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RespiTrack - Respiratory patterns tracking Android App

Guy Berger and May Schwartz

Supervised by Alon Zvirin and Yaron Honen


A person’s breathing pattern abnormalities are serving a major role in detecting many human diseases like asthma, acute respiratory failure, heart failure and more.
Yet the detection and analysis of such pattern abnormalities isn’t yet as advanced as other advancements in medicine and in most of the cases is subject to human analysis by a human and thus involves 2 major drawbacks which we aim to solve:
Physical examination – the patient must arrive at a clinic and be examined physically by a medical staff member.
Human error – The diagnosis is made by a medical staff member and thus prone to human mistakes.
The work that is being done by the GIP (Geometric Image Processing) Lab at Technion university in Haifa is the development an innovative automated system and method to detect normal and abnormal breathing patterns by performing analysis of breathing pattern pathologies and abnormalities in chest movement.
In this project we develop an Android App that follows this methodology and aims to solve the drawbacks described above.

Project RespiTrack - Respiratory patterns tracking Android App Picture 1
Project RespiTrack - Respiratory patterns tracking Android App Picture 2
Project Report

Please, see project report.

Final Presentation

Please, see final presentation.


Please, see demo clip.

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