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The device is a digital monitor intended for use in measuring blood pressure and pulse rate in adult patient population with wrist circumference ranging from 5 3/8 inches (13.5cm to 19.5cm). The device detects the appearance of irregular hearbeats during measurement and gives a warning signal with reading.

The Wrist Blood Pressure Monitor,Models: 222,222BT,W1681BL, W1681BT, W1681R are powered by a rechargable Li-ion battery, automatic, non-invasive blood pressure system intended for home use. The devices are intended for use in adult patient population with wrist circumference ranging from 5 3/8 inches to 7 2/3 inches (13.5 cm). The devices' wrist cuff inflates using an integral pump and deflates via an electric valve. During deflation, the wrist cuff pressure is monitored and pulse waveform data is extracted. The extracted pulse waveform data is then analyzed by software which determines pulse rate, as well as systolic and diastolic blood pressure. The systolic and diastolic blood pressures are measured using the oscillometric method. The cuff can measure pressure range from 0 to 295 mmHg, and the pulse rate range from 40 to 199 beats/min.

When the device detected irregular rhythms, " W " will display on screen. An irregular heartbeat rhythm is defined as a rhythm that is 25% less or 25% more than the average rhythm detected while your monitor is measuring blood pressure. The WHO blood pressure indicator bar can classify by WHO and ISH recommendation. The devices display the latest blood pressure reading, while up to 2 x 99 readings can be stored in memory.

Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided text:

Device Name(s): Wrist Blood Pressure Monitor (Models: 222, 222BT, W1681BL, W1681BT, W1681R)

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 86 subjects.
• Data Provenance: Clinical investigation conducted by Shenzhen Cihai Hospital (China), prospective study.

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

The document does not explicitly state the number of experts or their specific qualifications (e.g., years of experience for physicians/nurses performing the reference measurements). It states that the "auscultatory method (mercury sphygmomanometer)" was used as the reference standard, implying trained human operators.

4. Adjudication Method for the Test Set

The document states that the mean value and standard deviation of differences between the device and the mercury sphygmomanometer were calculated according to ISO 81060-2:2018. This suggests a direct comparison rather than a multi-reader adjudication process in the traditional sense for medical imaging or diagnostic algorithms. For blood pressure measurement, the reference standard (auscultatory method) intrinsically relies on trained observers.

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 MRMC comparative effectiveness study was done. This type of study is not applicable to a standalone wrist blood pressure monitor, which directly measures physiological parameters rather than assisting human readers in interpreting complex data.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance study was done for the device's accuracy in measuring blood pressure and pulse rate. The device operates independently to provide these measurements.

7. The Type of Ground Truth Used

The ground truth for the clinical accuracy study was established using the auscultatory method with a mercury sphygmomanometer, as described in ISO 81060-2:2018. This is considered a gold standard for non-invasive blood pressure measurement.

8. The Sample Size for the Training Set

The document does not specify a separate training set or its sample size. The clinical study described appears to be for validation/testing, not for training a model. Blood pressure monitors typically implement algorithms based on established physiological principles (oscillometry) and are calibrated, rather than "trained" in the machine learning sense with a distinct training dataset.

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

As no specific "training set" for an AI algorithm is mentioned in the context of the device's accuracy claims, this question is not directly applicable. The device's underlying measurement principle (oscillometric method) and its calibration would rely on established scientific and engineering practices, not on ground truth established from a training dataset in the AI sense.

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