Slack Channel Vayu Shakti


As a person with respiratory problems , I want a predictor/early warning tool  to help me prepare and adapt for different  to manage my condition better. This tool should 1. Capture my condition via self reporting and/or output of inhalation ; respiratory tests (FPV); Activity level / my oxygen saturation level; heart rate; self reported information (cough, physiotherapy) 2. Self reported qualitative input via a dairy (cough levels, sleep quality, physiotheraphy levels)3. Possibly combining data input from common activity apps (garmin, strava, smartwatches ) with the others listed data input to create a combined data view. 4. Monitor/record various climatic parameters ((meters/hours, oxygen concentration/temp./pressure/density)5. Have ability to enter climatic conditions (for artificial / micro climates like airplanes)6. Draw a historical relation of data ; co-relations and predict ahead of time with something like a score so that I can prepare. 7. A gamification element to encourage participation and active use of the solution / app either individually or as a group activity for mutual support/feedback. 8. Possibly a feature around medication reminders.

Thematic Area

4 -Measuring Causal Factors

Patient Champion

Champion S.S (5)

Team Composition would benefit from

UX design, human factors expert, web/ mobile app developer,  data-scientist, respiratory  (pneumologist)



08.11.2020 12:00

Hackathon finished

23.10.2020 12:00

Hackathon started

22.10.2020 22:14


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22.10.2020 20:56


Worked on by giovanni_nisato

22.10.2020 20:46


Readme fetched from source by giovanni_nisato

22.10.2020 20:46

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22.10.2020 20:46

Project started

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4. Measurement of causal factors

Today you may feel fine, but tomorrow you may feel it is the worst day of your life. What changed? Is it something you did or is it something that happened to you? These are questions that patients ask themselves all the time. What external and internal factors influence my well-being? These factors may not always be obvious, such as, for example, the weather. Patients would like to be able to measure these influences automatically and match them to their subjective well-being. This could provide them with deeper insight into their situation while also providing an unbiased (e.g. without flaws of memory) overview of the course of their disease, which could support them in meetings with HCPs.

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