Early lung canceration detection device and method based on expired gas of human body

Abstract

The invention relates to a device and a method for detecting early lung canceration of exhaled air of a human body, and aims to provide a device and a method for noninvasive detection of early lung canceration of the human body. The device integrates a gas blowing assembly, a gas detection assembly, an embedded processor, a temperature and humidity module, a display module, a voice broadcast module, an Internet of Things module, an artificial intelligence algorithm module and a gas exhaust assembly. According to the method, a metabolic marker exhaled by a human body is exposed to a sensor, and real-time monitoring of lung canceration is realized by utilizing resistance change captured by the sensor and combining a data processing technology and an internet of things function. And the detection result can give an early warning to a user in a display and voice mode. The implementation of the invention provides a portable early detection method for human lung canceration, and has potential application prospects in future smart medical treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of early diagnosis of lung cancer, and specifically to a device and method for automatically monitoring exhaled metabolic marker gas of early lung cancer in human body, thereby realizing early diagnosis of lung cancer in human body. Background Art

[0002] Lung cancer is one of the malignant tumors with high morbidity and mortality worldwide. Early detection of lung cancer is an important means to improve the cure rate of lung cancer. Although traditional clinical detection methods for lung cancer such as bronchoscopy, DNA sequencing and liquid biopsy have improved the accuracy of lung cancer diagnosis (Reference: Tanner, M., In high-risk persons, lung cancer screening with CT vs. no or CXR screening reduces lung cancer mortality, Annals of Internal Medicine 2021, 174, JC128, Tsukida,S., et al., Unexpected diffuse Alveolar Hemorrhage After Bronchoscopy, Chest 2023, 164, e71, Saputra, HA, et al., Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review, International Journal of Biological Macromolecules 2023, 252, 126149), but it still has disadvantages such as high cost, time-consuming detection process, complicated operation, and the need for professional technicians to analyze. In addition, the efficiency of early screening for human lung cancer still needs to be improved.

[0003] Recently, breath detection technology uses the rich physiological and pathological information contained in human exhaled breath samples. Studies have used gas chromatography, mass spectrometry and surface enhanced Raman spectroscopy to analyze gas samples and detect lung cancer metabolic marker gases (Wang, X., et al., Comprehensive study of volatile compounds of rareLeucosceptrum canum Smith honey: Aroma profiling and characteristic compound screening via GC-MS and GC-MS / MS, Food Research International 2023, 169,112799, Huang, L., et al., Noninvasive Diagnosis of Gastric Cancer Based onBreath Analysis with a Tubular Surface-Enhanced Raman Scattering Sensor, ACS Sensors 2022, 7, 1439). Although the existing breath detection technology has made great progress in the early diagnosis of lung cancer, it still has disadvantages such as poor portability of detection equipment, long detection process and high cost. In view of the limitations of the existing technology, the present invention provides an early lung cancer detection device and method based on human exhaled breath, which has the technical advantages of short detection time, reusability, low use cost and intelligent operation, and is expected to provide an intelligent detection device and method for the early diagnosis of lung cancer, reduce the cost of lung cancer detection, and improve the cure rate of patients. Summary of the invention

[0004] The purpose of the present invention is to provide an early lung cancer detection device and method based on human exhaled breath to solve the problems existing in the above-mentioned background technology.

[0005] In order to achieve the above-mentioned purpose, the present invention provides the following technical solutions: an early lung cancer detection device based on human exhaled breath, comprising: an air blowing component, a gas detection component, an embedded processor, a temperature and humidity module, a display module, a voice broadcast module, an Internet of Things module, an artificial intelligence algorithm module and a gas exhaust component, and each module is specifically as follows: A blowing assembly is installed on the top of the gas detection assembly. The blowing assembly includes an air inlet pipe and a disposable air blowing nozzle. One end of the air inlet pipe is connected to the disposable air blowing nozzle, and the other end is connected to the gas chamber of the gas detection assembly.

