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The Microlife Wrist Watch Blood Pressure Monitor, Model BP3AX1-4U with semiconductor pressure sensor is a device intended to measure the systolic and diastolic blood pressure and pulse rate of an adult individual by using a technique in which an inflatable cuff is wrapped around the wrist.

The device can be used in connection with your personal computer (PC) running the Microlife Blood Pressure Analyzer (BPA) software. The memory data can be transferred to the PC by connecting the monitor via cable with the PC.

The Microlife Wrist Watch Blood Pressure Monitor, Model BP3AX1-4U is designed to measure the systolic and diastolic blood pressure and pulse rate of an individual by using a technique in which an inflatable cuff is wrapped around the wrist. Our method to define systolic and diastolic pressures is similar to the auscultatory method but uses an electronic semiconductor pressure sensor rather than stethoscope and mercury manometer. The sensor converts tiny alteration in cuff pressure to electrical signals; by analyzing those signals to define the systolic, diastolic and calculating pulse rate is a well known technique in the market called the "oscillometric method". The device can be used in connection with your personal computer (PC) running the Microlife Blood Pressure Analyzer (BPA) software. The memory data can be transferred to the PC by connecting the monitor via cable with the PC.

The provided 510(k) summary for the Microlife Wrist Watch Blood Pressure Monitor, Model BP3AX1-4U, focuses on demonstrating substantial equivalence to a predicate device (Microlife Wrist Watch Blood Pressure Monitor, Model BP3AX1, K#040002) rather than presenting a standalone study with detailed acceptance criteria and performance metrics for the modified device. The key takeaway is that the clinical performance of the modified device is addressed by relying on the predicate device's compliance with the ANSI/AAMI SP10-2002 standard.

Here's an attempt to extract and synthesize the requested information based on the provided text, noting where information is not explicitly available for the modified device's clinical performance:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document explicitly states: "Repeat testing was not performed for the modified device, as clinical testing results were not affected by the changes to the modified device." This means the reported clinical performance refers to the predicate device's performance against the ANSI/AAMI SP10-2002 standard. Specific numerical performance metrics (e.g., mean difference, standard deviation) for blood pressure accuracy as per the AAMI standard are not provided in this summary for either the predicate or the modified device.

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

• Sample Size for Clinical Performance (Predicate Device): Not explicitly stated in the provided text for the clinical study that proved compliance with ANSI/AAMI SP10-2002.
• Data Provenance: Not explicitly stated for any clinical study. The summary focuses on non-clinical and technical tests for the modified device, and refers to clinical testing performed on the predicate device.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

• For Clinical Performance (Predicate Device): Not specified in the provided text. The ANSI/AAMI SP10 standard typically involves comparison against mercury sphygmomanometry performed by trained observers, but the number and qualifications of these observers are not detailed here.
• For Non-Clinical Tests (Modified Device): No experts were involved in establishing ground truth for the non-clinical and technical tests (reliability, EMC, PC-link software).

4. Adjudication Method for the Test Set

• For Clinical Performance (Predicate Device): Not specified. Standard practice for AAMI SP10 validation involves specific procedures for comparing automated readings against auscultatory readings, often involving multiple observers, but the adjudication method (e.g., 2+1, 3+1) is not explicitly detailed.
• For Non-Clinical Tests (Modified Device): Not applicable. These tests are objective pass/fail based on engineering specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance

• No such study was performed. This type of study is not relevant to a blood pressure monitor, which is a standalone measurement device, not an AI-assisted diagnostic tool for interpretation by human readers.

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

• Yes, in essence. The blood pressure monitor itself is a standalone device that provides measurements via its internal algorithm. The "oscillometric method" is an algorithm. The clinical testing of the predicate device against the ANSI/AAMI SP10-2002 standard essentially represents a standalone performance evaluation of the device's algorithm against a recognized standard reference method (auscultatory measurement).

7. The Type of Ground Truth Used

• For Clinical Performance (Predicate Device): The ground truth for blood pressure measurement against the ANSI/AAMI SP10-2002 standard would typically be auscultatory blood pressure measurements performed by trained observers using mercury sphygmomanometers. This is generally considered an "expert consensus" or "reference standard" method in this context.
• For Non-Clinical Tests (Modified Device): The ground truths were engineering specifications and functional requirements (e.g., successful data transfer for PC-link).

