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The pulse oximeter is a non-invasive device and intended for spot-checking of oxygen saturation and pulse rate for use with the finger of adult patients in healthcare environments. And it is not intended to be used under motion or low perfusion scenarios. The device is reusable.

The oximeter consists of probe, electronic circuits, and display and plastic enclosures. And one side of probe is designed to locate light emitting diodes and a light detector (called a photo-detector). Red and Infrared lights are shone through the tissues from one side of the probe to the other. Then parts of the light emitted absorbed by blood and tissues. The light absorbed by the blood varies with the oxygen saturation of haemoglobin. After that, the photo-detector detects the light volume transmitted through the tissues which depends on blood pulse, Hereafter, the microprocessor calculates a value for the oxygen saturation (SpO2). The subjected device is a reusable device, and need to reprocess as suggested in the user manual after each use. And the device is intended to be used on the finger, and powered by 2*1.5V AAA battery.OP-101 display the measuring results on 1.5' LED screen, and the backlight of the three models are red, white and green respectively. And the screen of OP-102 and OP-103 are 0.96' OLED and 1.3' OLED. Additionally, battery indicator and pulse waveform can be displayed on OP-102 and OP-103. The subjected device is indicated for continuous or spot check monitoring of functional arterial oxygen saturation (SpO2) and pulse rate of adult patients in hospitals and clinics.

This document describes the validation of a Pulse Oximeter device (models OP-101 and OP-102).

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are primarily derived from the ISO 80601-2-61:2017 standard for pulse oximeters, particularly for SpO2 accuracy.

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

• Test Set (Clinical Data): 12 adult volunteers were used to validate the accuracy of the finger pulse oximeter (Model: OP-101).
  • Data Provenance: The clinical study was conducted outside of the United States. It was a prospective, randomized clinical study.

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

The document does not specify the number or qualifications of experts directly involved in establishing the ground truth measurements. However, the ground truth was established by measuring SaO2 with a blood gas analyzer, which is a standard method that implicitly relies on trained medical professionals to operate and interpret.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for the test set in the sense of expert review of discrepancies. The accuracy validation appears to be a direct comparison between the device's SpO2 readings and the SaO2 measurements from the blood gas analyzer.

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

No multi-reader multi-case (MRMC) comparative effectiveness study was done or reported in this document. This type of study is more common for diagnostic imaging devices where human interpretation is a key component. For a pulse oximeter, the primary comparison is between the device's output and a gold standard physiological measurement.

6. Standalone Performance Study

Yes, a standalone performance study was done. The clinical study described involved evaluating the algorithm's performance (SpO2 and pulse rate measurements) against a recognized gold standard (blood gas analyzer) without human input / assistance in the measurement itself (beyond initial placement of the device and blood sample collection).

7. Type of Ground Truth Used

The ground truth for the clinical accuracy validation was arterial oxygen saturation (SaO2) measured by a blood gas analyzer. This is considered a gold standard for oxygen saturation in medical contexts.

8. Sample Size for the Training Set

The document does not explicitly mention a separate "training set" or its sample size. For medical devices like pulse oximeters, the development typically involves calibration data, and potentially internal validation data, but the focus of regulatory submissions is often on the performance demonstration of the final device (test set). Given the nature of a hardware-based measurement device, "training set" in the machine learning sense is less applicable here unless specific algorithms for signal processing or artifact rejection were developed with a dedicated training phase, which is not detailed.

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

As no specific "training set" is described for this device in the provided document, the method for establishing its ground truth is not detailed.

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The infrared thermometer is intended for the measurement and monitoring of human body temperature by doctors or customers in the hospital or at home.

EFT-16 series (Model: EFT-161, EFT-162, EFT-164, EFT-165, EFT-166) measure the body temperature through receiving the infrared energy radiation from the surface of objects. It is with forehead temperature mode, and ear temperature mode, directly show on the LCD screen. The device is widely used for home healthcare, medical institutes and many other occasions. The product is mainly composed with infrared temperature sensors, signal receiving processor, buttons, buzzer, LCD display, battery, etc. It focuses the infrared from the human's forehead or ear by the Fresnel lens.

The provided documentation describes the acceptance criteria and the study conducted for the Shenzhen Brav Electronic Technologies Co., Ltd. Infrared Thermometer models EFT-162, EFT-163, EFT-164, EFT-165, EFT-166.

1. Table of Acceptance Criteria and Reported Device Performance

Note on Accuracy: The proposed device actually reports a tighter accuracy range (±0.2°C across the entire measurement range) compared to the predicate device which had a wider tolerance (±0.3°C) at the extreme ends of its measurement range. This is presented as meeting the requirements of international standards ISO 80601-2-56:2019 and ASTM E 1965-98.

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

• Sample Size: The document does not explicitly state the sample size used for the clinical test set. It only mentions "Clinical testing is conducted per ASTM E 1965-98". ASTM E 1965-98 specifies requirements for clinical accuracy but does not dictate a fixed sample size. Typically, clinical studies for thermometers involve a certain number of subjects to demonstrate accuracy against a reference.
• Data Provenance: Not explicitly stated. The manufacturer is based in Shenzhen, China. The document does not specify if the clinical testing was conducted in China or another country, nor if it was retrospective or prospective. Given the device's intended use in both hospital and home settings, it would likely be prospective.

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

• The document does not mention the number of experts or their qualifications for establishing ground truth in the clinical testing. For a thermometer, ground truth is typically established by comparative measurements against a highly accurate reference thermometer (e.g., a laboratory standard thermometer or a rectal/oral mercury thermometer in a clinical setting) using established protocols, not expert consensus in the same way an imaging AI algorithm might be evaluated.

4. Adjudication Method for the Test Set

• The document does not mention any adjudication method for the clinical test set. Given the nature of a thermometer's performance evaluation (direct measurement comparison), an adjudication method in the context of multiple human readers/reviewers is generally not applicable.

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

• No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically performed for diagnostic imaging algorithms where human readers interpret images with and without AI assistance. This is not relevant for a clinical electronic thermometer.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, the performance evaluation for the Infrared Thermometer is inherently a standalone performance evaluation. The device itself performs the temperature measurement and displays the result. There is no "human-in-the-loop" component for its core function of temperature determination that would require a separate study to evaluate. The "clinical data" section describes testing the device's accuracy in measuring patient temperature.

7. Type of Ground Truth Used

• The ground truth for the clinical accuracy evaluation would be established by comparison against a reference standard in a clinical setting. ASTM E 1965-98 typically requires comparison of the device's readings with core body temperature measurements obtained using a validated, highly accurate reference thermometer (e.g., a standard mercury-in-glass thermometer or a highly accurate electronic reference thermometer) in a controlled environment, often involving simultaneous measurements. The document states "Clinical testing is conducted per ASTM E 1965-98 Standard Specification For Infrared Thermometers For Intermittent Determination Of Patient Temperature," which implies this method of ground truth establishment.

8. Sample Size for the Training Set

• The document does not provide information on a training set sample size. Infrared thermometers are typically calibrated and validated through engineering and clinical performance testing, not through machine learning model training in the same way an AI algorithm would be. While there might be firmware or algorithms for signal processing, the document does not describe a machine learning-based approach requiring a "training set" in the conventional sense.

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

• As there is no mention of a "training set" in the AI/machine learning sense, there is no information on how ground truth for such a set was established. Device calibration and internal processing logic are developed based on physics principles, sensor specifications, and empirical validation against known temperature references.

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