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README.md
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---
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# Dataset Description
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The dataset includes recordings from:
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https://arxiv.org/placeholder
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---
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# Repository Organization
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The repository contains two subfolders:
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### 1️⃣ `data_raw_and_filt`
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- Contains filtered EMG signals (4th-order high-pass at 20 Hz + 50 Hz notch)
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- Is stored in `.h5` format\
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- Uses the HDF5 key `"emg"`
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Directory structure example:
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```text
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df = pd.read_hdf("data_raw_and_filt/S01/silent/sess_1_batch_1.h5", key="emg")
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df.head()
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```
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------------------------------------------------------------------------
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#### File Content Structure (`data_raw_and_filt`)
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| Labels | `Label_int`, `Label_str` | Integer and string class labels |
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| Metadata | `session_id`, `batch_id` | Session and batch identifiers |
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### 2️⃣ `wins_and_features`
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- Non-overlapping windowed segments
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- Raw and filtered signals
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- Extracted time-frequency features
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These files can be directly used for model training or benchmarking.
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---
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# Code and Usage
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---
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#
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# Contributing
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We aim to promote standardized evaluation and fair comparison across models.
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Please refer to the repository README for submission guidelines.
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---
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# Citation
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If you use this dataset, please cite:
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url = {coming soon}
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}
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```
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## 📄 License
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See the `LICENSE` file for the full license text.
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- Apache License 2.0 — See the `LICENSE` file for the full license text.
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- Images are under the the Creative Commons Attribution 4.0 International License - see the `LICENSE.images` file for details.
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---
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# Dataset Description
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The dataset includes recordings from:
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https://arxiv.org/placeholder
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---
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# Repository Organization
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The repository contains two subfolders:
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### 1️⃣ `data_raw_and_filt`
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|
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- Contains filtered EMG signals (4th-order high-pass at 20 Hz + 50 Hz notch)
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- Is stored in `.h5` format\
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- Uses the HDF5 key `"emg"`
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-
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Directory structure example:
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```text
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df = pd.read_hdf("data_raw_and_filt/S01/silent/sess_1_batch_1.h5", key="emg")
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df.head()
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```
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------------------------------------------------------------------------
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#### File Content Structure (`data_raw_and_filt`)
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| Labels | `Label_int`, `Label_str` | Integer and string class labels |
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| Metadata | `session_id`, `batch_id` | Session and batch identifiers |
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### 2️⃣ `wins_and_features`
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- Non-overlapping windowed segments
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- Raw and filtered signals
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- Extracted time-frequency features
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These files can be directly used for model training or benchmarking.
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---
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# Code and Usage
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---
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# Contributing
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We aim to promote standardized evaluation and fair comparison across models.
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Please refer to the repository README for submission guidelines.
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---
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# Citation
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If you use this dataset, please cite:
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url = {coming soon}
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}
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```
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## 📄 License
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See the `LICENSE` file for the full license text.
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- Apache License 2.0 — See the `LICENSE` file for the full license text.
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- Images are under the the Creative Commons Attribution 4.0 International License - see the `LICENSE.images` file for details.
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## 👨💻 Contributors
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_Silent-Wear_ has been developed at _ETH Zürich_, by the _PULP-Bio_ [Biomedical Circuits, System](https://iis-projects.ee.ethz.ch/index.php?title=Biomedical_Circuits,_Systems,_and_Applications):
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- Giusy Spacone [Scholar](https://scholar.google.com/citations?user=dGE8uMEAAAAJ&hl=en) (Conceptualization, Experimental Design, Development)
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- Sebastian Frey [Scholar](https://scholar.google.com/citations?user=7jhiqz4AAAAJ&hl=en) (PCB design, Firmware, Documentation)
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- Fiona Meier (Hardware Development)
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- Giovanni Pollo [Scholar](https://scholar.google.com/citations?hl=it&user=znSV3doAAAAJ&view_op=list_works&sortby=pubdate) (Experimental Desing, Data Collection, Documentation)
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- Luca Benini [Scholar](https://scholar.google.com/citations?user=8riq3sYAAAAJ&hl=en)(Supervision, Conceptualization)
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- Andrea Cossettini [Scholar](https://scholar.google.com/citations?user=d8O91jIAAAAJ&hl=en)(Supervision, Project administration)
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