[0006] The gas detection component comprises a gas chamber, a power supply unit, a gas detection module in the chamber and a data processing module.

[0007] The gas detection module is composed of a voltage regulating circuit and a sensor circuit. The output end of the voltage regulating circuit is connected to the heating end of the sensor to control the working temperature of the sensor.

[0008] The data processing module is connected to the output end of the gas detection module, and is used to amplify the signal of the sensor and transmit the signal to the embedded processor.

[0009] The gas exhaust assembly is composed of a gas outlet at the bottom of the gas chamber and a switchable housing at the back of the gas chamber.

[0010] The voltage regulating circuit is composed of a power supply unit, a voltage stabilizing chip (U1), a resistor (R1), a potentiometer (Rp1) and capacitors (C1, C2); the input end of the voltage stabilizing chip U1 is connected to the positive electrode of the power supply unit and the capacitor C1, and the other end of C1 is connected to the negative electrode of the power supply unit; the adjustable end of the voltage stabilizing chip U1 is connected to the potentiometer Rp1 and the resistor R1, the other end of Rp1 is connected to the negative electrode of the power supply unit, and the other end of R1 is connected to the output end of the voltage stabilizing chip U1; the output end of the voltage stabilizing chip U1 is connected to the resistor R1, the capacitor C2 and the heating end of the sensor M, and the other end of C2 is connected to the negative electrode of the power supply unit.

[0011] The sensor circuit is composed of a power supply unit, a sensor (M), resistors (R2, R3) and a potentiometer (Rp2); one end of the sensor M is connected to the positive electrode of the power supply unit and the potentiometer Rp2, and the other end of Rp2 is connected to the input terminal V of the data processing module. - and resistor R3, the other end of R3 is connected to the negative pole of the power supply unit; the other end of the sensor M is connected to the input terminal V + And resistor R2, the other end of R2 is connected to the negative electrode of the power supply unit.

[0012] The data processing module is composed of a power supply unit, an operational amplifier (IC1, IC2, IC3) and resistors (R4, R5, R6, R7, R8, R9, R10, R11, R12); the positive input terminal of the operational amplifier IC1 is connected to the input terminal V + ; The reverse input terminal of IC1 is connected to resistors R4 and R5, the other end of R5 is connected to resistor R7 and the output terminal of IC1, the other end of R4 is connected to the reverse input terminal of operational amplifier IC2 and resistor R6, the other end of R6 is connected to resistor R8 and the output terminal of IC2; the positive input terminal of operational amplifier IC2 is connected to the input terminal V of the data processing module -; The reverse input terminal of the operational amplifier IC3 is connected to the resistor R7 and the resistor R9, and the other end of R9 is connected to the output terminal of IC3 and the resistor R11; the positive input terminal of the operational amplifier IC3 is connected to the resistor R8 and the resistor R10, and the other end of R10 is connected to the resistor R12 and the reference voltage REF, and the other end of R12 is connected to the negative pole of the power supply unit; the output terminal OUT of the entire data processing module is connected to the input terminal of the embedded processor.

[0013] The display module is connected to the embedded processor and is used to display the real-time voltage value of the sensor. When the voltage value reaches the set threshold, the display module will issue an alarm to prompt the user to handle it in time; at the same time, the temperature and humidity information in the device can be displayed.

[0014] The voice broadcast module is connected to the embedded processor. When the voltage value reaches a set threshold, the voice broadcast module will sound an alarm to remind the user that there is a risk of lung cancer.

[0015] The IoT module is a wireless communication module (Wi-Fi), which is used to receive relevant data from sensors in real time and transmit the relevant data to the Internet cloud via wireless connection for synchronous observation.

[0016] The artificial intelligence algorithm module is connected to the embedded processor, and is used to receive the real-time voltage value of the sensor and calibrate the corresponding gas characteristics, store them in the database, and improve the accuracy and intelligence of human exhaled gas detection through machine learning.

