K Number
K964235
Date Cleared
1999-03-02

(860 days)

Product Code
Regulation Number
870.1130
Panel
CV
Reference & Predicate Devices
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

This portable device, the ABPM Mobil-o- Graph "" Blood Pressure Monitor manufactured by I.E.M. GmbII is an automated, microprocessor controlled blood pressure monitor which monitors, accumulates and stores: heart beat (rate) systolic und diastolic data of a individual adult-patient (in the patient's environment) for a session which may last 24 to 48 hours.

Device Description

ABPM Nobil-o- Graph™ Blood Pressure Monitor, Model ABP Control is a computerized blood pressure system designed for clinical applications to allow physicians or other health care providers to record, store, and playback patient data.

AI/ML Overview

The provided text describes a 510(k) submission for the ABPM Mobil-o-Graph™ Blood Pressure Monitor, Model ABP Control, and references a predicate device. However, it does not contain specific acceptance criteria, performance metrics, or details of a study that proves the device meets such criteria.

The document primarily focuses on establishing substantial equivalence to a predicate device based on shared intended use, functionality (recording, storing, playing back patient data, displaying images, using mathematical computations and proprietary algorithms), and adherence to Good Manufacturing Practices.

Therefore, many of the requested details about acceptance criteria, performance, and study specifics cannot be extracted from this text.

Here's what can be gathered or inferred, with explicit mention of what is not present:

1. A table of acceptance criteria and the reported device performance

Acceptance CriteriaReported Device Performance
Not specified directly in the provided text. The primary "acceptance" is substantial equivalence to the predicate device.No specific performance metrics are reported in the provided text. The document states, "This device is safe and effective for the application for which it is intended and has been tested to confirm safety and efficacy," but provides no data.

2. Sample size used for the test set and the data provenance

  • Sample Size: Not specified.
  • Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

  • Number of Experts: Not specified.
  • Qualifications of Experts: Not specified.

4. Adjudication method for the test set

  • Adjudication Method: Not specified.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

  • MRMC Study: No MRMC study is mentioned. This device is a blood pressure monitor, not an AI-assisted diagnostic tool for "human readers."
  • Effect Size: Not applicable.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

  • A standalone performance assessment would typically be implied for a blood pressure monitor, as it provides direct measurements. However, the results of such a study (e.g., accuracy against a gold standard) are not provided in this document. The text only mentions that "it has been tested to confirm safety and efficacy."

7. The type of ground truth used

  • Type of Ground Truth: Not specified. For a blood pressure monitor, ground truth would typically be established by a reference standard measurement (e.g., invasive arterial line measurement or a highly calibrated manual sphygmomanometer reading) or a clinical standard of care.

8. The sample size for the training set

  • Sample Size: Not applicable/Not specified. This document pertains to a blood pressure monitor, which is not described as an AI/ML device that requires a "training set" in the conventional sense for a model. While it uses "proprietary algorithms" and "mathematical computations," these are not explicitly described as machine learning algorithms requiring a distinct training pipeline.

9. How the ground truth for the training set was established

  • How Ground Truth Established: Not applicable/Not specified, as no training set for an AI/ML model is described.

§ 870.1130 Noninvasive blood pressure measurement system.

(a)
Identification. A noninvasive blood pressure measurement system is a device that provides a signal from which systolic, diastolic, mean, or any combination of the three pressures can be derived through the use of tranducers placed on the surface of the body.(b)
Classification. Class II (performance standards).