EEGENIUS
Advanced EEG signal processing powered by Deep Learning. Predicting neurological conditions with mathematical precision.
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NEURAL_CODE
The human brain generates terabytes of electrical data daily. For decades, this symphony of signals has been noise. EEGENIUS turns the volume up.
By fusing low-latency Electroencephalography (EEG) with advanced Deep Learning architectures, we don't just see brainwaves—we predict outcomes. From early onset Parkinson's detection to precise ADHD sub-typing, we are mapping the invisible landscape of the mind.
Non-Invasive Insight
No needles, no radiation. Pure signal analysis captured from the scalp surface, processed in milliseconds.
Pattern Recognition
Our Neural Networks identify non-linear dependencies in EEG spectral power that the human eye simply cannot see.
Future Scalability
From clinics to wearables. Our lightweight models are designed to run on edge devices, democratizing diagnostics.
SYSTEM ARCHITECTURE
SIGNAL PROCESSING
Raw EEG/Voice data is filtered through a Butterworth bandpass filter (0.5-50Hz) to remove artifacts and power line noise before feature extraction.
NEURAL NETWORKS
Custom architecture featuring Dense layers with Dropout regularization (0.3) and ReLU activation functions optimized for medical tabular data.
REAL-TIME VISUALIZATION
WebGL-powered rendering engine creating immersive feedback loops for user interaction and data representation.
ARCHITECTS ///
Systems Online // Dev_Team_01
ADOLF LOBOWICZ
Full-stack architect and 3D specialist. Orchestrating the digital interface and backend infrastructure.
"Code is the new biology."
AKRITI SRIVASTAVA
The neural architect. Designed the Deep Learning models and feature extraction pipelines for high-precision diagnosis.
"The signal holds the truth."
CONTACT_US
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