[0017] The smartphone application software is connected to the embedded processor via a wireless connection to receive relevant data from the sensor in real time and perform synchronous observation, which will be more helpful for users to deal with abnormal signals in a timely manner.

[0018] Optionally, the early lung cancer exhaled gas includes but is not limited to benzaldehyde, toluene and formaldehyde marker gases.

[0019] A method for detecting early lung cancer based on human exhaled breath, using any of the above-mentioned devices for detecting early lung cancer based on human exhaled breath, comprises the following steps: A. Human exhaled breath generates electrical signals after being exposed to the sensor; B. Transmitting the electrical signal data of the sensor to the data processing module through the sensor circuit; C. The data processing module receives the electrical signal from the sensor, amplifies it, and then transmits the processed electrical signal to the embedded processor; D. The embedded processor processes the electrical signal to determine whether the concentration of the exhaled metabolic marker gas reaches a threshold value. If the threshold value is reached, the embedded processor sends a command to the voice broadcast module to display and inform the user of the test results; E. Use artificial intelligence algorithm modules to improve the accuracy and intelligence of human exhaled gas detection through machine learning; F. Send the detection data to the remote server and user device through the IoT module for further monitoring and recording; G. The remaining exhaled gas sample is discharged through the gas exhaust component for preparation for the next test. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0021] Figure 1 The overall block diagram of an early lung cancer detection device based on human exhaled breath; Figure 2 The present invention is a voltage regulation circuit structure diagram of an early lung cancer detection device based on human exhaled breath; Figure 3 The sensor circuit structure diagram of an early lung cancer detection device based on human exhaled breath; Figure 4 The data processing module structure diagram of an early lung cancer detection device based on human exhaled breath; Figure 5 A flowchart of a method for detecting early lung cancer based on human exhaled breath; Figure 6 The diagram is a structural diagram of an early lung cancer detection device based on human exhaled breath. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention. In the description of the present invention, it should be understood that the orientation or positional relationship shown in the figure is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0023] Example 1 See also Figure 1-6 As shown, the present invention is a device and method for detecting early lung cancer based on human exhaled breath, the device includes a blowing component, a gas detection component, an embedded processor, a temperature and humidity module, a display module, a voice broadcast module, an Internet of Things module, an artificial intelligence algorithm module and a gas exhaust component. Figure 6 As shown, it includes benzaldehyde, formaldehyde, toluene gas sensors and temperature and humidity module 1, voice broadcast module 2, display module 3, Internet of Things module 4, artificial intelligence algorithm module 5, disposable blowing nozzle 6, air inlet 7 and air outlet 8. When human exhaled gas is exposed to the sensor, electrical signals are generated; these signals are transmitted to the data processing module through the sensor circuit; the data processing module receives the electrical signals of the sensor, amplifies them, and then transmits the processed electrical signals to the embedded processor; the embedded processor processes the electrical signals to determine whether the concentration of the exhaled metabolic marker gas reaches the threshold value. If the threshold value is reached, the embedded processor issues a command to the voice broadcast module to display and inform the user of the test results; the machine learning of the artificial intelligence algorithm module is used to improve the accuracy and intelligence of human exhaled gas detection; the detection data is sent to the remote server and user equipment through the Internet of Things module for further monitoring and recording; finally, the remaining exhaled gas sample is discharged through the gas discharge component for the next test.

[0024] Example 2 See also Figure 1-6 As shown, the present invention is a device and method for detecting early lung cancer based on human exhaled breath, the device includes a blowing component, a gas detection component, an embedded processor, a temperature and humidity module, a display module, a voice broadcast module, an Internet of Things module, an artificial intelligence algorithm module and a gas exhaust component. Figure 6As shown, it includes an exhaled gas detection module 1, a SYN6288 module as a voice broadcast module 2, a data processing module 3, a power supply unit and an Internet of Things module 4, an artificial intelligence algorithm module 5, a disposable blowing nozzle 6, an air inlet 7 and an air outlet 8. When human exhaled gas is exposed to the sensor, electrical signals are generated; these signals are transmitted to the data processing module through the sensor circuit; the data processing module receives the electrical signals of the sensor, amplifies them, and then transmits the processed electrical signals to the embedded processor; the embedded processor processes the electrical signals to determine whether the concentration of the exhaled metabolic marker gas reaches the threshold value. If the threshold value is reached, the embedded processor issues a command to the voice broadcast module to display and inform the user of the detection results; the machine learning of the artificial intelligence algorithm module is used to improve the accuracy and intelligence of human exhaled gas detection; the detection data is sent to the remote server and user equipment through the Internet of Things module for further monitoring and recording; finally, the remaining exhaled gas samples are discharged through the gas discharge component for the next detection.

