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510(k) Data Aggregation
(420 days)
The Non-contact Infrared Thermometer (Models WL-301, WL-501, WL-601, WL-701) is an electronic thermometer using an infrared sensor to detect human body temperature from forehead on people of one month old and above. The device is reusable for home and clinical use.
The Infrared thermometers are hand-held, battery powered devices designed to measure human body temperature from the central forehead. Its operation is based on measuring the natural thermal radiation from central forehead.
The thermometers use a thermopile sensor with integrated thermistor for the target reading, a thermistor mounted in the head of the thermometer for ambient temperature readings, a parabolic mirror to help focus the infrared energy emitted from the forehead, and an infrared distance sensor for detection of no-contact use and compensation of the temperature reading.
The device mainly consists of infrared sensor, microprocessor, embedded software (Identified Software version is No: V1), memory, electro-acoustic components, LED display and the device is powered by 2AAA alkaline batteries.
The non-contact infrared thermometer included WL-301, WL-501, WL-601, WL-701. They can be selected calibration mode, body temperature mode and surface mode.
Here's a breakdown of the acceptance criteria and study information for the Non-contact Infrared Thermometer (Models WL-301, WL-501, WL-601, WL-701), based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (Predicate) | Reported Device Performance (Subject Device) | Notes/Differences |
|---|---|---|
| Measurement Range: 34°C ~ 43°C | Measurement Range: 34°C ~ 42°C | Different, but stated to meet ISO 80601-2-56:2017/Amd.1:2018 |
| Accuracy: | Accuracy: | |
| ±0.2°C: 35.0°C ~ 42.0°C | ±0.3°C: 34°C~42°C | Different, but stated to meet ISO80601-2-56 and demonstrated through clinical trial |
| ±0.3°C: 34.0°C ~ 34.9°C, 42.1°C ~ 43°C | ||
| Response time: 1S | Response time: <6S | Different, but software validated and performance testing meets ISO 80601-2-56 and ASTM E1965-98. |
| Buzzer: Yes | Buzzer: No, vibrate instead | Different, but considered not to affect safety/effectiveness. |
| Display screen: LCD | Display screen: LED | Different, but considered not to affect safety/effectiveness. |
| Memory: 60 sets | Memory: 1 set | Different, but considered not to affect safety/effectiveness. |
| Operation Environment: 10~40°C, 15-85% RH | Operation Environment: 15~40°C, RH ≤ 95% | Slightly different, but demonstrated to comply with IEC 60601-1 and ISO 80601-2-56. |
| Storage Environment: -20~+55°C, RH≤90% | Storage Environment: -20°C ~+55°C, RH≤95% | Slightly different, but demonstrated to comply with IEC 60601-1 and ISO 80601-2-56. |
| Conformance Standard: ISO80601-2-56 (performance) | Conformance Standard: ISO80601-2-56 (performance), with some clause exceptions evaluated in other reports. | Differences noted, but overall compliance asserted. |
| Biocompatibility: ISO 10993-1, ISO 10993-5, ISO 10993-10 | Biocompatibility: Meets ISO 10993-5 and ISO10993-10. Also mentions ISO 10993-1 conformance. | Appears to meet or exceed. |
| Cleaning Method Effectiveness: Not explicitly stated as acceptance criterion, but part of predicate's general compliance. | Cleaning Method Effectiveness: Meets AAMI TIR30:2011. | Demonstrated. |
| Shelf-life: Not explicitly stated as acceptance criterion. | Shelf-life: 2 years. | Demonstrated. |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: 150 patients
- Data Provenance: Not explicitly stated, but implies a prospective clinical trial conducted for the purpose of validating the device. The text does not specify the country of origin of the data.
3. Number of Experts Used to Establish Ground Truth and Qualifications:
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified. The ground truth was established using a "Reference clinical thermometer: a Glass thermometer, Model: CRW-23, Yuwell-Jiangsu medical equipment & supply Co." It's implied that a medical professional would use this reference thermometer to obtain the ground truth readings, but no specific expert qualifications are given.
4. Adjudication Method for the Test Set:
- Adjudication Method: Not specified. The process simply states that the clinical trial was performed and compared to a reference thermometer.
5. Multi-reader Multi-case (MRMC) Comparative Effectiveness Study:
- MRMC Study: No. This device is a standalone thermometer, not an AI-assisted diagnostic tool that would involve human readers. Therefore, an MRMC study and effect size of AI assistance on human readers are not applicable.
6. Standalone Performance Study:
- Standalone Performance Study: Yes. The clinical trial directly assessed the performance of the device (algorithm only, as it's an infrared thermometer with embedded software) against a reference clinical thermometer. The performance testing and clinical trials mentioned ("Measurement Range & Accuracy", "Measurement distance", "Response time") are all standalone evaluations of the device.
7. Type of Ground Truth Used:
- Type of Ground Truth: Reference clinical thermometer (Glass thermometer, Model: CRW-23, Yuwell-Jiangsu medical equipment & supply Co.). This is considered a clinical reference standard.
8. Sample Size for the Training Set:
- Sample Size for Training Set: Not applicable. This device is a non-contact infrared thermometer. While it contains embedded software (Software version V1), there is no mention of a "training set" in the context of machine learning or AI models. Its functionality is based on established infrared measurement principles and calibration, not a learned model from a dataset.
9. How the Ground Truth for the Training Set Was Established:
- How Ground Truth for Training Set Was Established: Not applicable, as there is no mention of a training set for machine learning. The device's accuracy would have been calibrated and verified during manufacturing and development processes against known thermal standards, but this is distinct from "ground truth for a training set" in the context of AI/ML.
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