases 0.000 description 3
- 230000001020 rhythmical effect Effects 0.000 description 3
- 238000010339 medical test Methods 0.000 description 2
- 108090000623 proteins and genes Proteins 0.000 description 2
- 208000025721 COVID-19 Diseases 0.000 description 1
- 241000711573 Coronaviridae Species 0.000 description 1
- 238000003915 air pollution Methods 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000006806 disease prevention Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 241000712461 unidentified influenza virus Species 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/02—Devices for withdrawing samples
- G01N1/22—Devices for withdrawing samples in the gaseous state
- G01N1/24—Suction devices
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
Landscapes
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Combustion & Propulsion (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
The invention relates to the technical field of medical use, in particular to a method for sampling multiple parts of an intelligent bionic human respiratory tract inhaled gas, which designs and manufactures the parts of the bionic human respiratory tract according to the respiratory state of the physiological respiratory characteristics of a human body and the physiological environment characteristics of the parts of the respiratory tract, collects gas samples when the inhaled gas flows through the parts in the bionic respiratory process, is used for detecting the physical properties, chemical components and microorganism types and the content, activity and functional state of the gas at the parts of the respiratory tract, simulates the physiological environment of the parts of the respiratory tract when the human body breathes under the physiological state by an artificial intelligence technology, contacts with the surface of a detection biochip, generates biological reaction, and performs further experimental analysis on detected signals. Compared with the prior art, the invention can realize effective test on harmful substances in the inhaled air by simulating the physiological environment of the human body, and has indirect reference value for maintaining the biological environment and the human health.
Description
Technical Field
The invention relates to the technical field of medical use, in particular to an intelligent bionic human respiratory tract multi-part inhaled gas sampling method.
Background
Respiratory diseases become one of the main health-threatening diseases, air pollution is an important factor causing the respiratory diseases, and the harmful ingredients invade the respiratory system of a human body in the process of breathing of people to cause various respiratory diseases.
However, with the recognition of the importance of the interaction between environmental factors and genes in vivo on the occurrence and development of human diseases, there is a need for intelligent equipment capable of timely and accurately detecting harmful substances in inhaled air to the human body and measuring the content and concentration of harmful substances in physiological environments of various parts of respiratory tract during physiological respiration for diagnosis and prevention of diseases.
Therefore, it is necessary to design an intelligent method for sampling inhaled gas at multiple sites of a bionic human respiratory tract, which is based on the physiological respiration characteristics of human body, such as: the method is established for collecting inhalation gas samples in the bionic human body breathing process under the breathing state set by parameters such as volume, pressure, flow, frequency and the like, and is used for various environments and medical test methods.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an intelligent bionic human respiratory tract multi-part inhaled gas sampling method, which comprises the following steps of: the method is established for collecting inhalation gas samples in the bionic human body breathing process under the breathing state set by parameters such as volume, pressure, flow, frequency and the like, and is used for various environments and medical test methods.
In order to achieve the aim, the invention provides an intelligent bionic human respiratory tract multi-part inhaled gas sampling method, which comprises the following steps:
s1: designing and manufacturing various parts of the bionic human respiratory tract according to the respiratory state of the characteristics of the human physiological respiration and the physiological environment characteristics of various parts of the respiratory tract;
the step of S1 includes the following:
s10: bionic manufacturing of various parts of the respiratory tract;
s20: collecting gas samples when the inhaled gas flows through all parts in the bionic breathing process;
s30: the device is used for detecting the physical properties, chemical compositions and microorganism types of the gas at each part of the respiratory tract and the content, activity and functional state of the gas;
s2: simulating physiological environments of all parts of the respiratory tract when breathing under the physiological state of a human body by using an artificial intelligence technology;
s3: contacting with the surface of a detection biochip, generating a biological reaction, and performing further experimental analysis on a detected signal;
the respiratory tract comprises the following parts: nasal cavity, oral cavity, throat, trachea, bronchi, alveoli;
the characteristics of the respiratory state include: capacity, pressure, flow rate, and frequency.
