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AGE Automatic Upper Arm Blood Pressure Monitor is intended for use by medical professionals or at home to monitor and display diastolic, systolic blood pressure and pulse rate on adult each time, with the cuff around the left upper arm according to the instruction in the user's guide manual.

AGE Automatic Upper Arm Blood Pressure Monitor is a battery driven automatic non-invasive blood pressure meter. It can automatically conduct the inflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult at arm within its claimed range and accuracy via the Oscillometry technique. The device also has low voltage indication, which will be triggered when the battery is low.

The provided text describes a 510(k) submission for an Automatic Upper Arm Blood Pressure Monitor. It focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the device meets specific acceptance criteria based on a clinical trial.

Therefore, many of the requested details about acceptance criteria, study design, expert ground truth, and human-in-the-loop performance are not available in this document, as they are typically associated with performance validation studies for AI/ML devices or new diagnostic methods, not blood pressure monitors seeking 510(k) clearance based on substantial equivalence to an existing device.

However, I can extract the relevant information regarding performance standards and comparisons that are mentioned:

1. A table of acceptance criteria and the reported device performance

The document references the standard AAMI / ANSI / ISO 81060-2 Second Edition, Non-Invasive Sphygmomanometers - Part 2: Clinical Validation Of Automated Measurement Type as the key performance standard.

While explicit acceptance criteria are not listed in a table, the standard itself defines accuracy requirements for blood pressure monitors. The device claims the following accuracy, which would implicitly be the performance criteria it aims to meet based on the standard:

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

The document states that the device was evaluated for "safety and performance by lab bench testing" and refers to "Clinical Validation Of Automated Measurement Type" according to ISO 81060-2.

• Sample Size: The document does not explicitly state the sample size (number of subjects/measurements) used for the clinical validation. ISO 81060-2 typically specifies minimum patient numbers (e.g., 85 subjects for validation). Without the full study report, the exact sample size cannot be determined from this document.
• Data Provenance: Not explicitly stated. Clinical validation studies for such devices typically involve prospective data collection from human subjects. The document does not specify the country of origin.
• Retrospective/Prospective: Clinical validation according to ISO 81060-2 is inherently prospective, involving live measurements on human subjects.

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

For blood pressure monitor validation (ISO 81060-2), ground truth is established by simultaneous auscultatory measurements performed by trained observers (commonly two, with a third if disagreements arise) using a reference sphygmomanometer. These are not "experts" in the sense of radiologists interpreting images, but rather trained technicians or clinicians. The document does not specify the exact number of observers or their specific qualifications, but the standard mandates specific training and performance for these observers.

4. Adjudication method for the test set

The ISO 81060-2 standard typically employs an adjudication method for reconciling reference blood pressure measurements. Commonly, two trained observers simultaneously measure, and if their readings differ by more than a predefined threshold, a third observer might be used, or the measurements are discarded and re-taken. This is inherent to the standard's methodology, though not explicitly detailed in this summary document.

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, an MRMC study was not done. This type of study is relevant for diagnostic devices, particularly those involving human interpretation, often with AI assistance (e.g., radiology AI). This device is an automatic blood pressure monitor, not an interpretive diagnostic system.

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

Yes, in essence. The primary performance evaluation for an automatic blood pressure monitor is its standalone accuracy against a reference method (auscultation). The device itself is designed to operate automatically, without continuous human intervention during the measurement cycle for interpretation. The reported accuracies (±3 mmHg for pressure, ±5% for pulse) reflect this standalone performance.

7. The type of ground truth used

The ground truth for non-invasive blood pressure monitors typically involves simultaneous auscultatory measurements performed by trained observers using a mercury or an equivalent validated reference sphygmomanometer. This is the "gold standard" for clinical validation of automated blood pressure devices as per ISO 81060-2.

8. The sample size for the training set

This document does not specify a separate "training set" sample size. For traditional medical devices like blood pressure monitors, there isn't typically a distinct "training set" in the machine learning sense. The device's algorithm (oscillometric method) is developed based on physiological principles and engineering, not "trained" on a large dataset of patient readings in the way an AI algorithm learns. The validation is done on a "test set" or clinical study population.

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

As there isn't a "training set" in the AI/ML sense, this question is not applicable. The device's internal algorithms are based on established oscillometric principles for blood pressure determination. Their accuracy is then validated (tested) against the clinical ground truth described in point 7.

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