8. The Sample Size for the Training Set

• Not applicable / Not specified. The device uses the "oscillometric method," which is a well-known, established algorithm, not typically "trained" in the sense of modern machine learning models with large datasets. If there were any algorithmic refinements based on data, the size of that data is not mentioned in the summary.

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

• Not applicable / Not specified. As noted above, the "oscillometric method" is a long-established technique. The summary does not describe a machine learning training process.

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The Microlife Wrist Watch Blood Pressure Monitor, Model BP3AX1 is a device intended to measure the systolic and diastolic blood pressure and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the wrist.

The Microlife Wrist Watch Blood Pressure Monitor BP3AX1 is designed to measure the systolic, diastolic and pulse rate of an individual by using a non-invasive technique with an inflatable cuff wrapped around wrist. Our method to define systolic and diastolic pressure is similar to the auscultatory method but uses an electronic semiconductor pressure sensor instead of a stethoscope and uses an electronic convention to define the systolic, diastolic and electrical signals, by analyzing those signals. The method for calculating pulse rate is a well known technique in the market and is the so called "oscillometric method".

The provided text describes the Microlife Blood Pressure Monitor Model BP3AX1 and its 510(k) submission. However, it does not contain a detailed table of acceptance criteria, reported device performance metrics, or a comprehensive study report with the specific information requested in your prompt (e.g., sample sizes for test/training sets, ground truth establishment details, MRMC study results, etc.).

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Microlife Wrist Watch Automatic Blood Pressure Monitor, Model BP-3BU1-5, K# 021305) and lists the non-clinical and clinical tests performed at a high level.

Here's what can be extracted and what is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: The document states that the device "met all relevant requirements" of AAMI SP10-1992. However, it does not provide the specific numerical acceptance criteria (e.g., mean difference, standard deviation limits) or the actual measured performance data (e.g., 2.3 mmHg ± 5.6 mmHg) from the clinical study. Similarly, for non-clinical tests, it only states "None of the testing demonstrated any design characteristics that violated the requirements" and "the relevant requirements...were met," without providing specific pass/fail criteria or quantitative results.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size for Test Set: Not specified. The document mentions that ANSI/AAMI SP10-1992 testing was performed, but does not provide the number of subjects or measurements included in this clinical validation.
• Data Provenance: Not specified. The document does not mention the country of origin of the data or whether the study was retrospective or prospective. Given the nature of a clinical validation study for a blood pressure monitor, it would typically be prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable/Not specified. For a blood pressure monitor, "ground truth" during clinical validation is typically established by trained human observers using a mercury sphygmomanometer simultaneously or sequentially with the automated device on the same subject, following a standardized protocol like AAMI SP10. The document does not specify the number or qualifications of these human observers.

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

Not specified. The document does not describe any specific adjudication method for discrepancies during the clinical testing. For AAMI SP10, there are specific requirements for agreement between observers, but the details of implementation are not provided here.

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 an automated blood pressure monitor, not an AI-assisted diagnostic tool that would typically involve "human readers" or "AI assistance" in the sense of image interpretation or complex clinical decision support. Therefore, an MRMC study and effect size for human readers improving with AI are not relevant to this type of device.

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

Yes, effectively. The "standalone" performance here refers to the device's ability to accurately measure blood pressure on its own. The clinical testing against the ANSI/AAMI SP10-1992 standard is a standalone performance evaluation of the automated device against a reference standard (typically a trained human observer using a mercury sphygmomanometer). The results state that "All relevant sections were met," indicating its standalone performance was deemed acceptable.

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

The ground truth for the clinical study would have been established by trained human observers using a reference standard (e.g., auscultation with a mercury sphygmomanometer), as prescribed by the ANSI/AAMI SP10-1992 standard. This is the accepted method for validating automated blood pressure devices.

8. The sample size for the training set

Not applicable/Not specified. This is an oscillometric blood pressure monitor, not a machine learning or AI-based device that typically requires a distinct "training set" in the context of model development. The algorithm for oscillometric measurement is well-established, and its "training" would be more akin to calibration and design refinement rather than statistical model training. If any internal data was used for initial algorithm development or parameter tuning, it is not disclosed as a "training set" here.

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

Not applicable/Not specified. As mentioned above, a "training set" in the context of machine learning is not directly applicable here. The fundamental principles of oscillometric measurement are physics-based, and calibration procedures would rely on traceable pressure standards, not "ground truth" derived from clinical data in the same way an AI model's training data would be established.

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