Compared with the prior art, the invention can realize effective test of the type, content and concentration of harmful substances in the air inhaled into the human body by simulating the human body breathing state, the breathing part and the breathing physiological environment through artificial intelligence and collecting the gas sample simulating the human body breathing, provides a more clinically significant detection result and has indirect reference value for maintaining the biological environment, the human health and preventing and treating diseases.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by those skilled in the art without any creative work based on the embodiments of the present invention belong to the protection scope of the present invention.
The invention provides an intelligent bionic human respiratory tract multi-part inhaled gas sampling method, which comprises the following steps:
s1: designing and manufacturing various parts of the bionic human respiratory tract according to the respiratory state of the characteristics of the human physiological respiration and the physiological environment characteristics of various parts of the respiratory tract;
the step of S1 includes the following:
s10: bionic manufacturing of various parts of the respiratory tract;
s20: collecting gas samples when the inhaled gas flows through all parts in the bionic breathing process;
s30: the device is used for detecting the physical properties, chemical compositions and microorganism types of the gas at each part of the respiratory tract and the content, activity and functional state of the gas;
s2: simulating physiological environments of all parts of the respiratory tract when breathing under the physiological state of a human body by using an artificial intelligence technology;
s3: contacting with the surface of a detection biochip, generating a biological reaction, and performing further experimental analysis on a detected signal;
the respiratory tract comprises the following parts: nasal cavity, oral cavity, throat, trachea, bronchi, alveoli;
the characteristics of the respiratory state include: capacity, pressure, flow rate, and frequency.
Example 1:
the method for sampling the multi-site inhaled gas of the intelligent bionic human respiratory tract is adopted to detect the content and concentration of various viruses, such as influenza virus and new coronavirus COVID-19, in the inhaled air in real time:
1) the method is characterized in that the parts of the bionic human respiratory tract are designed and manufactured according to the physiological environmental characteristics of the parts of the respiratory tract, such as: air collecting cavities in nasal cavity, oral cavity, throat, trachea, bronchus, and alveolus;
2) the inhaled gas in the air collecting cavities at all parts of the bionic human respiratory tract can be separated or combined and guided to a detection or biological reaction chamber, and the separated or combined collection can be switched with each other through a valve as required, for example, the gas entering the simulated nasal cavity and the simulated oral cavity is combined and enters the simulated upper respiratory tract, and the combined gas is guided out and enters the test;
3) collecting gas accumulated in multiple rhythmic breathing processes by adopting the processes of active inspiration and passive expiration for simulating rhythmicity in the physiological state of human respiration;
4) the device can simulate the physiological environment of each part of the respiratory tract when breathing under the human physiological state by the artificial intelligence technology, such as temperature, humidity, pH value and the like, so as to keep the activity state of various substances and microorganisms in the inhaled gas as close as possible to the physiological environment of each part under the human respiratory tract physiological state;
5) simulating the contact between the gas in different respiratory tract parts and the biochip for detecting virus gene in physiological environment to produce biological reaction, and converting the detected signal into transmittable signal for further experiment analysis;
6) each biochip can be taken out for further experimental analysis;
7) the application scenes are as follows: the method is characterized in that the type, concentration, content, activity and the like of the virus to be detected are monitored in real time in people cluster points such as subway stations, shopping malls, hospital halls and the like, and overproof alarm is carried out.
