A middleware, bridging a large number of tracking devices and other hardware with VR
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Updated
Jun 15, 2017 - C#
A middleware, bridging a large number of tracking devices and other hardware with VR
A Machine Learning based VR game for Neurorehabilitation.
Clinical guide for recoveriX brain-computer interface rehabilitation | Medical BCI for stroke, MS, TBI, SCI | Luxembourg
BeamBCI is a modular, Python-based framework for real-time brain-computer interface experiments, developed at Charité Berlin. It supports flexible modular components for data acquisition, processing, classification, and actuator control, all synchronized using LabStreamingLayer (LSL).
Personal website for AI consulting in healthcare and neurotechnology | explainable ML, predictive analytics, and generative models. Built with React + Tailwind.
VR testing prototype for Motor and Cognitive Dual Training Task
Next-generation explainable AI integrating EMG and kinematics to identify muscle drivers of stiff-knee gait in Hereditary Spastic Paraparesis.
🧠 Enhance neurorehabilitation with recoveriX, a BCI technology that helps patients regain motor functions through innovative therapy and real-time feedback.
Webcam-based games to aid in stroke recovery
Set of javascript scripts to simulate the input from the sensors used in GaitRehub project to control the exergames for neurorehabilitation.
| Who we are... | What we do... | High-Level Mission | Mission alignment with EIT HEI |
Conceptual research repository for privacy-preserving, outcome-based incentives in neuro-rehabilitation using ZK proofs.
GraspIt is a Python system that uses Functional Electrical Stimulation (FES) and infrared feedback to induce hand grasping. It’s modular, with sensor (tracking), stimulator (stimulation), and commander (voice commands) nodes, communicating via MQTT.
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