(319 days)
It is intended for measuring adult blood pressure and pulse rate over-the-counter.
Arm automatic blood pressure monitor is based on pressure vibration method. Blood pressure cuff use the air pump to inflate, then the arteries are extruded by the cuff with pressure. Pressure sensor collects the pressure in the cuff, and then converts it to digital signal to the CPU. Then the software calculates the systolic and diastolic blood pressure and pulse rate.
The arm automatic blood pressure monitor BF1112, BF1112, BF1113 and BF1115 have the same basic principles, main function, performance and intended use, and they are consistent in product structure and material.
Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Acceptance Criteria and Reported Device Performance
| Criteria | Acceptance Criterion | Reported Device Performance |
|---|---|---|
| Accuracy (Blood Pressure) | Pressure: ±3mmHg (±0.4kPa) or 2% of reading (from predicate) | Pressure: ±3mmHg (±0.4kPa) |
| Accuracy (Pulse Rate) | Pulse Rate: ±5% | Pulse Rate: ±5% |
| Measurement Range (Pressure) | 0mmHg~299mmHg (from predicate) | 0mmHg |
| Measurement Range (Pulse Rate) | 40bpm ~ 180bpm | 40bpm ~ 180bpm |
Study Details
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1. Sample size used for the test set and the data provenance:
- Sample Size: The document states that the clinical study was "evaluated according to ANSI/AAMI SP10." However, the exact sample size for the test set is not explicitly mentioned in the provided text. ANSI/AAMI SP10 is a standard for blood pressure measuring devices, and it outlines requirements for clinical validation, including sample sizes (typically a minimum of 85 subjects for accuracy assessment). Without further information, we cannot confirm the precise number of subjects used in this specific study.
- Data Provenance: The document does not specify the country of origin of the data or whether the study was retrospective or prospective. It only mentions that the applicant is from Shenzhen, China, and the predicate device manufacturer is Omron Healthcare, Inc.
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2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This information is not provided in the text. For blood pressure monitors, ground truth is typically established by trained observers taking manual auscultatory measurements using a mercury manometer or a validated oscillometric device, but the number and qualifications of such observers are not detailed here.
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3. Adjudication method for the test set:
- This information is not provided in the text.
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4. 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. This is a blood pressure monitor, not an AI-assisted diagnostic device typically evaluated with MRMC studies comparing human readers. The device is standalone.
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5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Yes. The device is an "Arm automatic blood pressure monitor" and operates as a standalone device, providing blood pressure and pulse rate measurements directly. The clinical study evaluated the device's performance against a standard, implying a standalone assessment of its accuracy.
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6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The ground truth for blood pressure monitor validation, as per ANSI/AAMI SP10, typically involves manual auscultatory measurements performed by trained observers using a reference standard (like a mercury sphygmomanometer). While not explicitly stated as "expert consensus," this method relies on expert human measurement.
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7. The sample size for the training set:
- This information is not provided in the text. For traditional medical devices like this, there isn't typically a distinct "training set" in the sense of machine learning algorithms. The device's underlying algorithm is developed and calibrated, and then its performance is validated against a separate test set. The document only mentions "Laboratory testing" for specification validation.
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8. How the ground truth for the training set was established:
- As there isn't a "training set" described in the machine learning sense, the method for establishing ground truth for a training set is not applicable here. The device's design and calibration would have been based on established physiological principles and engineering practices, likely involving various test conditions and reference measurements during development, but this is distinct from a machine learning training set.
§ 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).