Datasets:

webxos
/

BCI-grid-movement-v1

Tasks:

Reinforcement Learning

Time Series Forecasting

Tabular Classification

Modalities:

Formats:

Sub-tasks:

natural-language-inference

entity-linking-classification

acceptability-classification

Languages:

Size:

Tags:

reinforcement-learning

neural-decoding

human-computer-interaction

Libraries:

Dataset card Data Studio Files Files and versions

webxos commited on Mar 1

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@@ -30,8 +30,6 @@ size_categories:
 # BCI Grid Movement Intent Dataset
-## Dataset Description
 *UNDER DEVELOPMENT for TESTING purposes*
 *This dataset was generated with the gym located in /gym/ folder of this repo.*
@@ -43,7 +41,7 @@ large scale real hardware BCI datasets, addressing data scarcity and privacy iss
 *Simulated data for synthetic Intent testing, does not use real Neuralink/BCI hardware signals.*
-# RL/ML user input intent data:
 ML: Supervised decoding of motor intents (e.g., DNNs, classifiers) for cursor/game control, stroke rehab, ADHD treatment.
@@ -68,8 +66,6 @@ for policy optimization.
 - **BCI System Development**: Train and test BCI algorithms
 - **Real-time Intent Decoding**: Develop real-time BCI interfaces
-## Dataset Structure
 ### Data Fields
 - **timestamp**: UNIX timestamp in milliseconds

 # BCI Grid Movement Intent Dataset
 *UNDER DEVELOPMENT for TESTING purposes*
 *This dataset was generated with the gym located in /gym/ folder of this repo.*
 *Simulated data for synthetic Intent testing, does not use real Neuralink/BCI hardware signals.*
+### RL/ML user input intent data:
 ML: Supervised decoding of motor intents (e.g., DNNs, classifiers) for cursor/game control, stroke rehab, ADHD treatment.
 - **BCI System Development**: Train and test BCI algorithms
 - **Real-time Intent Decoding**: Develop real-time BCI interfaces
 ### Data Fields
 - **timestamp**: UNIX timestamp in milliseconds