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The ECP-MC3 device is intended for the treatment of chronic stable angina that is refractory to optimal anti-anginal medical therapy and without options for revascularization. It is intended for use in healthy patients to provide improvement in vasodilation, and increased blood flow. It is intended for use under the oversight of a healthcare professional.

ECP-MC3 is the most updated designed External Counter Pulsation System for non-invasive treatment of certain cardiovascular and other ischemia related diseases. The ECP-MC3 system is computer-controlled system that inflates and deflates three pairs of air cuffs in synchronization with the patient's cardiac cycle. The three pairs of cuffs are wrapped around the calves, lower thighs, and upper thighs/buttocks of the patients. As diastole begins, the cuffs inflate separately in sequence from the calves, to the lower thighs, to the upper thighs including the lower buttocks. This inflation sequence generates and impels a counter-pulsation wave, increasing diastolic blood pressure (diastolic augmentation), coronary perfusion pressure and coronary blood flow, and raising cardiac output. The start of inflation, deflation and cuff pressure can be adjusted by the operator. The system will deflate simultaneously before systole, this will reduce the heart's workload and resistance of blood vessel. Before ECP treatment, ECG electrodes and Finger Clip plethysmograph Sensor are placed on the patient. The ECG waveform is used to generate triggering signals for cuff inflation and deflation. The plethysmograph waveform is used to monitor the proper timing of the inflation cycle and to indicate the effect of ECP treatment on patient homodynamic.

The provided text describes the 510(k) premarket notification for the "External Counter Pulsation System; Model ECP-MC3". This document focuses on demonstrating substantial equivalence to legally marketed predicate devices, rather than proving the device's efficacy through clinical trials or detailed performance metrics against defined acceptance criteria typically seen for AI/ML devices. As such, the standard information requested for AI/ML device acceptance criteria and study design is not present in this document.

Here's a breakdown of why this document doesn't contain the requested information:

• Device Type: The ECP-MC3 is an External Counterpulsation System, a mechanical medical device, not an AI/ML diagnostic or therapeutic device.
• Regulatory Pathway: A 510(k) submission primarily relies on demonstrating substantial equivalence to a predicate device, meaning it has the same intended use, technological characteristics, and safety/effectiveness profile, or if there are differences, they do not raise new questions of safety or effectiveness. This is different from the rigorous performance testing and clinical trials often required for novel or AI/ML-driven devices.
• Focus of Testing: The non-clinical testing mentioned focuses on reliability, pressure control timing, pressure range accuracy, electrical safety, electromagnetic compatibility (EMC), and software verification/validation. These are standard engineering and safety tests for this type of device, not an assessment of AI algorithm performance.
• Lack of AI/ML Specifics: There is no mention of algorithms, machine learning models, training data, ground truth establishment, expert readers, or MRMC studies, which are all pertinent to AI/ML device evaluations.

Therefore, I cannot provide the requested information in the format of a table for acceptance criteria and reported performance, nor can I detail the specifics of an AI/ML study (sample size, experts, adjudication, MRMC, standalone performance, training data) because this information is not applicable to or contained within the provided 510(k) summary for the ECP-MC3 device.

The document explicitly states: "Clinical data were not required in this submission to support a finding of substantial equivalence." and "Clinical performance is not deemed necessary." This further emphasizes that direct performance measurement against clinical outcomes or a specific ground truth, as would be expected for an AI/ML device, was not part of this regulatory submission.

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