Algorithm for Processing Measurements of External Respiration Parameters Using Motion Capture Systems

Introduction. In healthcare, breath analysis is increasingly used to detect diseases and monitor human health. Assessment of respiratory parameters, such as breathing frequency, is an important component in evaluating the overall state of the respiratory system. However, conventional methods, such as spirometry, have their limitations. Motion capture systems, such as marker-based video analysis, offer a promising and innovative approach for measuring respiratory parameters in conjunction with other investigations. This approach provides accurate data on respiratory activity without requiring specialized medical equipment. The use of such systems has the potential to significantly extend the scope of their application in rehabilitation and sports medicine. Aim. Development of an algorithm for determining breathing parameters using a marker-based motion capture system. Development of an algorithm for optimal body position and best marker locations for determining breathing parameters. Analysis of control measurements. Materials and methods. The data obtained as a result of synchronous recording of signals from an optical motion capture system and a spirometer were analyzed. The respiration rate was determined by spectral analysis and Fourier transform. Results. An algorithm for analyzing and interpreting respiratory rate was developed. This algorithm not only considers body positions and marker locations, but also provides recommendations regarding their optimal placement. Conclusion. The results obtained confirm the prospects of marker video analysis in assessing the frequency of respiratory movements using a motion capture system. Further studies will be aimed at taking physical activity into account with the purpose of developing effective diagnostic methods of external respiration parameters and respiratory disorders.

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Journal
Journal of the Russian Universities Radioelectronics
Published
2024-09-28
DOI
https://doi.org/10.32603/1993-8985-2024-27-4-91-102
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
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article

Algorithm for Processing Measurements of External Respiration Parameters Using Motion Capture Systems

A. N. Tkachenko, Anastasia Drozdova, I. A. Sakun, E. M. Skrebova
Journal of the Russian Universities Radioelectronics
Non-Invasive Vital Sign Monitoring
article

Algorithm for Processing Measurements of External Respiration Parameters Using Motion Capture Systems

A. N. Tkachenko, Anastasia Drozdova, I. A. Sakun, E. M. Skrebova
article en

Abstract

Introduction. In healthcare, breath analysis is increasingly used to detect diseases and monitor human health. Assessment of respiratory parameters, such as breathing frequency, is an important component in evaluating the overall state of the respiratory system. However, conventional methods, such as spirometry, have their limitations. Motion capture systems, such as marker-based video analysis, offer a promising and innovative approach for measuring respiratory parameters in conjunction with other investigations. This approach provides accurate data on respiratory activity without requiring specialized medical equipment. The use of such systems has the potential to significantly extend the scope of their application in rehabilitation and sports medicine. Aim. Development of an algorithm for determining breathing parameters using a marker-based motion capture system. Development of an algorithm for optimal body position and best marker locations for determining breathing parameters. Analysis of control measurements. Materials and methods. The data obtained as a result of synchronous recording of signals from an optical motion capture system and a spirometer were analyzed. The respiration rate was determined by spectral analysis and Fourier transform. Results. An algorithm for analyzing and interpreting respiratory rate was developed. This algorithm not only considers body positions and marker locations, but also provides recommendations regarding their optimal placement. Conclusion. The results obtained confirm the prospects of marker video analysis in assessing the frequency of respiratory movements using a motion capture system. Further studies will be aimed at taking physical activity into account with the purpose of developing effective diagnostic methods of external respiration parameters and respiratory disorders.

Journal of the Russian Universities RadioelectronicsVol. 27(4)
Saint Petersburg State Electrotechnical University (RU)
Openalex Percentile: Top 85%
Non-Invasive Vital Sign Monitoring
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