[0025] Example 3 See also Figure 1-6 As shown, the present invention is a device and method for detecting early lung cancer based on human exhaled breath, the device includes a blowing component, a gas detection component, an embedded processor, a temperature and humidity module, a display module, a voice broadcast module, an Internet of Things module, an artificial intelligence algorithm module and a gas exhaust component. Figure 6 As shown, it includes an exhaled gas detection module 1, a voice broadcast module 2, a data processing module 3, a power supply unit and an artificial intelligence algorithm module 4, an ESP8266 as an Internet of Things module 5, a disposable blowing nozzle 6, an air inlet 7 and an air outlet 8. When human exhaled gas is exposed to the sensor, electrical signals are generated; these signals are transmitted to the data processing module through the sensor circuit; the data processing module receives the electrical signals of the sensor, amplifies them, and then transmits the processed electrical signals to the embedded processor; the embedded processor processes the electrical signals to determine whether the concentration of the exhaled metabolic marker gas reaches the threshold value. If the threshold value is reached, the embedded processor issues a command to the voice broadcast module to display and inform the user of the detection results; the machine learning of the artificial intelligence algorithm module is used to improve the accuracy and intelligence of human exhaled gas detection; the detection data is sent to the remote server and user equipment through the Internet of Things module for further monitoring and recording; finally, the remaining exhaled gas samples are discharged through the gas discharge component for the next detection.

Claims

1. An early lung cancer detection device based on human exhaled breath, characterized in that include: Blowing component, gas detection component, embedded processor, temperature and humidity module, display module, voice broadcast module, Internet of Things module, artificial intelligence algorithm module and gas exhaust component; among them, A blowing assembly is installed on the top of the gas detection assembly, and the blowing assembly includes an air inlet pipe and a disposable air blowing nozzle, one end of the air inlet pipe is connected to the disposable air blowing nozzle, and the other end is connected to the gas chamber of the gas detection assembly; The gas detection assembly includes a gas chamber, a power supply unit, a gas detection module in the chamber, and a data processing module; The gas detection module is composed of a voltage regulating circuit and a sensor circuit. The output end of the voltage regulating circuit is connected to the heating end of the sensor to control the operating temperature of the sensor. The data processing module is connected to the output end of the gas detection module, and is used to amplify the sensor signal and transmit the signal to the embedded processor; The gas exhaust assembly is composed of a gas outlet at the bottom of the gas chamber and a switchable housing at the back of the gas chamber.

2. The device for detecting early lung cancer based on human exhaled breath according to claim 1, characterized in that: The voltage regulating circuit is composed of a power supply unit, a voltage stabilizing chip (U1), a resistor (R1), a potentiometer (Rp1) and capacitors (C1, C2); the input end of the voltage stabilizing chip U1 is connected to the positive electrode of the power supply unit and the capacitor C1, and the other end of C1 is connected to the negative electrode of the power supply unit; the adjustable end of the voltage stabilizing chip U1 is connected to the potentiometer Rp1 and the resistor R1, the other end of Rp1 is connected to the negative electrode of the power supply unit, and the other end of R1 is connected to the output end of the voltage stabilizing chip U1; the output end of the voltage stabilizing chip U1 is connected to the resistor R1, the capacitor C2 and the heating end of the sensor M, and the other end of C2 is connected to the negative electrode of the power supply unit.

