| --- |
| license: other |
| license_name: physiomio-dua |
| license_link: LICENSE |
| extra_gated_heading: "Acknowledge data usage agreement to accept the repository" |
| extra_gated_description: "You can find the data usage agreement here: https://huggingface.co/datasets/formove-ai/physiomio/blob/main/LICENSE" |
| extra_gated_button_content: "I have read and understand the data usage agreement" |
| --- |
| |
| # 🧠 PhysioMio Dataset |
|
|
| <div align="center"> |
|
|
|  |
|  |
|  |
|  |
|
|
| **PhysioMio: Bilateral and Longitudinal HD-sEMG Dataset of 16 Hand Gestures from |
| 48 Stroke Patients** |
|
|
| *Julian Ilg, Alexander C. R. Oldemeier, Marie Fieweger, Luca Deuschel, Peter Rieckmann, Peter Young, Sabine Krause, Tim C. Lueth* |
|
|
| </div> |
|
|
| --- |
|
|
| ## 🔬 Overview |
|
|
| The **PhysioMio dataset** provides comprehensive longitudinal and bilateral high-density |
| surface electromyography (HD-sEMG) recordings from stroke patients with |
| arm paresis. This unique dataset captures the neuromuscular patterns of both |
| healthy and impaired forearms during rehabilitation, offering unprecedented |
| insights into post-stroke motor recovery. |
|
|
| ### ✨ Key Features |
|
|
| - 🏥 **48 stroke patients** with arm paresis |
| - 🤲 **16 distinct hand gestures** recorded per session |
| - 📅 **Longitudinal recordings** made during patients' stays in rehabilitation clinics |
| - 🔌 **64-electrode HD-sEMG array** for high-resolution muscle activity |
| - ⚖️ **Bilateral comparison** between healthy and impaired arms |
| - 📈 **Recovery progression** tracking across rehabilitation stages |
|
|
| --- |
|
|
| ## 📊 Dataset Statistics |
|
|
| | Metric | Value | |
| |--------|-------| |
| | **Participants** | 48 stroke patients | |
| | **Recording Sessions** | 1-2 healthy + 1-12 impaired per patient | |
| | **Gestures per Session** | 16 hand movements | |
| | **Electrodes** | 64-channel HD-sEMG array | |
| | **File Format** | Apache Parquet (.parquet) | |
| | **Comparison Data** | Healthy arm baseline | |
|
|
| --- |
|
|
| ## 🎯 Applications |
|
|
| This dataset is ideal for research in: |
|
|
| - 🧠 **Neuromuscular deficit analysis** in stroke patients |
| - 🔄 **Motor recovery pattern identification** |
| - 🤖 **Assistive technology development** |
| - 📊 **Personalized rehabilitation strategies** |
| - 🔬 **Comparative healthy vs. impaired arm studies** |
| - 🎯 **Machine learning for gesture recognition** |
|
|
| --- |
|
|
| ## 📖 Documentation |
|
|
| ### 📁 Data Structure |
|
|
| ```text |
| data/ |
| ├── patient1/ |
| │ ├── healthy_arm/ # Baseline recordings from healthy arm |
| │ │ ├── 01.parquet # Session 1 |
| │ │ └── 02.parquet # Session 2 |
| │ └── impaired_arm/ # Recordings from affected arm during rehabilitation |
| │ ├── 01.parquet # Session 1 |
| │ ├── 02.parquet # Session 2 |
| │ ├── ... # Additional sessions |
| │ └── 12.parquet # Session 12 (varies by patient) |
| ├── patient2/ |
| │ ├── healthy_arm/ |
| │ └── impaired_arm/ |
| └── ... # Additional patients (up to patient48) |
| ``` |
|
|
| The total number of files is 329. The dataset size is 4.4GB. |
|
|
| ### 🔍 Data Format |
|
|
| - **File format**: `.parquet` (Apache Parquet) |
| - **Sampling rate**: 2048 Hz |
| - **Electrode layout**: 64-channel grid around forearm |
| - **Session structure**: |
| - `healthy_arm/`: 1-2 baseline sessions from unaffected arm |
| - `impaired_arm/`: Multiple sessions during rehabilitation |
| (typically 1-12 sessions per patient) |
| - Each session contains 16 continuous segments, i.e. recordings of a gesture, |
| whereas the gesture is indicated in the column `movement_type`. The order |
| of gestures is always the same. The first gesture is "Rest". |
| |
|
|
| ### Movement types |
|
|
|  |
|
|
| --- |
|
|
| ## 📄 Paper |
|
|
| 📖 **[Read the full paper](https://www.nature.com/articles/s41597-026-06557-0)** |
|
|
| ### 📝 Citation (to be updated) |
|
|
| ```bibtex |
| @article{physiomio2026, |
| title={PhysioMio: A Longitudinal HD-sEMG Dataset for Stroke Rehabilitation Research}, |
| author={[Julian Ilg, Alexander C.R. Oldemeier, Marie Fieweger, Luca Deuschel, Peter Rieckmann, Peter Young, Sabine Krause, Tim C. Lueth ]}, |
| journal={[Scientific data 13]}, |
| year={2026}, |
| doi={[DOI]} |
| } |
| ``` |
|
|
| --- |
|
|
| ## 📊 Download |
|
|
| ### 🤗 Hugging Face |
|
|
| [](https://huggingface.co/datasets/formove-ai/physiomio) |
|
|
| ## 🤝 Contributing |
|
|
| - 🐛 **Bug reports**: [Open an issue](../../issues) |
|
|
| --- |
|
|
| ## 📜 License |
|
|
| This dataset is released under a [custom data usage agreement (LICENSE)](LICENSE.md). |
| Please cite our paper if you use this dataset in your research. |
|
|
| --- |
|
|
| ## 🏆 Acknowledgments |
|
|
| - 🏥 **Medical Team**: |
| - Medical Park Loipl, Bischofswiesen, Germany |
| - Medical Park Bad Feilnbach Reithofpark, Bad Feilnbach, Germany |
| - 💰 **Funding**: This research was conducted in the context of the |
| [START-interaktiv"physiomio"](https://www.interaktive-technologien.de/projekte/physiomio). |
| The authors gratefully acknowledge the received funding from the German Federal |
| Ministry of Education and Research for project 16SV9068 and from the German Federal |
| Ministry for Economic Affairs and Energy for project 03EFBY0337, in which the |
| presented study played a central role. |
| - 👥 **Participants**: All are indebted to all stroke patients who contributed |
| to this research over the course of their rehabilitation stay |
|
|
| --- |
|
|