Example 2:
the method for sampling the multi-part inhaled gas of the intelligent bionic human respiratory tract is adopted to detect the content and concentration of various harmful substances in the inhaled air, such as SO2, NO2, CO, O3, PM2.5, PM10 and the like in real time:
1) the method is characterized in that the parts of the bionic human respiratory tract are designed and manufactured according to the physiological environmental characteristics of the parts of the respiratory tract, such as: air collecting cavities in nasal cavity, oral cavity, throat, trachea, bronchus, and alveolus;
2) the inhaled gas in the air collecting cavities at all parts of the bionic human respiratory tract can be separated or combined and guided to a detection or biological reaction chamber, and the separated or combined collection can be switched with each other through a valve as required, for example, the gas entering the simulated nasal cavity and the simulated oral cavity is combined and enters the simulated upper respiratory tract, and the combined gas is guided out and enters the test;
3) collecting gas accumulated in multiple rhythmic breathing processes by adopting the processes of active inspiration and passive expiration for simulating rhythmicity in the physiological state of human respiration;
4) the device can simulate the physiological environment of each part of the respiratory tract when breathing under the human physiological state by the artificial intelligence technology, such as temperature, humidity, pH value and the like, so as to keep the activity state of various substances and microorganisms in the inhaled gas as close as possible to the physiological environment of each part under the human respiratory tract physiological state;
5) simulating the contact between the gas of each part of the respiratory tract and the surface of the detection module under the condition of physiological environment, generating biological reaction, and converting the detected signal into a transmittable signal to output for further experimental analysis;
6) each biochip can be taken out for further experimental analysis;
7) the application scenes are as follows: the method is characterized in that the type, concentration, content, activity and the like of the virus to be detected are monitored in real time in people cluster points such as subway stations, shopping malls, hospital halls and the like, and overproof alarm is carried out.
Example 3:
the method for sampling the multi-site inhaled gas of the intelligent bionic human respiratory tract is adopted to detect various harmful substances, such as SO2, NO2, CO, O3, PM2.5, PM10 and the like, in the inhaled air of the children and the types, the contents and the concentrations of microorganisms in real time:
1) the method is characterized in that the parts of the bionic human respiratory tract are designed and manufactured according to the physiological environmental characteristics of the parts of the respiratory tract, such as: air collecting cavities in nasal cavity, oral cavity, throat, trachea, bronchus, and alveolus;
2) the inhaled gas in the air collecting cavities at all parts of the bionic human respiratory tract can be separated or combined and guided to a detection or biological reaction chamber, and the separated or combined collection can be switched with each other through a valve as required, for example, the gas entering the simulated nasal cavity and the simulated oral cavity is combined and enters the simulated upper respiratory tract, and the combined gas is guided out and enters the test;
3) the process of active inspiration and passive expiration simulating the rhythmicity of human breathing physiological state is adopted to collect the gas accumulated in the process of multiple rhythmical breathings. The breathing frequency of the children is faster than that of adults, the system can adjust the simulated breathing frequency according to needs, and for example, the corresponding breathing frequency can be set in kindergartens and primary schools;
4) the device can simulate the physiological environment of each part of the respiratory tract when breathing under the human physiological state by the artificial intelligence technology, such as temperature, humidity, pH value and the like, so as to keep the activity state of various substances and microorganisms in the inhaled gas as close as possible to the physiological environment of each part under the human respiratory tract physiological state;
5) simulating the contact between the gas of each part of the respiratory tract and the surface of the detection module under the condition of physiological environment, generating biological reaction, and converting the detected signal into a transmittable signal to output for further experimental analysis;
6) each biochip can be taken out for further experimental analysis;
7) the application scenes are as follows: at child concentration points such as schools, playgrounds, kindergartens and the like, the types, concentrations, contents, activities and the like of harmful substances and viruses in the air to be detected are monitored in real time, and standard exceeding alarm is carried out.
The invention solves the problem that the traditional equipment can not detect the content and the concentration of harmful substances in the physiological environment of each part of the respiratory tract, and can more accurately sample the respiratory tract part of a human body and the gas in the physiological environment in an artificial intelligent simulation mode, thereby providing a detection result with more clinical significance and having indirect reference value for maintaining the biological environment, the human health and preventing and treating diseases.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A method for sampling the inhaled gas of multiple parts of an intelligent bionic human respiratory tract is characterized by comprising the following steps: the method comprises the following steps:
s1: designing and manufacturing various parts of the bionic human respiratory tract according to the respiratory state of the characteristics of the human physiological respiration and the physiological environment characteristics of various parts of the respiratory tract;
the step of S1 includes the following:
s10: bionic manufacturing of various parts of the respiratory tract;
s20: collecting gas samples when the inhaled gas flows through all parts in the bionic breathing process;
s30: the device is used for detecting the physical properties, chemical compositions and microorganism types of the gas at each part of the respiratory tract and the content, activity and functional state of the gas;
s2: simulating physiological environments of all parts of the respiratory tract when breathing under the physiological state of a human body by using an artificial intelligence technology;
s3: contacting with the surface of the detection biochip, generating biological reaction, and further analyzing the detected signal.
