Implementation of Machine Learning for Breath Collection

Paulo Santos, Valentina Vassilenko, Fábio Vasconcelos, Flávio Gil

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Economic and technologic progresses states the analysis of human’s exhaled air as a promising tool for medical diagnosis and therapy monitoring. Challenges of most pulmonary breath acquisition devices are related to the substances’ concentrations that are source (oral cavity, esophageal and alveolar) dependent and their low values (in ppbv - pptv range). We introduce a prototype that is capable of collecting samples of exhaled air according to the respiratory source and independent of the metabolic production of carbon dioxide. It also allows to access the breathing cycle in real-time, detects the optimized sampling instants and selects the collection pathway through the implementation of an algorithm containing a machine learning process. A graphical interface allows the interaction between the operator/user and the process of acquisition making it easy, quick and reliable. The imposition of breath rhythm led to improvements in accuracy of obtaining samples from specific parts of the respiratory tract and it should be adapted according to their age and physiological/health condition. The technology implemented in the proposed system should be taken into consideration for further studies, since the prototype is suitable for selectively sampling exhaled air from persons according to its age, genre and physiological condition.

Original languageEnglish
Title of host publicationBIODEVICES 2017 - 10th International Conference on Biomedical Electronics and Devices, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017
EditorsHugo Gamboa, Nathalia Peixoto, Ana Fred, Mario Vaz
PublisherSciTePress
Pages163-170
Number of pages8
Volume2017-January
ISBN (Electronic)978-989758216-5
Publication statusPublished - 1 Jan 2017
Event10th International Conference on Biomedical Electronics and Devices, BIODEVICES 2017 - Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017 - Porto, Portugal
Duration: 21 Feb 201723 Feb 2017

Conference

Conference10th International Conference on Biomedical Electronics and Devices, BIODEVICES 2017 - Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017
CountryPortugal
CityPorto
Period21/02/1723/02/17

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Keywords

  • Air Sampling/Monitoring
  • Average Time of Expiration
  • Breath Rhythm Imposition
  • Exhaled Air
  • Machine Learning Algorithm
  • Modelled Breath Algorithm
  • Selective Air Acquisition

Cite this

Santos, P., Vassilenko, V., Vasconcelos, F., & Gil, F. (2017). Implementation of Machine Learning for Breath Collection. In H. Gamboa, N. Peixoto, A. Fred, & M. Vaz (Eds.), BIODEVICES 2017 - 10th International Conference on Biomedical Electronics and Devices, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017 (Vol. 2017-January, pp. 163-170). SciTePress.