K Number
K220651
Date Cleared
2022-06-30

(115 days)

Product Code
Regulation Number
870.1130
Panel
CV
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

This device is intended to measure the systolic blood pressure as well as the pulse rate of adult by using the wrist circumference 12.5-21.5cm, it can be used in medical facilities or at home. It is supplied for OTC use.

Device Description

The subject device, Wrist Type Blood Pressure Monitor, is a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure and pulse rate of adults at wrist within its claimed range and accuracy via the oscillometric technique. The device has data storage function for data reviewing, including the systolic pressure, diastolic pressure, pulse rate and measurement time. The subject device is intended to be used in medical facilities or at home. And it is provided non-sterile, and not to be sterilized by the user prior to use. The proposed blood pressure monitor includes three models, which are W02S. W1102. W1102A. All models contain the same software. measurement principle and NIBP algorithm. The main differences are product appearance and the specification of solenoid Valve.

AI/ML Overview

The provided text describes the acceptance criteria and the study that proves the device (Wrist Type Blood Pressure Monitor) meets those criteria, primarily focusing on its clinical accuracy.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The device's clinical accuracy was evaluated according to ISO 81060-2:2018 (Third edition 2018-11). This standard sets the clinical acceptance criteria for automated non-invasive sphygmomanometers. While the specific numerical acceptance criteria (e.g., mean difference and standard deviation limits) from ISO 81060-2 are not explicitly detailed in the provided text, the summary states:

"The results of this clinical investigation show that the required limits for mean error and standard deviation are fulfilled by the subject device W1102 in the group of 95 adult subjects (56 male and 39 female) with qualified distribution."

And under Accuracy in the comparison table:

CriteriaAcceptance Criteria (Predicate)Reported Performance (Subject Device)
Pressure Accuracy±3mmHg±3mmHg (±0.4kPa)
Pulse Accuracy±5%±5% BPM

This is a direct comparison to the predicate device's accuracy, which the subject device matches. The clinical study further supports that these accuracy limits were met according to the ISO standard.

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

  • Sample Size: 95 patients (56 males and 39 females)
  • Data Provenance: The document does not explicitly state the country of origin. It indicates it was a "Clinical Test report" and mentions "95 patients were invited for the study." The manufacturer is based in Shenzhen, China, so it is highly probable the study was conducted there.
  • Retrospective or Prospective: The wording "95 patients were invited for the study" strongly suggests a prospective clinical study.

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

The ground truth for the clinical accuracy study was established using the standard auscultation method as the reference blood pressure monitor. This method typically involves trained medical professionals (e.g., nurses, doctors) taking manual blood pressure measurements. However, the document does not specify the number of experts or their qualifications.

4. Adjudication Method for the Test Set

The document mentions that blood pressure measurements were "repeated alternatively with the device and auscultation in the same arm according to the sequence in ISO 81060-2 Third edition 2018-11." This standard outlines specific protocols for comparing automated devices to a reference method, often involving multiple measurements and averaging. However, it does not explicitly describe an adjudication method in the sense of resolving discrepancies between multiple expert readers for image interpretation (which is common for AI/ML device studies). For blood pressure measurement, the auscultation method itself serves as the direct reference.

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 comparative effectiveness study was not done. This device is a standalone blood pressure monitor, not an AI/ML-assisted diagnostic tool that would typically involve human readers interpreting AI output. The study focused on the device's accuracy compared to a gold standard (auscultation).

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

Yes, a standalone performance evaluation was done. The clinical accuracy study assessed the device's ability to accurately measure blood pressure on its own, comparing its readings directly to those obtained via the auscultation method. This is a "standalone" evaluation of the device's measurement algorithm.

7. The Type of Ground Truth Used

The type of ground truth used was comparative measurement against a recognized gold standard: the standard auscultation method for blood pressure measurement.

8. The Sample Size for the Training Set

The document does not specify a separate "training set" sample size. For traditional medical devices like blood pressure monitors, the "training" (i.e., development and calibration) is typically done internally by the manufacturer during the product design phase, and the document focuses on the test set used for regulatory submission and clinical validation. There's no indication of an AI/ML model that would require a distinct training set in the context of this FDA submission.

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

As there's no mention of a distinct training set for an AI/ML algorithm in the context of this blood pressure monitor, the question about "ground truth for the training set" is not applicable in the way it typically applies to AI/ML devices. The device's underlying algorithm for oscillometric measurement is part of its design, calibrated through internal processes. The submitted study focuses on the validation of the final device's performance against clinical standards.

§ 870.1130 Noninvasive blood pressure measurement system.

(a)
Identification. A noninvasive blood pressure measurement system is a device that provides a signal from which systolic, diastolic, mean, or any combination of the three pressures can be derived through the use of tranducers placed on the surface of the body.(b)
Classification. Class II (performance standards).