Personal Dashboards for Self-Tracking Data

Thanks very much for the kind words and feedback! Also, apologies for the late reply. First time posting on this forum, so we missed all the notifications.

Noted down your comment about Factors during onboarding, we’ll make sure to look into how we can make the purpose of Factors more explicit for new users.

If you have any more feedback or anything else for us, please feel free to connect with us in the following ways:
• Our community on Reddit
• Our community on Element (similar to Discord, but privacy-focused)
• Shooting us an email hello@metriport.ai

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Very happy to hear that you are getting use out of it, and our apologies for the late reply! We missed all the notifications here as it was our first time posting.

Regarding the widgets for single numerical entries, I can see you’ve already found the items on our roadmap:

We definitely still have a long way to go with interoperability between different data integrations, but will be expanding on this significantly in the near future. Noted down the possibility of screen time on different apps, would be interesting to see how that affects sleep for sure and we’ll give this some thought. Would be great to chat regarding any further suggestions/ideas you have going forward, so we will make sure to keep in touch!

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Answer @agaricus
Platform risks assessment.
There is a stable world trend - the protection of personal data.
The sale of button phones is increasing.
Probably 50% of consumers of mobile devices will be indifferent to the safety of their personal data
However, an increasing number of consumers begin to protect personal data.
Promising solutions should store all data on the user’s devices and protect them with encryption.
The use of blockchain in startups is expensive.
Rarely, anyone in this forum mentions the safety of services.

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Hey all! I’m one of the folks building Cambrean - we’re building a biometric home for everybody. Think of it like a wallet for your health data.

We’re focussed on figuring out why your metrics are changing through centralizing both contextual & biometric data. I’m happy to chat with anyone who is interested in trying it out.

DMs open

Hi everyone,

I’ve always been impressed by the tools and dashboards that Quantified Self community have built to track and understand themselves. Like many of you, I’ve also tried building my own tracking and journaling tools for my mental well-being, but I found the process of tracking to be tedious. I believe that tracking should be effortless, like using Agaricus’s one-button tracker (thread) or a device that works in the background like a FitBit.

As a designer who has worked in e-commerce, I’ve also seen firsthand how big tech companies use our data to manipulate our behavior. I started wondering if there was a way to put that vast amount of data to good use for our own well-being. This led me to this wonderful Quantified Self community and the realization that a lot of problems can be solved through understanding our own behavior.

Inspired by Kelly_Finn 's comment and Wolfram’s Personal Analytics, I’ve been working on a tool that allows you to store, organize, and understand your digital footprint from a single place, using data exported from apps like Facebook. The tool also offers personalized reports and dashboard to empower you to take action on your own well-being.

I would love to get your feedback and thoughts on this project, and if you’re interested, you can sign up for early access on the landing page. Hopefully, I’m heading in the right direction.

Thipok.

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This is amazing. We need someone like you to help our founder at the nonprofit LLIF.org. Thanks for building something with a goal of helping people understand their data value, instead of pilfering it for your own intentions like for-profits have the habit of doing.

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I signed up for early access. (I have a project I’ve always wanted to do but haven’t quite gotten the momentum to attempt: Analyze my Twitter Follows/Unfollows to see how my interests have changed, and better manage what I’m influenced by.)

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I saw you gave up on the project, would be amazing if you could contribute to the community and make the APPs open source !

Very interesting project ! Even more so that you claim data is stored locally, so +1 for privacy and security.
Would be interesting to see this open-sourced or at least allowing for users to contribute open-source modules for integrations they needed akin to what happens with HPI, Nomie or more simply Logseq !

Finally, I think you would benefit of communicating/joining forces with: ChatAnalytics since it is open source.

Why do you think they gave up?
I saw no announcement about that, and there’s still recent activity in Github: GitHub - metriport/metriport: Metriport is an open-source universal API for healthcare data.

So what happened is that they stopped updating the app since July 2022.
They did not give any kind of updates to the community until various users posted on their subreddit what the future of the app was:

Besides, around Oct 2022 users found for themselves that the Metriport site changed completely and that they were changing the project to “going toward an Universal API for Healthcare Data,”, with still no update from the team.

Only in December 2022, Metriport team decided to post an update in their subreddit explaining that they gave up on the app and completely changed the project to be an open-source Health API (An update from the Metriport team - r/metriport).
So yes, what you see in their Github is the Metriport project that was converted into the API, but the app and their users (who paid) were completely ignored. The app still can be found in google play: https://play.google.com/store/apps/details?id=com.metriport.metriport

My only hope is that, since the app is no longer being developed, they at least open-source it to give back to the community since it was well built !

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Thanks for the informative reply and sorry I missed the discussions on reddit.
I totally agree that open sourcing it will be great

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Hi everyone!

Several months ago, I got inspired by @Agaricus and his participation to the Dataframed podcast, and I’ve since been working on creating my own personal life dashboard in PowerBI, where I track all sorts of things about my daily life.

