| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - time-series-forecasting |
| - other |
| language: |
| - en |
| tags: |
| - ppg |
| - photoplethysmography |
| - heart-rate |
| - ecg |
| - physiological-signals |
| - biosignals |
| - wearable |
| - multisite |
| - earring |
| - ring |
| - smartwatch |
| pretty_name: Multisite PPG Dataset |
| size_categories: |
| - 10G<n<100G |
| --- |
| |
| # Multisite PPG Dataset |
|
|
| A multisite photoplethysmography (PPG) dataset: long-duration recordings from four body locations, synchronized activity logs, and ECG-derived heart-rate ground truth. It supports PPG-based HR estimation, signal-quality assessment, motion-artifact handling, and cross-site generalization research. |
|
|
| For data preprocessing and baseline training code, see our GitHub repository: [anonymous-ppg/wearable-ppg-dataset](https://github.com/anonymous-ppg/wearable-ppg-dataset). |
|
|
|
|
| --- |
|
|
| ## At a glance |
|
|
| | | | |
| | --- | --- | |
| | **Approx. size** | ~18.6 GB | |
| | **Participants** | 20 (`P1`–`P20`) | |
| | **Setting** | Multi-day, free-living | |
| | **Wearable sites** | Earring, Necklace, Ring, Watch | |
| | **Wearable modalities** | Green PPG, IR PPG, 3-axis accelerometer, skin temperature | |
| | **References** | Polar H10 ECG + 3-axis accelerometer | |
| | **HR ground truth** | From synchronized Polar ECG (Pan–Tompkins + additional cleaning) | |
|
|
| ### Sampling rates |
|
|
| | Source | Signals | Rate | |
| | --- | --- | ---: | |
| | Wearable | PPG, accelerometer, temperature | **100 Hz** | |
| | Polar | ECG | **130 Hz** | |
| | Polar | Accelerometer | **25 Hz** | |
|
|
| --- |
|
|
| ## Repository layout |
|
|
| Three main components ship in this repo: |
|
|
| | Path | Role | |
| | --- | --- | |
| | `raw_data/` | Raw wearable streams, Polar references, activity logs | |
| | `ppg_windowed_data/` | 8 s windows aligned with ECG-derived HR labels | |
| | `sample_data/` | Tiny subset for format checks / tutorials | |
|
|
| Top-level tree: |
|
|
| ```text |
| Multisite-PPG/ |
| ├── raw_data/ |
| ├── ppg_windowed_data/ |
| ├── sample_data/ |
| ├── .gitattributes |
| └── croissant.json # ML Croissant metadata |
| ``` |
|
|
| --- |
|
|
| ## raw_data/ |
| |
| One folder per participant: wearable files at four sites, Polar references, and an activity log. |
| |
| ### Wearable: `P<N>_<Site>_raw.npz` |
| |
| `<Site>` ∈ {`Earring`, `Necklace`, `Ring`, `Watch`}. |
| |
| Each file holds timestamped green + IR PPG, 3-axis accelerometer, skin temperature, and alignment metadata for Polar. |
| |
| ### Polar references |
| |
| | File | Content | |
| | --- | --- | |
| | `P<N>_polar_ecg_raw.npz` | Polar H10 ECG | |
| | `P<N>_polar_accl_raw.npz` | Polar H10 3-axis accelerometer | |
|
|
| ### Activity log |
|
|
| `P<N>_activity_log.txt` — timestamped labels as `start <label>` / `end <label>` pairs. |
|
|
| --- |
|
|
| ## ppg_windowed_data/ |
|
|
| Pre-windowed segments per participant and site, aligned with ECG-derived HR. |
|
|
| ```text |
| ppg_windowed_data/ |
| ├── P1/ |
| │ ├── alignment_windows_P1_Earring.npz |
| │ ├── alignment_windows_P1_Necklace.npz |
| │ ├── alignment_windows_P1_Ring.npz |
| │ └── alignment_windows_P1_Watch.npz |
| ├── P2/ |
| │ └── ... |
| └── P<N>/ |
| └── ... |
| ``` |
|
|
| Each `alignment_windows_*.npz` includes: 8 s wearable PPG windows, motion channels, aligned ECG reference, ECG valid length, and HR labels. |
|
|
| | Parameter | Value | |
| | --- | ---: | |
| | Window length | 8 s | |
