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The MESI mTABLET ECG is indicated for use on adult or pediatric patients, to evaluate and diagnose patient cardiac function.

MESI mTABLET ECG is intended to measure heart activity by ten (10) electrodes placed on the patient's body which measure miniscule electrical activity generated by the heart muscle depolarizations.

The MESI mTABLET ECG is solely used in professional clinical environment by trained healthcare personnel. The MESI mTABLET ECG provides information regarding the patient's cardiac function. The physician has the responsibility of making proper judgments based on this information.

Prescription Use: Federal law restricts the use of this device to sale by or on the order of a physician.

The MESI mTABLET ECG portable 12 lead resting ECG system is intended to screen cardiac abnormalities. The MESI mTABLET ECG System acquires, permits viewing and storing signals from adult and pediatric patients. The MESI mTABLET ECG is one of several variations of the company's MESI mTABLET system portfolio.

MESI mTABLET ECG is intended to measure heart activity by ten electrodes placed on the patient body which measure miniscule electrical activity generated by heart muscle depolarizations. This activity is captured and displayed on the MESI mTABLET UNIT. The MESI mTABLET ECG supports acquisition of 10 seconds signal or manual mode with acquisition up to 5 minutes.

The MESI mTABLET ECG provides analytical statements when configured with the appropriate options. It also comes with Glasgow algorithm for automatic interpretation which offers dagnostic opinion is not intended to constitute professional advice, diagnosis or treatment, or be a substitute for professional judgment.

The request asks for specific details about the acceptance criteria and study that proves the device meets them. However, the provided document is a 510(k) summary for an FDA clearance, which focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed acceptance criteria and a performance study for a new algorithm.

Here's a breakdown of why the requested information cannot be fully extracted and what can be inferred:

The document does not contain:

• A table of explicit "acceptance criteria" for an algorithm's performance (e.g., sensitivity, specificity thresholds at a certain operating point).
• Details of a standalone study proving a new algorithm's performance against specific acceptance criteria. The Glasgow algorithm is a commercially available, previously developed and validated algorithm, not a new algorithm developed by MESI D.O.O. for this specific device.
• Sample sizes, data provenance, number of experts, adjudication methods for ground truth, or MRMC study results related to a new algorithm's diagnostic performance.
• Training set information for a new algorithm.

What can be extracted or inferred from the document:

1. A table of (implied) acceptance criteria and the reported device performance:

Since this is a substantial equivalence submission, the "acceptance criteria" are implicitly met by demonstrating that the device performs "as well as or better than" the predicate device and conforms to recognized standards for electrocardiographs.

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

• The document states, "No clinical data is required to determine substantial equivalence." This implies that no primary clinical test set was used by MESI D.O.O. to validate the diagnostic performance of its device's interpretation against specific acceptance criteria. The performance of the Glasgow algorithm itself would have been established historically by its developers.

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

• Not applicable for this submission, as no new clinical test data was presented for algorithm performance. The Glasgow algorithm's validation would have involved expert review at the time of its original development.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable for this submission, as no new clinical test data was presented for algorithm performance.

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 study was reported in this document. The device offers "analytical statements when configured with the appropriate options" and uses the "Glasgow algorithm for automatic interpretation," but explicitly states this "diagnostic opinion is not intended to constitute professional advice, diagnosis or treatment, or be a substitute for professional judgment." This indicates it's an aid, but its effectiveness in improving human reader performance was not quantified in this submission.

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

• A standalone performance assessment of the Glasgow algorithm would have been conducted by its original developers. This submission did not report a new standalone performance study for the MESI mTABLET ECG's interpretation capabilities. It leverages an existing, commercially available algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

• Not applicable for this submission regarding new algorithm validation. The underlying Glasgow algorithm would have been validated using clinically established ground truth, likely expert interpretation of ECGs.

8. The sample size for the training set:

• Not applicable. The Glasgow algorithm is a pre-existing, commercially available algorithm. MESI D.O.O. integrated this algorithm; they did not train a new algorithm.

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

• Not applicable, as MESI D.O.O. did not train a new algorithm. The ground truth for the Glasgow algorithm's training would have been established by its developers.

In summary: The provided document is an FDA 510(k) submission focused on demonstrating substantial equivalence, mainly through technical comparisons and adherence to standards, rather than proving the diagnostic performance of a novel AI algorithm with specific acceptance criteria and a dedicated study. The device integrates a well-known, pre-existing algorithm (Glasgow algorithm), whose performance validation would have occurred prior to its integration into this device.

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