Projects with this topic
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Data-driven pipeline for identifying latent neural-motor governing equations from multimodal EEG, EMG, and kinematic recordings. Hankel delay embedding → SVD → DMD → SINDy. Validated across 108 sessions (WAY-EEG-GAL dataset). Application to stroke rehabilitation.
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Quantum Synapse is an open-source, non-invasive brain–computer interface platform that enables mind-controlled interaction through wearable EEG technology. It combines real-time neural signal acquisition, signal processing, and machine learning to translate brain activity into digital input. Designed for privacy, modularity, and accessibility, the project provides a research-focused framework for exploring human–computer interaction without surgical implants or proprietary systems. https://roxanneardary.com/quantum-synapse/
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The Modular Non-Invasive BCI Engineering Platform is an open-source, AGPL-3.0+ neuroengineering framework designed to unify wearable brain-computer interfaces, hardware abstraction, and real-time neural decoding into a single modular system. It enables developers to build, simulate, and deploy EEG-based applications through interchangeable wearable and hardware modules, supported by machine learning pipelines, sleep and dream state analysis, hardware development tooling, and legal assurance systems for design validation and compliance. https://roxanneardary.com/modular-non-invasive-bci-engineering-platform/
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Open 4D consciousness lab — PEC biofeedback, CRV, ganzfeld, EEG bridge, dream fold, entity ingress API
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CLI Brain-Quick to EDF+ conversion with anonymization tool in Rust
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Matlab graphic user interface to perform auditory EEG experiments
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EEG morlet wavelet decomposition combined with a source‑separation algorithm (GED)
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A python tool to interact with an OpenEEG device
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Methods from MNE for Python as widgets for Orange 3 https://fifal.gitlab.io/orange-mne-library/
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VideoEEG Tagging - Does the person look at the screen ? - program for eye gaze direction estimation. Based on MediaPipe.
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In AugmentBrain we investigate the performance of different data augmentation methods for the classification of Motor Imagery (MI) data using a Convolutional Neural Network tailored for EEG named EEGNet.
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A Python tool that converts neurophysiological experiment datasets from the EEGbase portal to a NIX container format
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