r/QuantifiedSelf • u/AutoModerator • 8d ago
Weekly Lifestyle Data and Analytics App Thread
Post your apps here, and please support people bringing unique ideas to this space.
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u/rjozefowicz 7d ago
as always I can share my apps for iOS:
- metrya.app (https://apps.apple.com/us/app/metrya-health-ai/id6760779874) - recently big update 2.11.0 with rewritten sleep and workouts and stress monitor. 2.11.6 just released with water logging, dark mode, BMI and weekly reports. users are being super active with sharing ideas so whole feedback (kind of roadmap is visible here https://www.reddit.com/r/MetryaAIApp/comments/1vmg22z/collected_metrya_feedback_what_users_want_on_the/ ). With Gemini API Key AI Advisor is effectively free to use. 2.11.7 coming this week with refreshed screen and improved UX
- longevityarc.app (https://apps.apple.com/us/app/longevity-arc/id6766045106) - 2.0.0 version is out and 2.1.0 with localization is coming
- deskwalker - walking pad and standing desk app - also next version 1.11.0 is coming very soon with Desk Blocks, Calendar suggestions, Siri, Shortcuts, energy check in and elevation setup
as always also I mention that these are side projects, no subscriptions. If you have any problem with BYOK or price is too high just DM me, I am fully ok to provide discount links
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u/No_Juggernaut_4526 6d ago
**Week Series – Garmin watch faces that visualize a week of your data as bar charts**
I made 6 free Garmin watch faces, each focused on a different health/fitness metric. Instead of showing just today's value, each face displays the last 7 days as a bar chart so you can see your week-long pattern at a glance on your wrist.
The 6 metrics:
- Heart rate (daily resting HR trend)
- Steps
- Calories
- Distance
- Sleep duration
- Body Battery
Each comes in dark and light versions (12 watch faces total). Free on Garmin Connect IQ, no subscription.
**Dark versions:**
- HRWeek: https://apps.garmin.com/apps/9bf62492-a3f5-4eea-a8d7-4a3cc057cc30
- StepWeek: https://apps.garmin.com/apps/73664855-8122-489d-98b9-b1bb7de67fc3
- CalWeek: https://apps.garmin.com/apps/abdc675e-be21-4401-9928-2ce4e668f655
- DistanceWeek: https://apps.garmin.com/apps/0f41c24b-a183-4374-b2bf-2490377b158e
- SleepWeek: https://apps.garmin.com/apps/743ca305-e39d-4afe-b3b6-a3a03b91c289
- BodyBatteryWeek: https://apps.garmin.com/apps/ffd29ec2-2387-45a1-8fd1-50c6c54ee2fc
**Light versions:**
- HRWeek Light: https://apps.garmin.com/apps/37fa3dc8-713c-47ba-8ba4-6761cc8bbdd1
- StepWeek Light: https://apps.garmin.com/apps/a48023b7-e8ef-4d91-bee0-bb3673ad06e5
- CalWeek Light: https://apps.garmin.com/apps/c4863bd7-fb7a-4190-81e9-62ba8fb677d7
- DistanceWeek Light: https://apps.garmin.com/apps/f1db3320-b365-4564-b77e-e1df08729505
- SleepWeek Light: https://apps.garmin.com/apps/4f4e9f39-e255-4a30-b9d1-a39f0377d3ad
- BodyBatteryWeek Light: https://apps.garmin.com/apps/368fed25-caa3-4d21-b478-4c6939008717
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u/Charming_Rush4571 8d ago
Always cool to see what people are building in this space, the variety is wild sometimes. I mostly track my football sessions and sleep, curious if anyone has something for logging training load without it becoming a second job
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u/Hot-Abies205 7d ago
[Tool] Obsidian Health Connect: Local-first biometrics synced to markdown dashboards.
