Apparatus for Early Detection of Respiratory Diseases Aggravated by Respiratory Failure and Apnea-Hypopnea Syndrome

Since loss of working capacity and disability associated with respiratory diseases are caused by bronchial asthma and chronic obstructive pulmonary disease in 2/3 of cases, there is a need for technical support for early detection of these diseases. The developed diagnostic complex is based on an evolutionary mathematical model of the human respiratory system, describing the processes of gas exchange between the atmosphere and the lungs and between the lungs and blood. The complex allows analyzing such respiratory system parameters as arterial blood hemoglobin oxygen saturation, heart rate and respiratory rate. The complex is suitable for onetime (screening) measurements, as well as long-term (night/daily) monitoring. The corresponding software has been developed that allows analyzing the desaturation index, apnea-hypopnea index, photoplethysmogram, and visualizing the breathing process. The complex implements a standardized six-minute walk load test. This allows identifying respiratory failure, assessing its severity and conditions of occurrence. During the testing at a health resort, it was possible to diagnose obstructive apnea-hypopnea syndrome at an early stage in people who were unaware of the disease. The choice of a health resort was due to the comfortable conditions for conducting night monitoring, the availability of time and the desire of people to take care of their health and undergo diagnostics. 

1. Statistical Yearbook of the Republic of Belarus. Official Stat. Collection for 2023. Minsk, Belstat Publ., 2023 (in Russian).

2. Zelmanski O. B., Davidovskaya E. I. (2022) Respiratory Support: Aspects of Application for Therapy and Rehabilitation. Medelectronics–2022. Medical Electronics and New Medical Technologies, Collection of Scientific Articles from the XIII International Scientific and Technical Conference, Minsk, Dec. 8–9. Minsk, Belarusian State University of Informatics and Radioelectronics. 46–50 (in Russian).

3. Lapitsky D. V., Ermolkevich R. F., Metelsky S. M., Ryapolov A. N., Mitkovskaya N. P., Manichev I. A., et al. (2017) Diagnostic Capabilities of Non-Invasive Monitoring of Arterial Blood Hemoglobin Oxygen Saturation in the Clinic of Internal Diseases. Minsk, Belarusian State Medical University (in Russian).

4. Trusov P. V., Zaitseva N. V., Tsinker M. Yu. (2016) Modeling the Human Breathing Process: Conceptual and Mathematical Formulations. Mathematical Biology and Bioinformatics. 11 (1), 64–80. DOI: 10.17537/2016.11.64 (in Russian).

5. Boyarshinov M. G. (2010) Solution of the System of Euler Equations for the Steady Flow of an Ideal Gas from a Point Source. Bulletin of the Chelyabinsk State University. Physics. 8 (24), 5–8 (in Russian).

6. Squara P. (2014) Central Venous Oxygenation: When Physiology Explains Apparent Discrepancies. Critical Care. 579. https://doi.org/10.1186/s13054-014-0579-9.

7. Xu Zhang, Meimei Zhang, Shengkun Zheng, Liqi Wang, Jilun Ye (2016) A New Method for Noninvasive Venous Blood Oxygen Detection. BioMedical Engineering OnLine. 15 (84). https://doi.org/10.1186/s12938016-0208-8.

8. Johns M. W. (1991) A New Method for Measuring Daytime Sleepiness: The Epworth Sleepiness Scale. Sleep. 14 (6), 540–545.

9. Netzer N. C., Stoohs R. A., Netzer C. M., Clark K., Strohl K. P. (1999) Using the Berlin Questionnaire to Identify Patients at Risk for the Sleep Apnea Syndrome. Ann Intern Med. 131 (7), 485–491.

10. Chung F., Yegneswaran B., Liao P. (2008) STOP Questionnaire: A Tool to Screen Patients for Obstructive Sleep Apnea. Anesthesiology. 108 (5), 812–821.