Converting iOS Health data export to CSV

I have over seven years of data collected through the Health app on iOS on an iPhone 5S. While I could use the QS app to extract it that does not provide a future-proof solution. It isn’t supported or maiintained any more and likely won’t be available once I update to an iPhone 14 in the next few weeks.

So I’m looking for a tool that can extract the relevant data to incorpoate it into a spreadsheet. Thought about pandoc which converts certain formatted documents to CSV sadly not XML files which is what Health exports its data to.Pointers to tools that I can use would be appreciated.

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The app built by our nonprofit does not yet have csv export but we are adding that within the next year. Currently, you can sync all your AHK data to the app. It is inspired by the QS model and a lot of effort has been put in to making this a tool that nearly everyone can use, no device limits. I welcome you to try that if you’re not able to find a good data conversion method otherwise.


Interesting will take a look but as my spreadsheet includes exercise data extracted (easily) from a GPS tracker (specifially the open-source GPX Tracker for iOS) I need some convenient way to combine all my QS datas together. Plus of course I want to create my own analysis.

I’m working on an app that allows xml import as well as combining different data sources. There is no Apple health template yet, so it may require some adjustments after import, but I’m happy to support with that. The tool has some integrated analysis but you can also just export the result as csv. If you want to try it out:

Hi! I am curious - what happens to the user’s data they input into your system? I read through your privacy policy and terms of use but did not find anything about data ownership in case of business downturn or acquisition in my review.

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The data is only processed locally, so it actually never leaves the users PC. It uses the browser storage to save the data. In case of switching device all data can be exported/imported.

Thank you!