AI-ECG Tracker

K200036

Shenzhen Carewell Electronics Co., Ltd. · cleared 2020-03-20 · product code DPS · Cardiovascular

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The AI-ECG Tracker is a distributed ECG auto analysis system designed to assist physicians and qualified healthcare professionals in measuring and interpreting ambulatory ECG data. The system uses a machine learning based process (convolutional neural network or CNN) only for development of the AI ECG algorithm.”
Algorithmmachine learning based process (convolutional neural network or CNN)
source quote (p.6)
“The system uses a machine learning based process (convolutional neural network or CNN) only for development of the AI ECG algorithm. The AI ECG algorithm is only used for beat classification.”
Adaptive (vs locked)No
source quote (p.6)
“After the AI ECG algorithm is developed, the AI-based beat classification model is locked in the released product which means the marketed device doesn't have active machine learning or self-learning features.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Bench

sample size not stated

endpoints: verify that the subject device met all design specifications, as was Substantially Equivalent (SE) to the predicate device; complies with the following standards

standards: AAMI ANSI EC57:2012 Testing And Reporting Performance Results Of Cardiac Rhythm And ST-Segment Measurement Algorithms, IEC 60601-2-47:2012 Medical Electrical Equipment - Part 2-47: Particular Requirements For The Basic Safety And Essential Performance of Ambulatory Electrocardiographic Systems, IEC 60601-2-25:2011, Medical Electrical Equipment – Part 2-25: Particular requirements for the safety of electrocardiographs, IEC 62304 Edition 1.1 2015-06, Medical device software - Software life-cycle, ISO 14971:2007, Medical devices-Application of risk management to medical device

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

9
recalls in product code, 24mo
72
MAUDE reports in code, 12mo
+26%
vs code's own 3-yr baseline
3
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code DPS (Braemar Manufacturing, LLC, initiated 2024-12-18): "Not all Electrocardiogram (ECG) events received July 2022-July 2024 were not properly routed and subsequently reviewed due to an analysis step being disabled with the monitoring se" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:95837

  • recall_reason_pattern

    Software/algorithm-related recall in product code DPS (Baxter Healthcare Corporation, initiated 2024-10-11): "There is the potential for exam files being assigned duplicate Unique Identifiers (UIDs),. If the system receiving the DICOM file (e.g., Picture Archiving and Communication System" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:95559

  • recall_reason_pattern

    Software/algorithm-related recall in product code DPS (Schiller, Ag Altgasse 68 Baar Switzerland, initiated 2024-07-24): "Potential for high-frequency signal artifacts is recorded during an ECG acquisition performed by CARDIOVIT AT-180 electrocardiographs." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:95074

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/K200036