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The Medic4All Telemedicine System Model VMS-01 is intended to collect and transmit physiological information, such as glucose levels, via standard telephone lines or the internet to local or remote computer systems for use by the patient or a healthcare professional.

Medic4All's VMS-01 telemedicine system (VMS-01) is a wireless telephonic/internet-based physiologic monitoring system, designed for care of patients requiring periodic monitoring. It is designed for interactive, remote, physiological data measurement, transmission, processing, storage and display of data.

Here's an analysis of the provided 510(k) submission for the Medic4All Telemedicine System VMS-01, focusing on acceptance criteria and study data:

Acceptance Criteria and Device Performance for Medic4All Telemedicine System VMS-01

Based on the provided K061502 510(k) summary, the device is a telemedicine system for collecting and transmitting physiological information. The performance data focuses on the functional integrity and reliability of the system rather than clinical efficacy or accuracy in diagnosing specific conditions.

1. Table of Acceptance Criteria and Reported Device Performance

It is important to note: The provided document does not specify quantifiable acceptance criteria (e.g., "data transmission success rate > 99%") or detailed performance metrics. The statement "In all instances, the VMS-01 functioned as intended" serves as the general reported performance against implied criteria for each test category.

2. Sample Size Used for the Test Set and Data Provenance

The provided document does not specify a sample size for any test set or the data provenance (e.g., country of origin, retrospective or prospective). The descriptions are general statements about various types of "verification and validation testing activities."

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

The provided document does not mention using experts to establish ground truth for a test set. The validation activities described (EMC/Electrical Safety, unit testing, integration testing, etc.) are engineering and system validation tests, not clinical performance studies requiring expert-adjudicated ground truth.

4. Adjudication Method for the Test Set

As no expert adjudication for a clinical test set is mentioned, there is no adjudication method described.

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

No MRMC comparative effectiveness study (human readers with/without AI assistance) was conducted or reported in this 510(k) submission. This is a telemedicine system for data transmission, not an AI-assisted diagnostic tool.

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

The "performance data" section describes standalone functional testing of the system components and the whole system (e.g., unit testing, integration testing, data integrity testing, load/performance testing). This is algorithm-only in the sense that the system's technical operation was evaluated independently. However, it's not a standalone clinical performance study in the way it might be for a diagnostic AI.

7. The Type of Ground Truth Used

For the functional and reliability testing described (EMC/Electrical Safety, unit, integration, data integrity, usability, environmental, compatibility, performance, system, load/performance testing), the "ground truth" would be established by:

• Engineering specifications and design documents: Whether the system outputs match expected values, whether data is transmitted without corruption, whether modules integrate correctly.
• Standards compliance: For EMC/Electrical Safety, testing against industry and regulatory standards.
• User feedback/defined requirements: For usability testing, whether the system meets pre-defined usability criteria.

It is not clinical ground truth like expert consensus, pathology, or outcomes data, as this device primarily focuses on data collection and transmission functionality.

8. The Sample Size for the Training Set

This device is not an AI/machine learning model that requires a "training set" in the typical sense. It is a telemedicine system composed of hardware and software components. Therefore, no training set sample size is applicable or mentioned.

9. How the Ground Truth for the Training Set Was Established

As there is no training set, this question is not applicable.

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