Hey r/QuantifiedSelf! 👋
I built an open-source Obsidian plugin for anyone tracking biometrics in markdown or looking to own their personal health data locally without third-party cloud aggregators or monthly subscriptions.
What it does: Automated Syncing: Direct personal OAuth 2.0 connection to Google Health / Fitbit REST APIs, plus automated local drop-folder ingestion for Apple Health / iOS Shortcuts (100% local, zero middleman relay servers).
Tracked Biometrics: Sleep Stages & Scores, RMSSD Heart Rate Variability (HRV), Resting Heart Rate, SpO2, Skin Temp, Workouts/Active Minutes, and Nutrition/Hydration written directly into your daily note frontmatter.
Interactive Dashboard: Embed a health-dashboard block in any note to render theme-matching KPI cards, rolling 7/30-day averages, zero-dependency SVG sparklines, and multi-metric comparison graphs.
Custom Calculated Metrics: Define spreadsheet-style math formulas combining raw biometrics (e.g. customized Cognitive Readiness formulas, strain indices, or macro calorie calculations: (protein * 4) + (carbs * 4) + (fat * 9)) that evaluate and write back to your notes.
Food & Beverage Logger: Interactive visual meal logger with presets and serving sizes that syncs bi-directionally with Google Health.
GitHub & BRAT Setup Guide:👉 https://github.com/jare0014/obsidian-health-connect
Would love feedback from fellow QS trackers on additional metrics, formula hooks, visualizations, and feedback on in general!
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u/yashrocky 7d ago
I've been building a Windows app around a question I've found surprisingly difficult to answer accurately:
Where did my time on the computer actually go?
Not in the productivity-score sense, and not for employee monitoring. Just a personal record of how I spent my time.
Manual tracking never worked well for me because I would forget to start and stop timers. So Focus automatically records computer activity and builds a visual timeline of the day.
The part I'm most interested in is what happens after enough data builds up. A single day can be interesting, but patterns across days or weeks could potentially answer questions like:
- Where does most of my time actually go?
- What applications or activities consistently take more time than I realise?
- Did I change how I spent my time after trying to improve something?
The data stays local on the device. No account is required, and it's free for personal use.
Focus is currently in beta, and I'm looking for early users and feedback from people who are interested in personal data and self-tracking.
———
What would make desktop activity data genuinely useful to you over the long term, instead of just being interesting to look at once?
Focus: https://ripplestudios.app/
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u/louislubin 7d ago
Still Cloud is literally the place you quantify the self. You can tell it about yourself. Literally anything you can think of and it will log it. Super easy to use, you can use voice, text, images to bring everything about yourself together. Not only that but it understands your personality and patterns and gets better over time as you use it. If you’re interested in the beta testing dm me and I’ll hook you up with a coupon for 30days premium free
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u/SudoSleepWell 7d ago
Full disclosure: I built finit: https://getfinit.com
I made it because iOS only keeps a limited amount of detailed Screen Time history. finit saves the iPhone’s own per-app Screen Time data day by day, so over time you can compare weeks, months, years, and all time.
It doesn’t block apps or use a VPN or always-on background tracker. The data stays on your device and in your private iCloud.
On first setup, it can import the recent weeks that iOS still remembers, but it can’t recover older data Apple has already discarded.
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u/LM_Reader_Dev 7d ago edited 7d ago
Lecturameter! A reading habit tracker
Its main pourpose its to time tour reading session, get stats about them and start building a comprehensive profile about you as a reader throughout stats.
