Hypertension Notification Feature (HTNF)

The Hypertension Notification Feature (HTNF) is a software-only mobile medical application that analyzes photoplethysmography (PPG) data from Apple Watch to identify patterns suggestive of hypertension and provides notifications to users. It is intended for over-the-counter use by adults age 22 and older without prior hypertension diagnosis, and is not meant to replace traditional diagnosis, monitor treatment, or provide blood pressure surveillance.

HTNF uses PPG data collected opportunistically over 30-day periods via Apple Watch and employs a machine learning algorithm with a deep-learning model and linear classification layer. The predicate device (Viz HCM) analyzes 12-lead ECG on-demand in clinical settings. Key differences: HTNF is passive/opportunistic for PPG analysis; Viz HCM is on-demand ECG analysis. Both are software-only, machine learning-based notification devices intended to identify a cardiovascular condition for further evaluation rather than diagnosis.

Not stated in this summary.

Although HTNF and Viz HCM differ in target condition (hypertension vs. HCM), user type (lay users vs. clinicians), use setting (home vs. clinic), and input signal (PPG vs. ECG), both devices share identical intended use principles: employing machine learning to identify a single cardiovascular condition non-invasively and recommend further testing without providing diagnostic output. The submission argues these differences do not raise new safety or effectiveness questions because they can be adequately evaluated under the same regulatory classification (21 CFR 870.2380, Cardiovascular Machine Learning-Based Notification Software). Clinical performance data demonstrating acceptable sensitivity (41.2%) and specificity (92.3%) in the intended population, combined with verification/validation testing and human factors analysis, supports that HTNF maintains the same safety and effectiveness profile as the predicate despite different applications.