The person behind the signal
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ECG–BCG Synchronization Pipeline
Full-stack system aligning Polar H10 ECG with BCG (PVDF Sensor). R peaks detected via SciPy's signal module; BCG J peaks extracted and filtered using z-score based thresholding to retain only high-confidence peaks. Cross-correlation between R and J peaks computes per-beat alignment. R-to-J peak matching with ±50ms delay handling and drift logging.
- Python
- NumPy/SciPy
- asyncio/BLE
- Polar H10
- PVDF
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Contactless Vitals Stack
End-to-end pipeline extracting heart rate and respiratory rate from raw PVDF BCG signals — no contact, no wearable. Bandpass filtering, peak detection, and RR interval analysis to deliver continuous vitals from an under-mattress sensor.
- Python
- SciPy
- PVDF
- BCG
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Snoring Detection via BCG
Vibration-based snoring classifier using under-mattress PVDF sensor — no microphone required. Frequency-domain analysis of BCG signal to distinguish snoring events from movement artifacts and normal breathing patterns.
- Python
- SciPy
- scikit-learn
- PVDF
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Multi-Sensor Signal Processing
Evaluated and extracted meaningful insights from diverse sensor modalities — contactless vitals (HR, respiration) from PVDF, bed occupancy and posture detection from custom capacitive sensors. Demonstrates the ability to adapt signal processing and data science techniques to any sensor to unlock actionable health insights.
- PVDF
- Capacitive Sensors
- Signal Processing
- Python
- scikit-learn