Research2026
Epilepsy Prediction from Neurological Signals
A machine learning framework that reads raw EEG traces and predicts the onset of epileptic seizures before they occur.
- Designed a full signal-to-prediction pipeline: denoising, feature extraction, and classification across 5,000+ time-series EEG samples.
- Reached ~94% prediction accuracy using a spiking neural network approach tuned for temporal signal data.
- Findings are being formalized into a research paper, currently in preparation.
~94%
Accuracy
5,000+
EEG samples
Paper in prep
Status
PythonMachine LearningSNNSignal Processing