2. The method for intelligently sampling the inhaled gas at multiple parts of the human bionic respiratory tract according to claim 1, wherein the method comprises the following steps: the respiratory tract comprises the following parts: nasal cavity, oral cavity, throat, trachea, bronchus, and alveolus.
3. The method for intelligently sampling the inhaled gas at multiple parts of the human bionic respiratory tract according to claim 1, wherein the method comprises the following steps: the characteristics of the respiratory state include: capacity, pressure, flow rate, and frequency.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111055444.1A CN113916617A (en) | 2021-09-09 | 2021-09-09 | Intelligent bionic human respiratory tract multi-part inhaled gas sampling method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111055444.1A CN113916617A (en) | 2021-09-09 | 2021-09-09 | Intelligent bionic human respiratory tract multi-part inhaled gas sampling method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN113916617A true CN113916617A (en) | 2022-01-11 |
Family
ID=79234267
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111055444.1A Pending CN113916617A (en) | 2021-09-09 | 2021-09-09 | Intelligent bionic human respiratory tract multi-part inhaled gas sampling method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113916617A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118057143A (en) * | 2022-11-21 | 2024-05-21 | 北京市科学技术研究院城市安全与环境科学研究所 | Air sampler based on human breathing principle |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10130266A1 (en) * | 2001-06-20 | 2003-01-02 | Peter Lueth | Plotting method for general respiration curves for use with testing devices that simulate human breathing, whereby test persons are tested in a wide range or conditions and the data used to prepare generalized respiration curves |
CN101466437A (en) * | 2006-04-12 | 2009-06-24 | Cl.Com有限公司 | Evaluation methodology of the protection characteristics of personal protective equipments against biological agents |
WO2014089588A1 (en) * | 2012-12-12 | 2014-06-19 | Simcharacters Gmbh | Method and device for training in artificial respiration |
CN107422109A (en) * | 2017-06-13 | 2017-12-01 | 山东科技大学 | Analogue system and mineral environment dust emulation mode |
CN107607511A (en) * | 2017-10-21 | 2018-01-19 | 云南中烟工业有限责任公司 | The detection method that a kind of cigarette smoke influences on the Subcellular Localization of aquaporin 5 |
CN109166438A (en) * | 2018-10-15 | 2019-01-08 | 西安建筑科技大学 | A kind of breathing thermal manikin and its operating method sucking exposure detection for particulate pollutant human body |
CN111199785A (en) * | 2020-02-19 | 2020-05-26 | 清华大学 | Method and system for establishing human body external respiratory system |
CN111766092A (en) * | 2020-07-10 | 2020-10-13 | 中国矿业大学 | Virus droplet aerosol infection interactive simulation experiment system |
CN112304850A (en) * | 2020-11-23 | 2021-02-02 | 中国矿业大学 | Self-absorption filter type protective mask comprehensive performance test experimental device and method |
CN112525621A (en) * | 2020-12-17 | 2021-03-19 | 辽宁省检验检测认证中心 | Method and device for collecting atmospheric micro-plastic |
-
2021
- 2021-09-09 CN CN202111055444.1A patent/CN113916617A/en active Pending
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10130266A1 (en) * | 2001-06-20 | 2003-01-02 | Peter Lueth | Plotting method for general respiration curves for use with testing devices that simulate human breathing, whereby test persons are tested in a wide range or conditions and the data used to prepare generalized respiration curves |
CN101466437A (en) * | 2006-04-12 | 2009-06-24 | Cl.Com有限公司 | Evaluation methodology of the protection characteristics of personal protective equipments against biological agents |
WO2014089588A1 (en) * | 2012-12-12 | 2014-06-19 | Simcharacters Gmbh | Method and device for training in artificial respiration |
