In a busy clinical setting, staff must trust that diagnostic hardware produces reliable results.

Yet, calibration drift accumulates invisibly, undermining this trust and potentially exposing patients to misdiagnosis or inappropriate treatment.

Manual recalibration routines are often skipped due to time constraints, and device alerts are either too sensitive (causing alert fatigue) or too lax (missing real issues).

How do we balance automation, reliability, and practical workload when the risk is both invisible and high-impact?

The root challenge is the lack of continuous, unobtrusive means to detect and correct minute calibration changes in real time.

Hardware limitations and workflow constraints prevent frequent checks, and current embedded diagnostics miss subtle or early-stage drift.

Periodic manual recalibration or scheduled service checks, plus simplistic on-device alerts.

These approaches rely on staff vigilance, are prone to error, and lack real-time responsiveness to small changes.