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Infrared Thermometer is intended to detect body temperature from forehead in the population including infant (above 6 months), child, adolescent, and adult.

The proposed device, Infrared Thermometers, which includes model FR800 and FR850 are hand-held, reusable, battery powered device, which are intended to detect body temperature from forehead for infant (above 6 months), child, adolescent, and adult.

The proposed device is intended for non-contacting infrared temperature measurement. The distance of the measurement is 3cm~5cm.

The proposed device uses a temperature sensor, which can detect the object temperature [human body temperature], environment temperature and temperature of sensor itself; these temperatures are then transfer to electronic signal and amplified; and then it is transferred to digital signal by AD module in MCU of the proposed device. MCU will calculate the body temperature, and then transfer to screen for display.

The Infrared Thermometer, Models FR800 and FR850, underwent non-clinical and clinical testing to demonstrate its substantial equivalence to the predicate device, Microlife Digital Infrared Forehead Thermometer, Model FR1MN1-1 (K161728).

1. Acceptance Criteria and Reported Device Performance:

2. Sample Size for Test Set and Data Provenance:

• Sample Size: Not explicitly stated in the provided text for the clinical study. It mentions "Controlled human clinical studies were conducted," but not the number of subjects.
• Data Provenance: Not explicitly stated (e.g., country of origin). The testing was conducted in accordance with ASTM E 1965-98(2003) which is an American standard, implying the study might adhere to practices commonly found in regions where this standard is adopted, but specific origin is not mentioned. The sponsor and correspondent are based in China, suggesting the possibility of data collection there or involvement of Chinese entities in the study.

3. Number of Experts and Qualifications:

• This information is not provided in the given document. The document refers to non-clinical and clinical testing, but does not detail the specific involvement or qualifications of experts for establishing ground truth within the clinical trial context.

4. Adjudication Method for the Test Set:

• This information is not provided in the given document.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. The clinical testing focused on the standalone performance of the device ("clinical accuracy of the proposed device is not inferior to that of predicate device") rather than its effect on human reader performance.

6. Standalone Performance Study:

• Yes, a standalone (algorithm only without human-in-the-loop performance) study was done. The non-clinical tests (Electrical Safety, EMC, Performance standards, Biocompatibility, Software V&V) and the clinical accuracy evaluation directly assess the device's inherent performance. The clinical study evaluated the device's standalone ability to measure body temperature accurately, comparing it to the performance requirements in standards and to the predicate device.

7. Type of Ground Truth Used:

• For the clinical study, the ground truth was based on clinical validation for infrared thermometer following ASTM E 1965-98(2003). This standard typically involves comparing the device's readings against a highly accurate reference thermometer (e.g., a mercury-in-glass or electronic contact thermometer in a controlled environment), often with a core body temperature measurement as the gold standard. The document states "clinical bias, clinical uncertainty and clinical repeatability have been evaluated per clinical validation."

8. Sample Size for the Training Set:

• This information is not applicable as this device (Infrared Thermometer) is a hardware medical device that directly measures a physical parameter. It does not use algorithms that require a "training set" in the context of machine learning. The "software verification and validation" mentioned refers to traditional software engineering processes, not machine learning model training.

9. How Ground Truth for Training Set Was Established:

• This information is not applicable for the same reason as point 8.

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Wrist Type Automatic Blood Pressure Monitor is a digital monitor intended for use in measuring blood pressure and pulse rate in adult patient population who can understand the instruction manual with the wrist circumference range printed on the wrist cuff. The intended wrist circumference is 13.5-19.5 cm.

The proposed device, Wrist Type Automatic Blood Pressure Monitor, is a battery driven automatic non-invasive blood pressure monitor. It can automatically complete the inflation and measurement, which can measure systolic and diastolic blood pressure and pulse rate of the adult person at wrist within its claimed range and accuracy via the oscillometric technique. User can select the unit of the measurement: mmHg or KPa.

The device has the data storage function in order for data reviewing, including the systolic pressure, diastolic pressure, pulse rate and measurement time. It has a bar indicating function, which can indicate the WHO (World Health Organization) Blood Pressure Classification of the measured blood pressure by referencing Diastolic Blood Pressure issued at Journal of Hypertension 1999. Vol 17, No.2.

The proposed 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 5 models, which are BP165W, BP180W, BP186W and BP 188W. All models follow the same software, measurement principle and NIBP algorithm. The main differences are product appearance and key numbers.

The provided text describes the acceptance criteria and a clinical study for the Wrist Type Automatic Blood Pressure Monitor (Models: BP165W, BP180W, BP186W, BP188W) by Shenzhen Jiacom Technology Co., Ltd.

Here's a breakdown of the requested information:

1. A table of acceptance criteria and the reported device performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document states that a clinical accuracy study was conducted according to ISO 81060-2:2013. This standard details the requirements for clinical validation of automated non-invasive sphygmomanometers. While the specific sample size, country of origin, and whether the data was retrospective or prospective are not explicitly stated in this document, adherence to ISO 81060-2:2013 generally implies:

• A minimum of 85 participants for clinical testing to ensure a statistically robust evaluation (as per the standard's requirements for phase II testing).
• A prospective study design, as the standard describes a protocol for conducting direct comparisons against a reference measurement.
• Data provenance would be from the site where the clinical validation was performed, but the specific country is not mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Again, the document does not explicitly state the number or qualifications of experts. However, for a clinical validation study adhering to ISO 81060-2:2013, the ground truth (reference blood pressure measurements) is typically established by trained observers (experts) using a mercury or auscultatory sphygmomanometer. The standard requires the observers to be trained and qualified, often with specifications regarding their experience and successful completion of a training program to minimize inter-observer variability.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

For clinical validation studies following ISO 81060-2:2013, the standard dictates that reference blood pressure measurements be taken simultaneously by at least two trained observers using an auscultatory method. If there is a significant discrepancy between the two observers' readings, a third observer might be involved (though the standard prioritizes agreement between the initial two). So, a 2 (two trained observers) method is implied, with potential for adjudication if specified by the study protocol compliant with the standard.

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

There is no indication that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was conducted, nor is there any mention of "AI assistance" or "human readers" in the context of blood pressure measurement in this document. This device is an automatic blood pressure monitor, not an AI-assisted diagnostic tool requiring human interpretation.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, the primary clinical validation conducted was a standalone performance study of the device's algorithm. The document states that the "clinical accuracy of the proposed device was evaluated per... ISO 81060-2 Second Edition 2013-05-01." This standard specifically assesses the automated device's ability to measure blood pressure without human intervention (other than proper placement and initiation of the measurement), comparing its readings to simultaneously obtained reference measurements.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

The ground truth used for the clinical validation would be expert reference measurements obtained using a validated auscultatory method (e.g., mercury sphygmomanometer) as mandated by the ISO 81060-2:2013 standard.

8. The sample size for the training set

The document does not provide any information about a "training set" or algorithm development. The information focuses on the clinical validation of an already developed device. Automatic blood pressure monitors based on oscillometric techniques often rely on established algorithms and calibration methods rather than machine learning "training sets" in the contemporary sense.

9. How the ground truth for the training set was established

As no training set is described in the provided information, the method for establishing its ground truth is also not mentioned.

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