| --- |
| license: cc-by-nc-4.0 |
| pretty_name: LEVEL Running Dataset |
| language: |
| - en |
| tags: |
| - running |
| - gait |
| - imu |
| - wearable |
| - accelerometer |
| - gyroscope |
| - biomechanics |
| - heart-rate |
| - ecg |
| - time-series |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: sessions |
| default: true |
| data_files: sessions.csv |
| --- |
| |
| # LEVEL Running Dataset |
|
|
| Open, raw running recordings from body-worn LEVEL motion sensors (feet, lower back, wrist, arm), |
| time-synchronized with a Polar H10 chest strap (heart rate, RR intervals, ECG), phone GPS, barometer |
| and step counter, and additional ground truth where available. Collected with the LEVEL Collector |
| platform, which runs on Android phones and Windows PCs, across deliberately varied sensor setups, and |
| tracked run over run for open research on running performance, fatigue and injury prevention. |
|
|
| > In 2025, my doctor gave me "the talk." You know the one. The one where I need to exercise more and |
| > eat better. So I picked up running, and somewhere along the way I thought: I'm a biomechanics |
| > engineer, and I work for a company that makes IMU motion sensors. Why not take some measurements? |
|
|
| ## Two purposes |
|
|
| **1. LEVEL Collector, working anywhere.** An open record of the collection platform itself: different |
| sensors, placements, settings and devices, in and out of the research lab. **LEVEL Inez** is a small |
| wearable 6-axis motion sensor (accelerometer ±16 g, gyroscope) that clips or straps onto the body -- |
| here both feet, the lower back and a wrist or arm -- and streams for about 36 hours (a day and a half) at 100 Hz on a |
| charge. **LEVEL Collector** is the research app that records several of them at once, over the |
| phone's Bluetooth or the **LEVEL Hub** USB receiver, with the sensor clocks kept in step, alongside the |
| phone's GPS, barometer and step counter and add-ons such as a Polar H10 chest strap, all on one clock, |
| as plain documented CSV files (the [format spec](data/data_dictionary.md)). |
|
|
| **2. Running research.** A longitudinal, within-participant record of real running: pace, heart rate, |
| cadence and foot mechanics across runs, conditions and fatigue. Almost all running-injury research |
| compares runners with each other, cross-sectionally or in prospective cohorts with a single baseline |
| measurement, so following a runner's own mechanics over time is still rare; and the public running-IMU |
| datasets are nearly all lab- or treadmill-bound and rarely bilateral at the foot. This one is within-subject and longitudinal, |
| outdoors, with both feet and every stream on one clock, built to ask whether *your own* mechanics |
| drift predicts *your* breakdown, with chest-strap, phone-GPS and other reference data to check the |
| sensors against. |
|
|
|  |
|
|
| *One 61-minute run at a glance: movement from each LEVEL sensor, heart rate, speed, cadence and |
| relative elevation, all on one clock. Gaps are real dropouts.* |
|
|
| ## Reports |
|
|
| Written-up results live in the companion Space |
| [lvlmotion/running-reports](https://huggingface.co/spaces/lvlmotion/running-reports): the cumulative |
| SUMMARY (objective, literature, methodology, longitudinal results) and one report per run, built from |
| this dataset's public data. |
|
|
| ## The sessions |
|
|
| <!-- glance:start (generated by scripts/make_catalog.py) --> |
| **11 sessions, 1 participant, 5.6 h of recording, 34 km outdoors, 2026-09-07 to 2026-10-08.** |
| <!-- glance:end --> |
| |
| <!-- sessions:start (generated by scripts/make_catalog.py from sessions.csv -- do not edit by hand) --> |
| | Date | Session | Conditions | Data (min) | Run (min) | Distance (km) | LEVEL sensors | Reference data | Packet loss (%) | Eff. rate (Hz) | Max gap (s) | |
| |---|---|---|---:|---:|---:|---:|---|---:|---:|---:| |
| | 2026-09-07 | [R01](figures/S01/R01/overview.png) | outdoor | 61 | 61 | 7.21 | 4 | watch | 0.6 | 99.3 | 0.31 | |
| | 2026-09-12 | [R02](figures/S01/R02/overview.png) | outdoor | 44 | 44 | 5.00 | 4 | chest strap, watch | 10.4 | 89.5 | 0.66 | |
| | 2026-09-14 | [R03](figures/S01/R03/overview.png) | outdoor | 32 | 32 | 3.47 | 4 | chest strap, watch | 4.0 | 95.9 | 0.51 | |
| | 2026-09-14 | [R04](figures/S01/R04/overview.png) | outdoor | 28 | 29 | 2.91 | 4 | watch | 4.1 | 95.8 | 1.51 | |
| | 2026-09-17 | [R05](figures/S01/R05/overview.png) | indoor | 8 | 8 | | 4 | chest strap | 0.3 | 99.6 | 0.31 | |
| | 2026-09-19 | [R06](figures/S01/R06/overview.png) | outdoor | 15 | | | 4 | chest strap | 6.6 | 93.3 | 0.71 | |
