PulseClean
Clean wearable health data into analysis-ready CSVs
What it does
PulseClean converts messy Apple HealthKit exports and wearable CSV files into clean Standard Schema CSVs ready for analysis in Python, R, Excel, or BI tools. Start free with 3 jobs per month, no credit card required.
Does the same job
all alternatives →- AHApple Health MCP Server2025 · github.com · ▲199
Hey HN, This is an MCP server to chat with Apple Health data. I built it because I'm working on (yet another) personal trainer tool that keeps track of my workout goals, etc. and does scheduling for me. Part of that is weekly check-ins. I thought pairing those check-ins with sensor data could be useful, so here we are. It seems there isn't a way to automate access to Apple Health data, so this relies on an iOS app that can quickly/easily export key data to CSV. So the process at the moment is to export the data every Sunday before doing a check-in. More steps than I'd like, but in…
- EHExport Health – Easily export your Apple health data to JSON or CSV2020 · exporthealth.app · ▲21
- VYVisualize your Apple Health data in Grafana2023 · github.com · ▲42
Hi HN, I made a tool for displaying your Apple Health data (activities, workouts, body metrics) and display them in Grafana to be manipulated, aggregated etc. It's useful for finding trends, get daily/monthly/yearly stats and visualize outdoor routes on a bigger screen !
- AHAidlab – Health Data for DevsOct 2025 · ▲59
Hey HN! I'm Jakub, and together with my co-founders Agnieszka and Nathan, we built Aidlab, a wearable that gives developers gold-standard physiological data. Unlike health trackers with locked-down APIs, Aidlab ships with a free SDK [1] across 6+ platforms so you can just pip install aidlabsdk or flutter pub add aidlab_sdk or whatever platform (even Unity), and start streaming raw health data and events in real time with simple didReceive*(timestamp, value) callbacks. Currently, we are exposing 13 data types including raw ECG, cough/snoring, motion, raw respiration, skin temperature,…
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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