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The MI-1000 system is used to measure Wavelet Surface Residuum indices at rest and during low level electrical stimulation during the cardiac refractory period. This data is presented in a graphical format for interpretation by a trained physician. The MI-1000 system is also used for the measurement of SAECG indices. The MI-1000 system should be used only as an adjunct to clinical history and the results of other noninvasive and /or invasive tests.

The device consists of an IBM compatible PC, nine skin surface electrodes, one electronics board, a patient interface module and software. Seven of the electrodes are used for sensing cardiac electrical activity. The remaining two electrodes are used to apply low level current pulses (maximum 40 milliamps) to the patient. This technology uses noninvasive, externally applied, subthreshold (low amplitude) far-field stimulus while acquiring electrocardiogram data.

The provided text describes a 510(k) premarket notification for the Micro-Induction 1000 system (MI-1000 System). It focuses on the device's substantial equivalence to a previously cleared version and the performance data for the modified system.

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "A complete software validation and verification was completed to verify that the acquired data was able to be correctly analyzed and the Wedensky indices were correctly calculated and displayed. All testing successfully met the required criteria."

However, specific numerical acceptance criteria (e.g., accuracy, precision thresholds) and the exact reported performance metrics (e.g., specific error rates, percentages of correct calculations) are not detailed in the provided text. The statement above is a general affirmation of successful testing without quantitative measures.

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

No information regarding the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective) is provided.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

No information regarding the number of experts used to establish ground truth or their qualifications is provided.

4. Adjudication Method for the Test Set:

No information regarding the adjudication method is provided.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No MRMC comparative effectiveness study was mentioned. The text states:

• "No clinical testing was required."
• "All of the displayed information is subject to physician interpretation." (This implies a human-in-the-loop scenario, but no study comparing human readers with and without AI assistance is described.)

6. Standalone (Algorithm Only) Performance Study:

The document suggests that the performance evaluation was focused on the "signal post-processing and display" and that "the acquired data was able to be correctly analyzed and the Wedensky indices were correctly calculated and displayed." This implies a standalone performance evaluation of the algorithmic components related to data analysis and calculation.

However, specific metrics for this standalone performance (e.g., accuracy of calculations, error rates in post-processing) are not provided. The statement "All testing successfully met the required criteria" is a general summary.

7. Type of Ground Truth Used:

The ground truth used to verify the software performance would primarily be known reference values or expected outcomes for the "acquired data" and "Wedensky indices" calculations. Since it's a software validation for calculation and display, it would involve comparing the system's output against a defined correct output for specific inputs. This is a form of "truth by design" or "truth by calculation correctness" rather than expert consensus on medical findings or pathology.

8. Sample Size for the Training Set:

No information regarding the sample size for the training set is provided. The document focuses on modifications to an existing system's post-processing and display, implying less emphasis on a de novo machine learning model's training.

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

No information regarding the establishment of ground truth for a training set is provided. Given the nature of the device (signal processing and display modifications to an existing technology), it's unlikely that a traditional "training set" with medical ground truth labels was used in the way it would be for a diagnostic AI algorithm. Instead, the validation appears to be focused on the correctness of the mathematical transformations and presentation of data.

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