Elata SDK is the cross-platform biosignal toolkit for building neurotechnology and remote biosensing apps on web and native.
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Updated
Jun 9, 2026 - TypeScript
Elata SDK is the cross-platform biosignal toolkit for building neurotechnology and remote biosensing apps on web and native.
Python API for Mentalab biosignal aquisition devices
personal repository
List of summer schools to study brain-computer interfaces, neurotechnology & related fields worldwide
Bio-Silicon Synergetic Intelligence System
AI-powered intelligence platform aggregating breakthroughs in neurotech and BCI
The open closed-loop OS for gamma-entrainment research — a Rust/WASM/edge harness to measure, adapt & compare 40 Hz multisensory stimulation protocols with signed, reproducible evidence. Research-grade, not a medical device.
Open Source EEG
MindsApplied EEG Signal Filter for Real-time or Offline Analysis
A daemon service allowing web apps to read fingerprints from biometric devices using the Neurotechnology SDK
🧠🔥 Adaptive and inclusive neurotech platform for real-time multimodal data — born from the Olympic flame project.
A retro arcade of thought-controlled minigames - proving neurotechnology is already here, accessible, and ready to hack.
BrainBrowsR is a software stack that allows a user to control the browser through SSVEP. We want to unlock social media for people with extreme paralysis, ALS or locked-in syndrome.
God-View for your brain
Open-source EEG analysis agent workflows and prompts for NeuraDock EEG Workstation.
A framework for implementing modular Brain-Computer Interfaces
Simulate, record, and play interactive games using your brain (Supports Neurosky EEG Headset)
The AxonOS Consent Protocol — specification and reference implementation. no_std, zero-alloc, forbid(unsafe): bounded CBOR codec, exhaustive consent state machine, StimGuard for brain–computer interfaces. All AxonOS.
A modular and extensible software framework for soft real-time signal processing, originally designed for short-latency closed-loop neural applications.
This web app uses an AI model trained with TensorFlow.js to guess if a (fake) person would be "focused" or "distracted" based on simulated brain waves (alpha/beta/gamma) generated every second.
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