SensorFM leverages a foundation model architecture to interpret complex time-series data from wearable devices. This research transforms raw biometric signals into actionable health insights without requiring task-specific training. It enables a general interface for health monitoring. Practitioners can now deploy a single model across diverse sensors to detect anomalies and track wellness trends.