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HL168JD uses the oscillometric method to automatically measure systolic and diastolic blood pressure as well as heart rate. The measurement position is at human being's wrist. All values can be read out in one LCD panel. The device is designed for home use and recommended for use by adults aged 18 years and older with wrist circumference ranging approx. 5.37.7 inch (135 195 mm).

HL168JD 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 approx. 5.3~ 7.7 inch (135~ 195 mm) and for home use.

Here's an analysis of the provided text, outlining the acceptance criteria and study details for the HL168JD Full Automatic (NIBP) Blood Pressure Monitor:

Acceptance Criteria and Device Performance

The core acceptance criteria for the HL168JD device are derived from its stated accuracy and compliance with relevant medical device standards for blood pressure monitors.

Table 1: Acceptance Criteria and Reported Device Performance

Study Information

The provided document describes the clinical and non-clinical tests performed to demonstrate the device's safety and effectiveness and its substantial equivalence to a predicate device.

1. Sample Size used for the Test Set and Data Provenance:

   • The document does not explicitly state the sample size (number of subjects/patients) used for the clinical tests that validated the accuracy against standards (ANSI/AAMI SP10, ISO 81060-2, ESH).
   • The data provenance is not explicitly mentioned (e.g., country of origin, retrospective or prospective). However, the mention of "European Society of Hypertension validation according to International Protocol revision 2002" and publication on "dabl website" suggests a clinical study was conducted following international guidelines, likely prospective.

2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

   • The document does not specify the number of experts or their qualifications used to establish the ground truth in the clinical validation studies. For blood pressure monitor validation, this typically involves trained observers taking auscultatory measurements using standardized sphygmomanometers, with dual observation often employed for accuracy.

3. Adjudication Method for the Test Set:

   • The document does not specify the adjudication method used for the clinical test set. In blood pressure validation studies, ground truth is typically established by trained human observers using mercury or calibrated aneroid sphygmomanometers, often with multiple observers to minimize bias and provide a reference.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not mentioned or implied in this document. This type of study is more relevant for diagnostic imaging devices where AI assists human interpretation.

5. Standalone (Algorithm Only) Performance:

   • Yes, the core of the clinical testing involves evaluating the standalone performance of the HL168JD device (the "algorithm only") against established reference measurements. The device itself is an automated non-invasive blood pressure monitor, and its accuracy is assessed independently against the reference standard without human-in-the-loop interpretation being part of the primary clinical validation.

6. Type of Ground Truth Used:

   • For the clinical accuracy validation (compliance to ANSI/AAMI SP10, ISO 81060-2, and ESH International Protocol), the ground truth would be expert reference measurements (e.g., auscultatory blood pressure readings by trained clinicians using calibrated sphygmomanometers) performed concurrently with the device's measurements on the same subjects. The ESH protocol, in particular, has specific requirements for reference measurements.

7. Sample Size for the Training Set:

   • As this device is a standalone blood pressure monitor (not a machine learning/AI diagnostic system in the modern sense), the concept of a "training set" for an algorithm, as typically used in AI/ML, does not apply directly. The device operates based on an oscillometric method with a fixed algorithm, not one that "learns" from data. Therefore, there is no stated training set size.

8. How the Ground Truth for the Training Set Was Established:

   • Since there's no conventionally defined "training set" for this type of device, this question is not applicable. The underlying oscillometric algorithm would have been developed and refined based on engineering principles and physiological models, not through a data-driven machine learning training process.

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