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510(k) Data Aggregation
(123 days)
HL168KB automatically measures human's Systolic, Diastolic blood pressure and heart rate by using the oscillometric method. All values can be read out in one LCD panel. Measurement position is at human being's wrist. The intended use of this over-the-counter device is for over the age of 18 with wrist circumference ranging from 135 mm to 195 mm (Approx. 5.3~7.7 inches) and for home use.
When the device detects the appearance of irregular heartbeats during measurement, an indicated symbol will appear with measuring readings. And this device can let the storage data be transferred to the connected personal computer (PC) via USB cable.
HL168KB automatically measures human's Systolic. Diastolic blood pressure and heart rate by using the oscillometric method. All values can be read out in one LCD panel. Measurement position is at human being's wrist. The intended use of this over-the-counter device is for over the age of 18 with wrist circumference ranging from 135 mm to 195 mm (Approx. 5.3~7.7 inches) and for home use.
The user is able to set the personal target value and the device will flash the value when the measured blood pressure value exceeds the target one. Also, user can save and manage the measurement data by transferring the measured readings of blood pressure to the connected personal computer (PC) via USB cable.
Additionally, the device will display a symbol of wordlis, to indicate the detection of irregular heartbeat rhythm as defined as a rhythm is more than or less than 25% from the average heartbeat during the measurement.
This document describes the premarket notification for the Full Automatic (NIBP) Blood Pressure Monitor, Model HL168KB.
Here's an analysis of the acceptance criteria and the study that proves the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Accuracy (Pressure) | ± 3 mmHg |
| Accuracy (Pulse) | ± 5% |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It only mentions that the device is compliant with the ANSI/AAMI SP-10:2002+A1:2003+A2:2006 Standard for Manual, electronic, or automated sphygmomanometers and that "All the relevant activities were performed by designate individual(s) and the results demonstrated that the predetermined acceptance criteria were fully met."
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
The document does not provide information on the number of experts used to establish ground truth or their qualifications. The ANSI/AAMI SP-10 standard itself outlines the methodology for clinical validation, which typically involves a comparison against a reference standard measured by trained observers (experts). However, the specific details of the experts for this study are not included in this summary.
4. Adjudication Method for the Test Set
The document does not specify an adjudication method like 2+1 or 3+1. The ANSI/AAMI SP-10 standard outlines statistical methods for comparing the device measurements to reference measurements, but it doesn't describe an adjudication process for disagreeing expert measurements in the way it might for image-based diagnostic studies. It focuses on the agreement between the device and the reference measurement.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is more common for diagnostic imaging or screening devices where human readers interpret results, and the AI's role is to assist or replace human interpretation. For a blood pressure monitor, the device provides a direct measurement, and the "human reader" aspect is not applicable in the same way. The study focuses on the accuracy of the device's measurements against a reference standard.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, a standalone performance study was done. The study assesses the accuracy of the HL168KB device itself, without human intervention in the measurement process after initial cuff placement and operation. The device "automatically measures human's Systolic, Diastolic blood pressure and heart rate by using the oscillometric method," indicating a standalone algorithm-only performance.
7. The Type of Ground Truth Used
The ground truth used for blood pressure monitors compliant with ANSI/AAMI SP-10 standards is typically simultaneous auscultatory measurements performed by trained observers (experts) using a mercury sphygmomanometer or another validated reference device. This is the gold standard for non-invasive blood pressure measurement in clinical validation studies. The document implicitly refers to this by stating compliance with the ANSI/AAMI SP-10 standard.
8. The Sample Size for the Training Set
The document does not specify a training set sample size. This type of device relies on established oscillometric principles and algorithms for blood pressure measurement, which are typically developed and refined over time, rather than being "trained" on a specific dataset in the way a modern AI/machine learning model might be. Compliance with ANSI/AAMI SP-10 primarily focuses on clinical validation of the final product, not the developmental "training" phase.
9. How the Ground Truth for the Training Set Was Established
As above, the document does not discuss a "training set" in the context of recent AI/ML development. The fundamental principles of oscillometric blood pressure measurement are based on physiological understanding and engineering design. The "ground truth" during the development and calibration of such devices would have been established through extensive physiological studies and comparisons with invasive arterial pressure measurements or validated non-invasive methods to refine the algorithms for converting cuff oscillations into blood pressure values. This is part of the engineering development process rather than a specific "training set" as understood in current AI contexts.
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