Additionally it has:
- Compatibility with CSV coming from any other app (mainly Goodreads and StoryGraph) or your own CSV
- Five different shelves to organize your books
- Fully functional book search via online and offline catalog
- Tons of stats: including a monthly and an hourly heatmap, several charts, a weekly summary and a yearly Wrapped report at the end of the year
- Custom challenges. Including a daily challenge
- Two bingos: 4x4 and a harder 3x3 for Pro users
- Two types of timers: normal and inmersive for Pro users
- Five different themes: Clear, Dark (both free), Aurora, and Leather (Pro)
- A different app icon for Pro users
- 7 days free trial with no card needed. When it ends you get one Pro theme of your choice for free
- Pagi, the mascot of the app! Will guide you through the tutorial and onboarding tips
- Local and Cloud backup of all your library
- Two widgets: the book widget where you can see your progress in one book and the monthly comparison widget (Pro) where you can see a comparison of the stats of this month compared to the last one
What I'm planning next:
- iOS version
- Compacted book details
- Shareable book cards
- Shareable closing moments with Pagi (the app mascot)
- Your "reading universe", a more "universal" approach to your all-time stats
- Half stars
- Reading reminders
- Support for more languages (currently the app only works in English and Spanish)
- Previewing your imported data
- Edge and spine photos at the sides of the books cover
- Dusk theme a mix of warm and cold colors
- Tag system
- Some other small QoLs to make navigation and use smoother
Edit: Formatting and I are mortal enemies
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u/thedatawhiz 4d ago
How do you log what and when are you reading? This is unclear
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u/LM_Reader_Dev 4d ago edited 4d ago
You have a big + button to add a book, then you simply start a timer or add a manual session entering book details by taping the book in your library.
I'll add a tip on how to log your readings, maybe I've gotten so used to it that people don't know how to do it, but I think it's clear
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u/thedatawhiz 4d ago
Sure, because I'm looking at automated systems to do, I'm exactly avoiding the big + button
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u/LM_Reader_Dev 4d ago
You shouldn't avoid big buttons hahaha. Anyway I'll make sure to add a new tip for that :)
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u/Public-Geologist-866 6d ago
https://reddit.com/link/p5zo1qd/video/97ayze8zjplh1/player
How I track my piano practice on WeekOS 🎹
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u/RateEmbarrassed6921 6d ago
FitMesh Sync, Android and iOS. It reads what your devices have already written to Health Connect or Apple Health and reconciles them into one day.
The three rules it is built on, since this sub cares about method more than features:
Every number carries the device it came from. Not in a settings screen, on the number itself. If your step count came from your phone rather than your ring, you can see that without going looking.
Sources are ranked per metric, never blended. A chest strap wins heart rate and does not compete for steps. Inside a time bucket the higher priority source wins outright and the other only fills gaps, because averaging one good reading with one bad one gives you a mediocre reading and no way to tell afterwards which parts were which. You can override the order yourself per metric, which matters more than I expected, because people know things the ranking cannot, like that they leave their phone on a desk all day.
Quantities that are not the same quantity never share an axis. Apple Health gives you SDNN, Health Connect gives you RMSSD. Same wrist, same night, different measurements. Ranking those against each other would be picking a winner between metres and feet.
The honest limits, since you will find them anyway. There is no confidence weighting inside a bucket, it is a fixed order rather than a model that notices a source has been behaving oddly all week. And ranking solves disagreement about a value while doing nothing for disagreement about an event: if two sources agree it was sleep and disagree about when it started, there is no number to choose between. That boundary problem is the part I am least happy with.
Servers are in the EU. Fourteen day trial, then either a one time unlock or a subscription, whichever you prefer. Solo developer, and most of what is in it now came from people in threads like this one telling me what was wrong with it.
Site: https://www.fitmesh.fit/en Android: https://play.google.com/store/apps/details?id=com.fitmeshsync.app iOS: https://apps.apple.com/app/fitmesh-sync/id6779751708
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u/jdbloodstone 4d ago
I built HealthAPI: an iPhone app that syncs Apple Health into a personal REST API, so I can query years of sleep, HRV, workouts, and steps from curl or an AI instead of exporting XML. HealthKit access is read-only, and iPhone + Watch totals are de-duplicated so the numbers match the Health app. 7-day free trial, then a subscription (Pro $4.99/mo, Developer $9.99/mo). Not medical advice.
