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BEADDA
Project Timeline
Nov 2025 - Current
OVERVIEW
BEADDA is an AI-driven physiotherapy system integrating EEG, EMG, and computer vision to measure cognitive and physical performance in real time. I built a unified biosensing pipeline by integrating OpenBCI EEG and EMG hardware with LabStreamingLayer (LSL) to synchronize multi-channel neural and muscle signals. I implemented full signal-processing workflows—including filtering, artifact reduction, calibration, and feature extraction—to create reliable neural and muscular metrics suitable for downstream AI models. This system enables real-time assessment of user state, forming the foundation for adaptive physiotherapy feedback and AI-guided movement correction.
HighlightS
- ✨ Built one of the first unified EEG–EMG physiotherapy systems, enabling real-time neuro-muscular insight.
- 🧠 Created a multimodal biosensing pipeline that links cognitive state (EEG) with muscle activation (EMG) for adaptive rehab.
- ⚙️ Engineered a real-time, research-grade signal processing stack with robust filtering, calibration, and feature extraction.
- 🚀 Established a scalable foundation for AI-driven physiotherapy, supporting automatic feedback and performance assessment.
- 🔗 Achieved precise cross-modality synchronization of EEG, EMG, and computer vision data through LSL.
- 🧩 Designed a modular, extensible architecture, allowing rapid integration of new sensors and AI models.
SKILLS
EEGEMGLSLPythonFilteringCalibrationBiosignalsIntegrationStreaming
Additional Details
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