[Dataset] Add Luciw2014 Grasp-and-Lift Motor Execution dataset
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Description
Dataset Information
| Field | Value |
|---|---|
| Name | Luciw2014 |
| Subjects | 12 |
| Channels | 64 |
| Sampling Rate | 500 Hz |
| Paradigm | Motor Execution |
| Tasks | Grasp and lift (tactile discrimination) |
| Publication | Scientific Data (Nature), 2014 |
| DOI | 10.1038/sdata.2014.47 |
| Repository | Figshare |
Description
Motor execution dataset involving grasp-and-lift actions with tactile feedback. Participants grasped objects with different weights and surface friction.
Source
Identified from Gwon et al. 2023 review paper (DOI: 10.3389/fnhum.2023.1134869)
Notes
- Motor Execution (not MI) - may need new paradigm class
- Well-documented in Scientific Data
Related
This issue is a sub-issue of #1 (Discover new datasets)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the Luciw2014 Scientific Data publication and locating the dataset in Figshare, then review how existing MOABB datasets and paradigms are represented. No file or test is named in the issue; done means the dataset is integrated with its metadata and grasp-and-lift motor-execution tasks, including any required paradigm support.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100