| | Stride | 1 s | |
|
|
| --- |
|
|
| ## sample_data/ |
| |
| Same layout as `ppg_windowed_data/`, but small enough for quick inspection without pulling the full release. |
| Details in its own readme. |
| |
| --- |
| |
| ## Quick start |
| ### Install |
| ```bash |
| pip install huggingface_hub numpy |
| ``` |
| ### Download dataset |
| **Sample only** (~1.4 GB): |
| |
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="anonymous-ppg-dataset/Multisite-PPG", |
| repo_type="dataset", |
| local_dir="multisite-ppg-submission", |
| allow_patterns="sample_data/*", |
| ) |
| ``` |
| |
| **Full dataset** (~18.6 GB): |
| |
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="anonymous-ppg-dataset/Multisite-PPG", |
| repo_type="dataset", |
| local_dir="multisite-ppg-submission", |
| ) |
| ``` |
| |
| --- |
|
|
| ## Loading in Python |
|
|
| ```python |
| from pathlib import Path |
| import numpy as np |
| |
| # Example file: |
| # Multisite-PPG/ppg_windowed_data/P1/alignment_windows_P1_Earring.npz |
| npz_path = Path("Multisite-PPG/ppg_windowed_data/P1/alignment_windows_P1_Earring.npz") |
| |
| with np.load(npz_path) as z: # allow_pickle=False by default |
| ppg_green = z["ppg_green"] # (N, T) |
| ppg_ir = z["ppg_ir"] # (N, T) |
| hr_gt = z["hr_gt"] # (N,) |
| t0_ms = z["t0_ms"] # (N,) |
| t1_ms = z["t1_ms"] # (N,) |
| ppg_fs = float(z["ppg_fs"]) # scalar, typically 100.0 |
| ecg = z["ecg"] # (N, Lmax), zero-padded |
| ecg_valid_len = z["ecg_valid_len"] # (N,), valid ECG samples per window |
| accel_x = z["accel_x"] # (N, T) |
| accel_y = z["accel_y"] # (N, T) |
| accel_z = z["accel_z"] # (N, T) |
| |
| print("ppg_green:", ppg_green.shape, "hr_gt:", hr_gt.shape, "ppg_fs:", ppg_fs) |
| |
| # Example: recover valid (unpadded) ECG for one window |
| i = 0 |
| ecg_i = ecg[i, : int(ecg_valid_len[i])] |
| ``` |
|
|
| - Use `ppg_green` or `ppg_ir` as model input windows. |
| - Use `hr_gt` as the heart-rate label aligned to each window. |
| - Use `ecg_valid_len` to remove right-side zero padding from `ecg`. |
|
|
| --- |
|
|
| ## Intended uses |
|
|
| - PPG-based heart-rate estimation under motion |
| - Signal-quality assessment and artifact detection |
| - Cross-site generalization and multisite wearable modeling |
| - Benchmarking preprocessing and representation learning on biosignals |
|
|
| --- |
|
|
| ## Limitations |
|
|
| - Free-living recordings: not strictly gap-free continuous sessions. |
| - Motion artifacts and low-quality segments occur naturally. |
| - Activity labels are user-logged and sparse, not exhaustive. |
| - **Not** validated for clinical decision support. |
|
|
| --- |
|
|
| ## Ethics and anonymization |
|
|
| Participant IDs are replaced with codes (`P1` … `P20`). This release does not include personally identifying information. |
|
|
| --- |
|
|
| ## License |
|
|
| Released under [**CC BY-NC 4.0**](https://creativecommons.org/licenses/by-nc/4.0/) (Attribution–NonCommercial). |
|
|
| **Allowed:** non-commercial research and education; derivative preprocessing with attribution. |
|
|
| **Not allowed without separate permission:** commercial use; re-identification attempts; clinical deployment without independent validation. |
|
|
| Full legal text: [Creative Commons BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/legalcode). |
|
|
| --- |
|
|
| ## Extra metadata |
|
|
| Machine-readable dataset description: see [`croissant.json`](https://mlcommons.org/croissant/) at the repository root. |
|
|
| --- |
|
|
