Asger Gitz-Johansen
61 lines
2.5 KiB
Markdown
61 lines
2.5 KiB
Markdown
# sleep-detection
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A small ML pipeline that turns wrist accelerometer + heart rate data into per-epoch sleep stage predictions (hypnogram building blocks).
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Built to support [InfiniTime PR #2304](https://github.com/InfiniTimeOrg/InfiniTime/pull/2304), which adds sleep tracking to InfiniTime (PineTime firmware) but stops at raw data logging.
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This repo explores whether a small offline-trained classifier can turn that raw data into sleep stages and eventually an on-device hypnogram.
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## Repo layout
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- `src/sleep_detection/` — data loading, epoching/features, model, training loop
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- `scripts/` — supporting/experimentation scripts
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- `plots/` — output plots
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## Datasets
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Not included in this repo — download separately:
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- [PhysioNet: Motion and heart rate from a wrist-worn wearable and labeled sleep from polysomnography](https://physionet.org/content/sleep-accel/1.0.0/) (Walch et al., 2019) — primary dataset used so far.
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- [PhysioNet: A Multi-Night Instantaneous Heart Rate and Accelerometry Dataset with EEG Sleep Stage Labels](https://physionet.org/content/bidsleep-dataset/1.0.0/) — larger, newer, same sensor modalities.
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<!-- - [PhysioNet: MMASH](https://physionet.org/content/mmash/1.0.0/) — 24h continuous HR + accelerometer + sleep quality, healthy adults.-->
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## Getting started
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This is just a regular python project. I recommend you work in an editable virtual environment during development.
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```sh
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cd sleep-detection
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python3 -m venv .venv
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source .venv/bin/activate
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python3 -m pip install -e .
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```
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The [uv](https://github.com/astral-sh/uv) project manager should also work just fine if you prefer to use that.
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### Datasets
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Not included in this repo, but a convenience download script exists. Note that this will take a while because the
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physionet servers are deliberately quite slow.
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```sh
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./download.sh
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```
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## Usage
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As an example training a model on the `sleep-accel` dataset subject `1066528`:
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```sh
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sleep-detection \
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-a physionet.org/files/sleep-accel/1.0.0/motion/1066528_acceleration.txt \
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-H physionet.org/files/sleep-accel/1.0.0/heart_rate/1066528_heartrate.txt \
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-l physionet.org/files/sleep-accel/1.0.0/labels/1066528_labeled_sleep.txt \
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--output model.pt
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```
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## Help Wanted
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I am not sure if the way I am feeding / dividing the training data up is done appropriately and if the model is too
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simple for this kind of dataset. I would love some help from someone who have experience and proper insight into how to
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train models using pytorch. Feel free to message me, submit an issue, fork the project etc.
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