| | 2026-09-28 | [R07](figures/S01/R07/overview.png) | outdoor | 37 | 37 | 4.24 | 4 | | 3.6 | 96.3 | 0.41 | |
| | 2026-09-30 | [R08](figures/S01/R08/overview.png) | outdoor | 45 | 45 | | 4 | | 0.7 | 99.2 | 0.31 | |
| | 2026-10-03 | [R09](figures/S01/R09/overview.png) | outdoor | 20 | 41 | 5.00 | 4 | watch | 0.0 | 99.9 | 0.01 | |
| | 2026-10-05 | [R10](figures/S01/R10/overview.png) | outdoor | 33 | 33 | 4.46 | 4 | watch | 1.9 | 98.0 | 0.36 | |
| | 2026-10-08 | [R11](figures/S01/R11/overview.png) | indoor | 14 | 14 | 2.03 | 4 | watch | 0.0 | 99.9 | 0.06 | |
|
|
| *11 sessions. Click a session for its overview figure; every column (setup, versions, heart rate, capture quality) is in `sessions.csv`.* |
| <!-- sessions:end --> |
|
|
| Every run's figures sit in `figures/<subject>/<session>/`: `overview.png` (start there), `data-*.png` for |
| each published source as recorded (`imu`, `phone`, `h10`, `fit3`), `derived-*.png` for anything computed |
| from them (`spectrum`), and `analysis-*.png` from our running analysis: `gait` (cadence, ground contact |
| time, vertical oscillation over the run), `foottilt` (a 3 s window of foot swing), `groundtruth` (IMU cadence |
| against the watch, heart rate and GPS pace, where recorded) and `pace` (pace and elevation, where GPS was on). |
| The analysis figures are provisional: the algorithms are not yet validated against a lab reference, and |
| `make_figures.py` does not regenerate them. `sessions.csv` has one row per session with |
| every column, in groups that read left to right: conditions, the setup that was varied, what the run |
| measured, then the capture analysis (packet loss, clock alignment, phone battery); the column |
| definitions are in the [format spec](data/data_dictionary.md). |
|
|
| Failures stay in: a chest strap that dropped out, a capture cut short, sensor clocks that did not align. |
| They are flagged in `sessions.csv` (the capture columns and each session's `notes`) and in the figures. |
|
|
| ## The data |
|
|
| ``` |
| data/<subject>/R01/level/ one folder per session: LEVEL sensor CSVs, chest strap, phone streams, metadata |
| data/<subject>/R01/fit3/ watch data for the run (where worn) |
| data/context/ the only non-anonymous folder: per-session date, conditions, event; participants |
| data/data_dictionary.md every file, column and unit, and the de-identification policy |
| figures/ per session: overview.png, data-*.png (as recorded), derived-*.png (computed), |
| analysis-*.png (running analysis, provisional) |
| scripts/ lvl_running (iterate / load / plot) + make_figures.py, make_catalog.py |
| ``` |
|
|
| ## Quick start |
|
|
| ```python |
| # pip install -r scripts/requirements.txt (run from the dataset folder) |
| import sys; sys.path.insert(0, "scripts") |
| from lvl_running import iter_sessions, load_session, plot_session |
| |
| for run_dir in iter_sessions("data"): # every run, all participants and sessions |
| run = load_session(run_dir) # LEVEL sensors by placement + phone streams + metadata |
| print(run.name, sorted(run.imus), f"{run.duration_s / 60:.0f} min") |
| |
| plot_session("data/S01/R01/level", "my_figures") # the same figures as figures/S01/R01/ |
| ``` |
|
|
| `python scripts/make_figures.py` regenerates the `overview`, `data-*` and `derived-*` figures from `data/`; `python scripts/make_catalog.py` |
| regenerates `sessions.csv` and the session table above. |
|
|
| ## Limitations |
|
|
| - **One participant so far**, the dataset's author. More participants will join; until then nothing |
| here generalizes beyond one runner. |
| - **Setups vary between runs on purpose** (see `sessions.csv`); compare runs on the sensors they share. |
| - **Consumer references:** the watch and phone GPS are convenient, not gold standards; the Polar H10 |
| is the heart-rate reference. |
| - **Accelerometer range:** foot impacts can reach the ±16 g limit, and 100 Hz under-samples the impact |
| transient (see `derived-spectrum.png`); timing-based measures are unaffected. |
|
|
| ## License and citation |
|
|
| The data and figures are **CC BY-NC 4.0** (see [LICENSE](LICENSE)): free for research and other |
| non-commercial use with attribution; commercial use reserved. The code in `scripts/` is **MIT** |
| (see [scripts/LICENSE](scripts/LICENSE)). Copyright Level Health Innovations Corp. |
|
|
| Cite as: Lin, J. (2026). *LEVEL Running Dataset.* Level Health Innovations Corp. |
| https://huggingface.co/datasets/lvlmotion/running |
|
|
| Built at [LEVEL](https://lvlmotion.com). Jonathan Lin designed, collected and analysed this dataset; the |
| experiment and reporting were built with AI assistance from Claude (Anthropic). Questions and |
| collaboration: jlin@lvlmotion.com |
|
|
