SensorFM utilizes a foundation model architecture to interpret complex time-series data from wearable devices. This research moves beyond narrow task-specific models to create a general interface for health monitoring. It enables more flexible analysis of physiological signals. Practitioners can now leverage pre-trained weights to accelerate the development of personalized health diagnostics.