3. The device for detecting early lung cancer based on human exhaled breath according to claim 1, characterized in that: The sensor circuit is composed of a power supply unit, a sensor (M), resistors (R2, R3) and a potentiometer (Rp2); one end of the sensor M is connected to the positive electrode of the power supply unit and the potentiometer Rp2, and the other end of Rp2 is connected to the input terminal V of the data processing module. - and resistor R3, the other end of R3 is connected to the negative pole of the power supply unit; the other end of the sensor M is connected to the input terminal V + And resistor R2, the other end of R2 is connected to the negative electrode of the power supply unit.

4. The device for detecting early lung cancer based on human exhaled breath according to claim 1, characterized in that: The data processing module is composed of a power supply unit, an operational amplifier (IC1, IC2, IC3) and resistors (R4, R5, R6, R7, R8, R9, R10, R11, R12); the positive input terminal of the operational amplifier IC1 is connected to the input terminal V + ; The reverse input terminal of IC1 is connected to resistors R4 and R5, the other end of R5 is connected to resistor R7 and the output terminal of IC1, the other end of R4 is connected to the reverse input terminal of operational amplifier IC2 and resistor R6, the other end of R6 is connected to resistor R8 and the output terminal of IC2; the positive input terminal of operational amplifier IC2 is connected to the input terminal V of the data processing module - ; The reverse input terminal of the operational amplifier IC3 is connected to the resistor R7 and the resistor R9, and the other end of R9 is connected to the output terminal of IC3 and the resistor R11; the positive input terminal of the operational amplifier IC3 is connected to the resistor R8 and the resistor R10, and the other end of R10 is connected to the resistor R12 and the reference voltage REF, and the other end of R12 is connected to the negative pole of the power supply unit; the output terminal OUT of the entire data processing module is connected to the input terminal of the embedded processor.

5. The early lung cancer exhaled gas according to claim 1 includes but is not limited to benzaldehyde, toluene and formaldehyde marker gases.

6. The display module according to claim 1, characterized in that: Connected to the embedded processor, it is used to display the real-time voltage value of the sensor. When the voltage value reaches the set threshold, the display module will issue an alarm to prompt the user to handle it in time; it can also display the temperature and humidity information in the device.

7. The voice broadcast module according to claim 1, characterized in that: Connected to the embedded processor, when the voltage value reaches the set threshold, the voice broadcast module will sound an alarm to remind the user that there is a risk of lung cancer.

8. The Internet of Things module according to claim 1, characterized in that: The IoT module is a wireless communication module (Wi-Fi), which is used to receive relevant data from sensors in real time and transmit the relevant data to the Internet cloud via wireless connection for synchronous observation.

9. The artificial intelligence algorithm module according to claim 1, characterized in that: It is connected to the embedded processor, receives the real-time voltage value of the sensor and calibrates the corresponding gas characteristics, stores them in the database, and improves the accuracy and intelligence of human exhaled gas detection through machine learning.

10. A method for detecting early lung cancer based on human exhaled breath, characterized in that: The device for detecting early lung cancer based on human exhaled breath as claimed in any one of claims 1 to 9 comprises the following steps: A. Human exhaled breath generates electrical signals after being exposed to the sensor; B. Transmitting the electrical signal data of the sensor to the data processing module through the sensor circuit; C. The data processing module receives the electrical signal from the sensor, amplifies it, and then transmits the processed electrical signal to the embedded processor; D. The embedded processor processes the electrical signal to determine whether the concentration of the exhaled metabolic marker gas reaches a threshold value. If the threshold value is reached, the embedded processor sends a command to the voice broadcast module to display and inform the user of the test results; E. Use artificial intelligence algorithm modules to improve the accuracy and intelligence of human exhaled gas detection through machine learning; F. Send the detection data to the remote server and user device through the IoT module for further monitoring and recording; G. The remaining exhaled gas sample is discharged through the gas discharge component for preparation for the next test.

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