Machine Learning
Featured ProjectNeuroGuard Seizure Detection
NeuroGuard is an end-to-end seizure detection system leveraging multimodal wearable sensor data (EEG, ECG, EMG, accelerometer, gyroscope) to predict and detect epileptic seizures. Uses a hybrid CNN-LSTM architecture with attention mechanisms and Focal Loss for handling class imbalance in medical datasets.
Project Duration
Jan 2025 — Jun 2025
Client
Healthcare ClientNDA
Key Features
Multimodal sensor processing
Real-time seizure prediction
CNN-LSTM hybrid model
Attention mechanisms
Patient-wise validation
TensorBoard monitoring
Technology Stack
PythonPyTorchCNN-LSTMTensorFlowSignal ProcessingDeep Learning
Project Metrics
>95%
accuracy
>70%
recall
5+
sensors
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