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The Fukuda Denshi VaSera model VS-1500AU is a non-invasive diagnostic system designed to assist in the detection of peripheral vascular diseases. It has a capability of measing non-invasive blood pressures, heart rate, pulse volume recordings and heart sounds.

The device also has the capability of calculating ABI (Ankle Brachial Index), TBI (Toe Brachial Index), and pulse wave velocity measurements.

The device is intended to be used under the order of a physician, in hospitals, doctor's offices, clinics or other medical facilities where non-invasive peripheral vascular tests are performed.

The device is intended to be used on adult population only.

The device is not intended for home use.

The Fukuda Denshi VaSera model VS-1500AU is a prescriptive device intended for use by health care professionals. It is designed to be used to assist the clinician in the detection of peripheral vascular diseases and has been designed and tested to automate published clinical diagnostic test methods. The device is capable of measuring non-invasive blood pressures, non-invasive pulse volume recordings and heart sounds. In addition, the device is capable of calculating specific clinically recognized indices such as ABI (Ankle Brachial Index), TBI (Toe Brachial Index) and pulse wave velocity.

The provided text describes a 510(k) summary for the Fukuda Denshi VaSera Model VS-1500AU. However, it does not contain specific acceptance criteria or the detailed results of a study that proves the device meets such criteria.

The document states: "Final testing for the device included various performance tests, including clinical validation using the predicate device, to insure that all functional and performance specifications were met." and "In conclusion, drawing from laboratory testing, validation and risk Analysis, the Fukuda Denshi VaSera model VS-1500AU demonstrates that this device is as safe and effective and performs as well as the legally marketed predicate devices..."

This indicates that a study (clinical validation) was performed, and the results were found to be satisfactory for substantial equivalence. However, the details of this study, including specific acceptance criteria as quantitative metrics (e.g., minimum sensitivity, specificity, accuracy, or correlation coefficients) and the reported device performance against those criteria, are not provided in this summary.

Therefore, I cannot populate the table or answer many of the questions directly from the provided text.

Here's a breakdown of what can and cannot be answered based on the input:

1. Table of acceptance criteria and reported device performance:

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

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). The text only mentions "clinical validation using the predicate device."

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

• Not specified. The study relied on comparison to a "predicate device" and potentially its established measurements.

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

• 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:

• Not applicable. This device is a diagnostic system that automates measurements, not an AI-assisted interpretation system for human readers. The clinical validation was likely a comparison of its measurements to those of the predicate device, not an MRMC study with human readers.

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

• The "clinical validation using the predicate device" implies a standalone performance assessment of the device's measurements against established methods. The device itself is designed as an automated measurement system.

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

• The "ground truth" for the device's performance would primarily be the measurements obtained from the legally marketed predicate device (Colin Medical VP-1000/2000 and Fukuda Denshi DS-5300 Patient Monitor), as the VaSera VS-1500AU was tested to automate similar diagnostic test methods and was determined to be "as safe and effective and performs as well as" these predicates.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device that requires a distinct "training set" in the conventional sense. The "validation" mentioned refers to testing the device's algorithms and hardware against established methods, not training a machine learning model.

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

• Not applicable, as there is no mention of a training set for an AI/ML model.

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