pyRiemann/pyRiemann-qiskit

A library for machine learning and quantum programming based on pyRiemann and Qiskit projects

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Established

This tool helps researchers and engineers in Brain-Computer Interfaces (BCI) and EEG analysis by applying quantum machine learning to interpret brainwave data. It takes in EEG signals, processes them using advanced mathematical techniques, and outputs classifications that can reveal patterns related to brain states or responses. The end-users are scientists and practitioners working with neural data who want to explore cutting-edge quantum algorithms for complex pattern recognition.

Available on PyPI.

Use this if you are a BCI or EEG researcher looking to experiment with quantum-enhanced classification algorithms for your covariance matrix data, especially when traditional methods struggle with complex tasks or limited datasets.

Not ideal if you need real-time analysis or if you are working with extremely large datasets, as quantum algorithms can be computationally intensive and may experience delays with remote quantum hardware.

Brain-Computer Interfaces EEG analysis neuroscience research quantum machine learning neural signal processing
Maintenance 10 / 25
Adoption 7 / 25
Maturity 25 / 25
Community 18 / 25

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Stars

31

Forks

13

Language

Python

License

BSD-3-Clause

Last pushed

Mar 08, 2026

Commits (30d)

0

Dependencies

16

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