I’ve written an article (A step-by-step guide to building your personal life dashboard | by Valentin Herinckx | Aug, 2023 | Medium) to share my insights and I’d be delighted to get some feedback from the community on it!

If you plan to use some of the sources I used in my journey, you can find all the python code I wrote in this GitHub repo: GitHub - VaHerinckx/LifeLog_Project

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Thanks.

I think you have solved a problem for me with your apple_processing.py script. Been wanting to extract items from my Health app exports without needing to use an external web site to unpick the XML.

Although looking through the source I am intrigued by the call on sed to delete specific lines from the exported Health app data, viz

sed -e ‘156,211d’ …

as those lines in my export are right in the middle of data that I am interested in extracting for my quantification. What is it you are trying to remove there as I don’t want to lose anything that is useful to me.

But I did spot there are data entries that I had not realised was in there namely

HKQuantityTypeIdentifierFlightsClimbed and HKQuantityTypeIdentifierWalkingSpeed

I probably should go re-read the HealthKit document more closely as there may be other relevant (to me) data previously overlooked.

Cheers.

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@glimfeather glad the code could help!
The reason I’m removing those rows is because, for some reason, the .xml file I receive from apple seems to be corrupted, and those rows were making my code bug.

I’m not an .xml file expert, but it seems like the row numbers don’t match from one person to another, as they can contain information or not based on what your Iphone stores about you. In my case, those were empty rows about glasses prescription. If the code is running without removing them for your files, I think you can leave them in!

@Valentin_Herinckx thanks for the response. I can quite forsee why certain data lines might cause problems.

At the moment I only use a few of iOS Health app’s data items can generate/store. For “fun” I looked at the user Summary to Edit Favourites then selected All to get a complete list of what can be stored. Some of the items indeed entire categories are irrelevant for me — Cycle Tracking, for example, I do not need as there is no risk of my ever becoming pregnant because well I’m male.

I speak XML fluently. :crazy_face:

Not only would the lines change from one user to another (depending upon what specific data is being collected) but they do change from device to device. I can see at a glance which lines originate from the various iPhone models I have owned although the keys of the items remain the same.

On the sed line it might be better to find out what those lines contain and then search explicitly for the the type/key by name. I’m no expert on sed but have found loads of useful documentation around the web; some of it very cryptic.

Following up on my most recent response here I stumbled across an interesting domain using Apple Health (as an exemplar) in their work. Namely forensics! Trying a naïve DuckDuckGo search of “sql apple health” had found me this conference/academic journal paper https://www.sciencedirect.com/science/article/pii/S2666281723000057 on using workout tracking data stored in Apple’s Health app database to verify an alibi. The paper is focused on retaining vital forensic evidence some of which can be lost when using the app’s export function. Apparently timezone data is lost/normalised to GMT. For my usage that isn’t an issue.

Also highlighted some interesting uses of workout data with one of the paper’s authors using the “Rowing” category to record his “bell ringing” activities. I can see why he might make that lateral leap rowing is pulling horizontally and bell ringing pulling vertically. Although the variability of GPS tracking could put a perp merely in the vacinity of a crime not at its exact location.

The mentioned repurposing of workout categories started me thinking whether there are any others that I might repurpose to support my quantified self. The idea has somewhat tempered my hold out for buying an Apple Watch only when it includes on board blood pressure monitoring with the immediate possibilities of tracking my exercise (primarily walking). Also thinking that maybe ovulation data’s “hot flushes” subcategory could be useful in tracking the side-effect of some of my medication and whether is a correlation with any of my regular activities. (Anecdotally it feels like the hot flushes are worse in the mid to tail end of a course and less frequent immediately after a new course has been administered.) Being male ovulation tracking had really been of no interest to me plus I thought it a risky form of family planning but this paper has sparked my imagination.

Looks like I need to read the Halth Kit documentation in greater detail — only given it the most cursory of glances to date — to see what (other) lateral moves there could be achieved by reuse.

Hi @alexey, I’m just out of highschool and am now going down the rabbit hole of QS. Your personal site it amazing and by far the best looking design i’ve seen so far. Would you be able to send me some details of how you have done this or share a link to your git if possible? Honestly, I’m shocked that anyone could make something this polished for a personal project!

Finally bit the bullet and bought myself an Apple Watch 9 with a Withings blood pressure monitor. For some months have been using the Health app on my iPhone. With the upgrade to iOS 17 and iPadOS 17 I am becoming frustrated with the Health apps’ display method. Great to see the individual items but I want them plot together so I can see if there is a cause for a spike in my blood pressure or why side effects of some medication are now reducing. Difficult to do any of that when essentially what one is presented with a list of discrete readings.

The more I look at Apple’s Health app presentation the more I dislike it. The most recently updated categories are sorted to the top of the list (Summary > Show All Health Data) which means I never know where to look for the item thta interests me.For example, when I have a Hot Flush — it’s a well documented and common side effect of some of my medication — this most-recent-first causes a hunt for Hot Flushes ready to add a data point and some times, such as today, it isn’t in the list but is on the Yesterday list instead.