CN107422109A (en) * | 2017-06-13 | 2017-12-01 | 山东科技大学 | Analogue system and mineral environment dust emulation mode |
CN107607511A (en) * | 2017-10-21 | 2018-01-19 | 云南中烟工业有限责任公司 | The detection method that a kind of cigarette smoke influences on the Subcellular Localization of aquaporin 5 |
CN109166438A (en) * | 2018-10-15 | 2019-01-08 | 西安建筑科技大学 | A kind of breathing thermal manikin and its operating method sucking exposure detection for particulate pollutant human body |
CN111199785A (en) * | 2020-02-19 | 2020-05-26 | 清华大学 | Method and system for establishing human body external respiratory system |
CN111766092A (en) * | 2020-07-10 | 2020-10-13 | 中国矿业大学 | Virus droplet aerosol infection interactive simulation experiment system |
CN112304850A (en) * | 2020-11-23 | 2021-02-02 | 中国矿业大学 | Self-absorption filter type protective mask comprehensive performance test experimental device and method |
CN112525621A (en) * | 2020-12-17 | 2021-03-19 | 辽宁省检验检测认证中心 | Method and device for collecting atmospheric micro-plastic |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118057143A (en) * | 2022-11-21 | 2024-05-21 | 北京市科学技术研究院城市安全与环境科学研究所 | Air sampler based on human breathing principle |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107271337B (en) | Human alveolus aerosol deposition measurement experiment system | |
Risby et al. | Current status of clinical breath analysis | |
Adamkiewicz et al. | Association between air pollution exposure and exhaled nitric oxide in an elderly population | |
US7255677B2 (en) | Detection, diagnosis, and monitoring of a medical condition or disease with artificial olfactometry | |
CN102596029B (en) | Method and apparatus for measuring the concentration of a gas in exhaled air | |
CN106456053A (en) | Selection, segmentation and analysis of exhaled breath for airway disorders assessment | |
EP3448254A1 (en) | A method for collecting a selective portion of a subject's breath | |
Beydon et al. | Pre/postbronchodilator interrupter resistance values in healthy young children | |
CN103491872B (en) | Air flue checks status indicator in real time | |
CN104665835A (en) | Human energy metabolism detection device and method | |
CN105496412B (en) | A kind of expiration inflammation monitoring method and device | |
CN103169476A (en) | Method and device for identification and early warning of respiration wave form image | |
CN116110585B (en) | Respiratory rehabilitation evaluation system for chronic obstructive pneumonia | |
CN205263092U (en) | Measurement device for expiration nitric oxide and carbon monoxide concentration | |
CN113916617A (en) | Intelligent bionic human respiratory tract multi-part inhaled gas sampling method | |
CN104713989A (en) | Mixing chamber technology-based gas metabolism detection apparatus and method thereof | |
CN113168785B (en) | Method and system for simulating deposition of inhaled medicament on lungs | |
SIngh et al. | Review of Infrared Carbon-Dioxide Sensors and Capnogram Features for Developing Asthma-Monitoring Device. | |
Koenig et al. | Bronchoconstrictor responses to sulfur dioxide or sulfur dioxide plus sodium chloride droplets in allergic, nonasthmatic adolescents | |
Linn et al. | Chamber exposures of children to mixed ozone, sulfur dioxide, and sulfuric acid | |
CN104391087B (en) | A kind of moisture is exhaled and is measured Exhaled nitric oxide concentration method and device | |
Solak et al. | Respiration monitoring using a paper-based wearable humidity sensor, a step forward to clinical tests | |
CN114754945A (en) | Method for monitoring dynamic leakage flow and leakage rate of respirator in operation process | |
CN210931411U (en) | A expiration detector for lung cancer screening based on graphite alkene sensor | |
Santos et al. | Implementation of machine learning for breath collection |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |