Personalized Physiology Analytics Engine software

K142512

VGBio, Inc (DBA PhysIQ) · cleared 2015-06-11 · product code PLB · Cardiovascular

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The PhysIQ Personalized Physiology Analytics Engine (“PPA Engine”) is a computerized analysis software program that is designed for detecting change in the relationships among the patient's vital signs throughout dynamic physical activity, based on data input from multi-parameter vital sign monitoring devices. ... Software only”
Algorithmcomputerized analysis software program that is designed for detecting change in the relationships among the patient's vital signs throughout dynamic physical activity, based on data input from multi-parameter vital sign monitoring devices. The PPA Engine first “learns” a patient's personalized baseline, defined by the relationship among the vital signs derived from measurements obtained during routine activities of daily living. Once the baseline vital sign relationships are established, it analyzes the subsequent data to assess how the relationships among the vital signs incoming during the monitoring period compare to the established baseline. The PPA Engine calculates the Multivariate Change Index (MCI), a scalar index between 0 and 1, which represents the likelihood that the relationships among the patient's vital signs are different from those at baseline, which was established during routine activities of daily living. An MCI value closer to zero (0) indicates that the monitored relationships among the vital signs are similar to the learned baseline. An MCI value closer to one (1) indicates that the patient's monitored relationships among the vital signs are likely to be different from the learned baseline. ... Non-linear combination of vital parameters
source quote (p.6)
“The PhysIQ Personalized Physiology Analytics Engine (“PPA Engine”) is a computerized analysis software program that is designed for detecting change in the relationships among the patient's vital signs throughout dynamic physical activity, based on data input from multi-parameter vital sign monitoring devices. The PPA Engine first “learns” a patient's personalized baseline, defined by the relationship among the vital signs derived from measurements obtained during routine activities of daily living. Once the baseline vital sign relationships are established, it analyzes the subsequent data to assess how the relationships among the vital signs incoming during the monitoring period compare to the established baseline. The PPA Engine calculates the Multivariate Change Index (MCI), a scalar index between 0 and 1, which represents the likelihood that the relationships among the patient's vital signs are different from those at baseline, which was established during routine activities of daily living. An MCI value closer to zero (0) indicates that the monitored relationships among the vital signs are similar to the learned baseline. An MCI value closer to one (1) indicates that the patient's monitored relationships among the vital signs are likely to be different from the learned baseline. ... Non-linear combination of vital parameters”
Adaptive (vs locked)No
source quote (p.6)
“The PPA Engine first “learns” a patient's personalized baseline, defined by the relationship among the vital signs derived from measurements obtained during routine activities of daily living. Once the baseline vital sign relationships are established, it analyzes the subsequent data to assess how the relationships among the vital signs incoming during the monitoring period compare to the established baseline. ... Normality is defined as the patient's own baseline.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

sample size not stated

endpoints: Verification testing for the PPA Engine (to verify that the device meets its specifications); Validation testing of the PPA Engine's MCI output (to validate correlation of MCI with changes in the relationships among vital signs compared to baseline in order to meet its intended use)

Retrospective clinical

sample size not stated

endpoints: MCI output correlates with changes in the relationships among vital signs compared with baseline

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Cardiovascular panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K142512