App Store: https://apps.apple.com/us/app/healthapi/id6770383795
Docs: https://healthapi.app/docs
Curious what metrics this community would actually want in a daily summary that I have not exposed yet.
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u/Team_Vora 3d ago
We build Vora, and we recently redesigned blood-work tracking around longitudinal context rather than one-off interpretation.
Each result stays connected to its source report, can be reviewed across time, and can be viewed beside nutrition across 95 micronutrients, supplements, activity, sleep, glucose, blood pressure, and wearable data. We are deliberately trying to show useful context without implying causation or diagnosis.
The visual walkthrough is here:
https://www.reddit.com/r/vorahealth/comments/1w1hok1/blood_work_should_stay_useful_after_you_close_the/
For people doing self-tracking, which adjacent data is actually useful when reviewing a lab trend, and which connections create more noise than signal?
Disclosure: We build Vora. This comment was prepared with AI assistance and reviewed and approved by Team Vora. Illustrative data only. Vora does not diagnose or replace a clinician.
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u/Prestigious_Day5414 3d ago
Solo dev here, been building Simple Health (iOS): it reads Apple Health data and explains it in plain language instead of another dashboard.
The part I think this sub would actually care about is the dedup, not the AI. HealthKit does not dedup across sources: if your sleep gets written by both your phone and your watch, or a workout gets logged by two apps, Apple Health just shows you two overlapping entries. Sleep is elected per block (preferred source, else whoever has stage data, else whoever has the most minutes), then grouped into nights by chaining fragments that are close together in time, since a short resumption after waking used to get misread as its own night and steal the real one. Workouts and mindful sessions dedup on over 50% time-overlap between sources, keeping the richer or longer entry.
On the AI side you get a choice: run it on-device (Apple's on-device model, nothing generated server-side) or send it to a cloud model for a sharper writeup. HealthKit access is read-only either way, and anything the app remembers about your patterns (night owl, weekend sleep debt, whatever it's picked up) is a visible list you can edit or delete, not a black box.
Free to download, core tracking is free, the AI features are a subscription with a trial.
Not live yet so don't go looking for it, but the next thing I'm shipping is three deterministic day-scores kept deliberately on different scales: Recovery as a percentile against your own history, Rhythm using fixed regularity anchors instead of your own spread (so a chronically irregular sleeper doesn't get graded on a curve that congratulates the irregularity), and Effort as a same-weekday fill ratio rather than a percentile, since effort is supposed to climb through the day, not compare to a fixed target.
App Store, if you want to look: https://apps.apple.com/app/id6773782403
Curious for this crowd: does a fixed-anchor regularity score, one that never adjusts to the user's own baseline, read as more honest to people who actually think about this stuff, or does it just read as broken?
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u/Acrobatic-Riri 1d ago
I made an open-source attempt to reconcile conflicting wearable data before giving it to an AI for query/analysis
Hi all! As a fitness-obsessed data nerd, I built this after running into a problem with using multiple trackers (Oura+Garmin watch and chest strap form me). They often produce overlapping or contradictory observations, and simply giving all of them to an LLM can be confusing and not as meaningful as it could be. And I know many of you here have this problem or are trying to solve this too.
MetricBraid puts a reasoning layer in between the wearable data and the AI. The underlying approach is informed by independent scientific research on wearable-device validity and measurement error, rather than assuming that one brand/device is always the most reliable. Different devices and sensor types can perform differently depending on the metric, activity, body location, signal quality and context. In other words, a device that is useful for one measurement is not automatically the best source for every other measurement.
MetricBraid tries to reflect that by treating source selection as a measurement-specific reasoning problem:
- deduplicates overlapping events
- routes different measurements to the most appropriate available sensor
- considers the measurement context and the known strengths and limitations of different sensor types
- separates "which source should I use?" from "how trustworthy is this measurement?"
