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