Perin Health System (PHD80060-2)

K252984

Perin Health Devices, LLC · cleared 2026-01-22 · product code DRG · Cardiovascular

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.6)
The Perin Health System is a wireless remote patient monitoring platform that enables healthcare professionals to perform spot-checking and retrospective monitoring of physiological data from adult patients. The Perin Health System is designed for use in hospitals, clinics, long-term care facilities, physician offices, and home environments. The Perin Health System comprises the following components: 1. Perin Health Patch wearable device 2. Perin Health Patient Mobile Application 3. Perin Health Cloud 4. Perin Health Provider Portal 5. Perin Health Inpatient Application
AlgorithmAlgorithms are run in the cloud to process measurements from the Health Patch and generate Signal Quality Index, Heart Rate, Heart Rate Variability, Respiratory Rate, Oxygen Saturation, and Posture.
source quote (p.10)
Algorithms are run in the cloud to process measurements from the Health Patch and generate Signal Quality Index, Heart Rate, Heart Rate Variability, Respiratory Rate, Oxygen Saturation, and Posture.
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.25)
Software in the Perin Health System was securely designed, documented, verified & validated as per the USFDA Guidance Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions.

Validation studies (5)

Bench

sample size not stated

endpoints: Biocompatibility testing; Electrical Safety and electromagnetic compatibility testing; Skin temperature accuracy performance; Auscultation data of heart and lung sounds has been verified; Defibrillation proof testing; Body Motion, Fall Detection, and Posture performance; Step Count performance; Alert system & Visual alarm display; Usability study; Wireless performance & coexistence testing; Software in the Perin Health System was designed, documented, verified & validated; Shelf-life testing; Packaging testing

standards: ISO 10993-1: 2018, ISO 10993-5:2009, ISO 10993-10:2021, ISO 10993-23:2021, IEC 60601-1(Ed.3.2), IEC 60601-1-2 (Ed. 4.1), IEC 60601-1-11(Ed. 2.1), ISO 80601-2-56:2017(E), ANSI/AAMI/IEC 60601-2-27:2011, ANSI/AAMI/IEC 60601-2-47:2012, IEC 60601-1:2005, IEC 60601-1:2005/AMD1:2012, IEC 60601-1:2005/AMD2:2020, ANSI/CTA-2056-А, IEC 60601-1-8 (Ed. 2.2), IEC 60601-1-6 (Ed. 3.2), ANSI/IEEE C63.27:2017, IEC 62304

Retrospective clinical

n=12 patients

endpoints: accuracy of SpO2% in induced hypoxia studies in the range of 70% to 100% SpO2

standards: ISO 80601-2-61(Ed. 2.0)

Retrospective clinical

n=35 patients

endpoints: Respiratory Rate accuracy performance

Retrospective clinical

n=243 patients

endpoints: ECG, Heart Rate, R-R Interval, and Heart Rate Variability performance

Retrospective clinical

n=26 patients · 3 site(s)

endpoints: sustained adhesion to the body for 360 hours; stable performance across all evaluated parameters (timing intervals, SNR, morphological features) and for all demographic and clinical subgroups

Reported performance (3 observations)

accuracyas written: “SpO2% Accuracy (Arms)3.3CI Arms of 3.5 for 67% to <80%, 3.1 for 80% to <90%, and 3.3 for 90% to 100%
source quote (p.25)
The overall measured Arms in the range of 70 to 100% SpO2 was 3.3%, with Arms of 3.5 for 67% to <80%, 3.1 for 80% to <90%, and 3.3 for 90% to 100%.
accuracyas written: “Respiratory Rate Accuracy (Arms)1.7CI between 0.5 and 2.8
source quote (p.25)
The accuracy root mean square (Arms) for 259 points was 1.7 breaths per minute, with all subgroups exhibiting Arms between 0.5 and 2.8.
accuracyas written: “Respiratory Rate Accuracy (MAE)0.8CI between 0.4 and 1.3
source quote (p.25)
The mean absolute error (MAE) for 259 points was 0.8 breaths per minute, with all subgroups exhibiting MAE between 0.4 and 1.3.

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

1
recalls in product code, 24mo
77
MAUDE reports in code, 12mo
+240%
vs code's own 3-yr baseline
2
drift signals on this device
  • adverse_event_inflection

    MAUDE adverse-event reports for product code DRG: 77 in the 12 months ending 2026-06, vs a 22.7/12mo average over the prior 3 windows (+240%). Code-level count — reports are not attributed to this specific device.

    first seen 2026-07-08 · openFDA /device/event.json count=date_received product_code=DRG

  • recall_reason_pattern

    Software/algorithm-related recall in product code DRG (Biointellisense Inc. 570 El Camino Real, initiated 2024-07-19): "Software anomaly causing the skin temperature measurement accuracy to be slightly out of specification." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:94943

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.

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