- preserves provenance so the AI can explain where a number came from
- leaves conflicts unresolved when there isn't a defensible winner
The goal is to make the AI's assumptions explicit and evidence-aware, while preserving uncertainty when the available data doesn't justify a confident conclusion.
The routing model is device-agnostic, although the bundled integrations currently cover Oura and Garmin. It can also work with exports/local data and other agents or integrations.
It's open source and currently v0.2.1:
https://github.com/drleahzou/MetricBraid
I'd particularly like feedback from people using two or more wearables.
What combinations of devices or real-world edge cases do you think would break this approach? And any other thoughts are super welcome! Thanks in advance!
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u/Content-Two5729 1d ago
Android supplement + sleep tracker — looking for 20 people for a 14-day test
Hi — I’m the indie developer behind PerunForce, a Polish Android wellness app built for people who want supplements, food, sleep and recovery in one place rather than in separate notes and spreadsheets.
The current app lets you:
• build a supplement stack with exact form, dose, timing and reminders
• track adherence, stock, shopping and estimated costs
• log food, calories, macros and available micronutrients
• keep sleep, caffeine, hydration and recovery notes together
• optionally read compatible activity, sleep and body data through Health Connect
I’m looking for up to 20 Android users who already take several supplements and care about sleep or recovery.
The test is simple: use the app for 14 days, keep your normal routine, and tell me where logging becomes useful — or annoying. The goal is not to claim that a supplement caused an outcome. It is to see whether structured records make adherence and personal patterns easier to review without relying on memory.
As a thank-you, active testers who send concrete feedback can receive 1–2 months of Pro. This is for feedback, not for a positive review.
Website and Google Play link:
https://perunforce.com/?utm_source=reddit&utm_medium=community&utm_campaign=quantifiedself_14day
I’d especially value criticism from people who already use Garmin, Samsung Health, Amazfit/Zepp or another Health Connect-compatible source.
Disclosure: I’m the developer of PerunForce. It is a wellness/organization tool, not a medical device and not a replacement for professional advice.
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u/hibbos 1d ago
Hi, I built Dosette because I kept running into a basic problem with supplement tracking: knowing that you took something is not the same as knowing whether it helped.
Most trackers compare days you took a supplement with days you missed it. I don't think that is very useful. Missed doses tend to happen when you're ill, travelling, or your routine is off, which can make almost anything look effective. Some supplements also take time to work or remain in your system after a missed day.
Dosette handles this by comparing stretches of at least seven days on something with stretches of at least seven days off. Each stretch counts as one block, so a six-week period doesn't drown out a shorter one. Confidence never goes above moderate, and if there isn't enough history, the app says so.
You can track your own daily ratings or selected Apple Health measures. It also logs medicines, but it never suggests stopping or experimenting with prescribed medication. There's no account and no advertising, and the log stays on the phone.
It's available on iOS here:
https://apps.apple.com/us/app/dosette-supplement-tracker/id6744556682
I'd be interested in how people here would approach the block length. Is seven days a reasonable default, or should it change depending on what you're tracking?
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u/Plastic-Key-9907 7d ago
Solo developer here — no company, no funding, just me building Plena (iOS + Apple Watch, beta): a meditation/recovery app. The part this sub might actually care about is the HRV methodology: the daily signal is your overnight SDNN median against a 30-day overnight-only baseline. No overnight data? It falls back to recent nights, then background resting samples — and every reading is labeled with where it came from ("Last night", "Earlier today"). It refuses to compare across domains: a 2pm resting sample never gets diffed against a sleep-only baseline, since that mostly measures time-of-day, not recovery. When there’s no honest comparison to make, it says so instead of making one up.
Data stays on device — no servers, no SDKs, App Store label is genuinely "Data Not Collected". Premium is free during the beta. Looking for Series 4+ testers who’ll wear the Watch to sleep a few nights and poke holes in the methodology: https://testflight.apple.com/join/6E3qPV4f