SignalSmithEnd-to-End Signal Integrity.
A vertically integrated platform. We control the physics, the firmware, and the inference to deliver clinical-grade accuracy.
Acoustic & RF Engineering
Commodity sensors introduce noise. SignalSmith uses a custom Radar sensor designed specifically for biological signal extraction.
- Computational UnitZero-fan architecture eliminates mechanical vibration noise.
- Edge Compute ModuleOn-board DSP handles privacy filtering at the source.
The Motion Engine
Raw radar data is chaotic. Our proprietary adaptive beamforming algorithms isolate vital micro-doppler signatures from environmental clutter in real-time.
Context-Aware Inference
Optical Guidance
Camera input informs the radar where to look. By tracking the subject's bounding box optically, we steer the radar beam for persistent lock.
Behavioral Context
The system distinguishes "Resting" from "Freeze Response" by analyzing micro-posture shifts that radar alone might miss.
Anomaly Detection
Unsupervised learning establishes patient-specific baselines, triggering alerts only when deviation exceeds their personal norm.
Clinical Grade Data.
Developer Ready.
We don't just give you a "Health Score." We provide raw, processed, and inferred data streams via a robust JSON API, ready for integration into your existing electronic health records (EHR) or research pipelines.
{
"timestamp": 1715620000,
"subject_id": "k9_01",
"vitals": {
"hr_bpm": 72,
"rr_rpm": 16,
"confidence": 0.98
},
"status": "resting",
"fusion_metrics": {
"radar_snr": 12.4,
"optical_lock": true
}
}