FIELD: non-invasive diagnostics.
SUBSTANCE: invention relates to the field of non-invasive diagnostics of the disease COVID-19 by measuring the parameters of the composition of the gaseous medium exhaled by the diagnosed person. The method for non-invasive diagnostics is carried out using a device (8) containing a gas sensor cell (4) for analyzing air exhaled by a person. The cell includes an array of 1 to N semi-selective gas sensors with different response mechanisms (1), an air temperature sensor (2), a relative air humidity sensor (3), a measuring unit (5), a microprocessor (6), and a means of collecting and supplying exhaled air to the gas sensor cell. The gas sensors are chosen to give an uncorrelated response to disease markers contained in exhaled air. At the same time, exhaled air is supplied to the gas sensor cell. The temperature and humidity of the incoming air are measured and the temperature of the gas sensors in the array is changed. A voltage pulse of specified duration and amplitude is applied to the electrodes of the array of gas sensors, and the time dependences of the response parameter of each gas sensor in the array are measured. The magnitude of the response of each gas sensor in the array is calculated. The resulting sensory response values are averaged. The probability of the presence of a coronavirus disease in a person is determined by analyzing the average values of the sensory response according to the classifier previously stored in the memory of the microprocessor and obtained by measuring the sensory response of the array of sensors for samples of healthy and sick COVID-19 people. The investigated sample is additionally sterilized and discharged into the atmosphere. The sensor cell is cleaned before the next test.
EFFECT: rapid diagnostics of COVID-19 is achieved, which can be used in test systems for daily rapid screening of people in crowded places, with high accuracy and reliability of measurement results due to the uncorrelated response from individual array sensors, which ensures maximum analysis efficiency with minimum analysis time.
2 cl, 5 dwg
Title | Year | Author | Number |
---|---|---|---|
GAS SENSOR CELL FOR NON-INVASIVE ANALYSIS OF HUMAN EXHALED AIR | 2022 |
|
RU2787244C1 |
METHOD FOR NONINVASIVE DIFFERENTIAL DIAGNOSIS OF DISEASES OF RESPIRATORY SYSTEM AND DEVICE FOR ITS IMPLEMENTATION | 2021 |
|
RU2760396C1 |
METHOD FOR SCREENING OF MALIGNANT TUMORS OF THORACIC CAVITY ORGANS | 2019 |
|
RU2707099C1 |
METHOD FOR EARLY DETECTION OF NEUROLOGICAL DISORDERS IN PATIENTS WITH COVID-19 | 2021 |
|
RU2779562C1 |
METHOD FOR DETERMINING THE PROBABILITY OF HEPATIC FIBROSIS IN PATIENTS PREVIOUSLY SUFFERING FROM COVID-19 | 2021 |
|
RU2764050C1 |
METHOD FOR DIAGNOSING MALIGNANT TUMORS OF THORACIC CAVITY ORGANS | 2023 |
|
RU2817246C1 |
METHOD FOR NON-INVASIVE MONITORING OF THE UPPER RESPIRATORY TRACT IN CALVES | 2019 |
|
RU2729106C1 |
DEVICE FOR COMPENSATION OF HYPERGLYCEMIA IN DIABETIC PATIENTS | 2015 |
|
RU2605792C2 |
METHOD FOR PREDICTING THE RISK OF DEVELOPING COVID-19 IN PATIENTS WITH HEMATOLOGICAL MALIGNANCIES | 2022 |
|
RU2783422C1 |
METHOD FOR DETECTING INFECTION OF HUMANS AND ANIMALS WITH SARS CoV 2 AND A DIAGNOSTIC KIT FOR IMPLEMENTING THE METHOD | 2021 |
|
RU2776295C1 |
Authors
Dates
2022-11-29—Published
2022-04-08—Filed