bciflow 1.0.0.dev4

A package for BCI-related tasks, including dataset loading, preprocessing, feature extraction, and classification.

BCI Flow

Bciflow is a Python package focused on Brain-Computer Interface (BCI)-related work. It provides tools for loading pre-established datasets, performing analysis, pre-processing, filtering, feature extraction, and classification, covering the entire process of creating BCI models. Installation

You can install bciflow directly from PyPI using pip:

pip install bciflow 

Features

• Dataset Loading: Support for popular BCI datasets, such as BCI Competition datasets, OpenBMI, among others.
• Pre-processing: Filtering, artifact removal, normalization, and other data preparation techniques.
• Feature Extraction: Methods for extracting relevant features from EEG signals, such as frequency bands, CSP (Common Spatial Patterns), etc.
• Classification: Implementation of classification algorithms such as SVM, LDA, Neural Networks, among others.
• Complete Pipeline: Facilitates the creation of complete pipelines for processing and analyzing BCI data.

Loading a Dataset

The datasets must be loaded by the user, and the data path must be provided by the user in the path parameter. For example, to load the CBCIC dataset:

from bciflow.datasets import cbcic
# Load CBCIC dataset
data = cbcic(
    subject=1,  # Subject number
    session_list=None,  # List of sessions to load (default: all sessions)
    labels=['left-hand', 'right-hand'],  # Labels to include
    path='data/cbcic/'  # Path to the dataset files
)