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Valeo VT-601 Series IR Thermometer, (Model no.: VT-601D, VT-601E, VT-601F) is infrared thermometer intended for the intermittent measurement of human body temperature in people of all ages.

The Valeo VT-601 Series IR Thermometer, (Model no.: VT-601D, VT-601E . VT-601F) is hand-held, non-sterile, reusable, battery operated device that can measure human body temperature. The Valeo VT-601D IR Forehead/ Ear Thermometer can measure human body temperature in 2 ways: (1) The temporal artery over forehead. (2) Tympanic temperature via the human ear. The Valeo VT-601E IR Ear Thermometer measures human body temperature natural thermal infrared radiation emitted from the ear tympanic. The Valeo VT-601F IR Forehead Thermometer measure human body temperature by the temporal artery over forehead. Operation is based on the measuring of the natural thermal infrared radiation emitted from the surface of the skin over the temporal artery or from the ear tympanic.

Here's a breakdown of the acceptance criteria and study information for the Valeo VT-601 Series IR Thermometer, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified directly in the provided text. The document mentions "A Clinical Test Report conducted according to ASTM E 1965: 1998 (2009)" but does not detail the number of subjects or measurements.
• Data Provenance: The study was "performed by the manufacturer." The country of origin is not explicitly stated for the study data itself, but the manufacturer (VALEO Corporation) is based in Taipei, Taiwan. The study is retrospective in terms of being a report of past activity, but the study itself (the clinical test) would have been prospective to gather the data.

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

This information is not provided in the text. As this is a medical device for measuring temperature, the "ground truth" would likely be established by a reference thermometer or highly accurate clinical measurement standards, rather than expert judgment in the human-reader sense.

4. Adjudication Method for the Test Set:

This information is not applicable and therefore not provided. Temperature measurements are typically compared directly to a "gold standard" reference, without the need for human adjudication between multiple readers of the device's output.

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:

This is not applicable. The device is an infrared thermometer, not an AI-powered diagnostic imaging tool that assists human readers.

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

The device is a standalone algorithm/device. Its performance is evaluated on its own ability to measure temperature. The accuracy criteria listed above define its standalone performance.

7. The Type of Ground Truth Used:

The ground truth used for assessing accuracy was based on the "method recommended in ASTM E1965 standard." This standard specifies methods for determining the accuracy of clinical thermometers, which typically involves comparing the device's readings against a reference thermometer (a highly accurate and calibrated device) in a controlled environment, and/or against a subject's core body temperature measured by an invasive "gold standard" method in clinical trials. Therefore, the ground truth is derived from a standardized clinical measurement method.

8. The Sample Size for the Training Set:

This information is not applicable and therefore not provided. The Valeo VT-601 Series IR Thermometer is a physical device based on infrared sensing technology, not a machine learning model that requires a training set.

9. How the Ground Truth for the Training Set was Established:

This information is not applicable and therefore not provided. As stated above, the device does not use a "training set" in the context of machine learning. The device's design and calibration would be based on engineering principles and physical laws of infrared radiation, validated against established measurement standards like ASTM E1965.

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The device measures the body temperature of a patient by means of a sensor (transducer) coupled with an electronic signal amplification, conditioning and digital LCD (display) unit. The device is reusable and intended for oral, axillary or rectal temperature measurements.

Clinical Electronic Thermometer

The provided text concerns an FDA 510(k) clearance for a "Clinical Electronic Thermometer" (K982140). The documents focus on the regulatory approval process and indications for use, rather than a detailed study description of acceptance criteria and device performance. Therefore, I cannot extract the specific information requested in your prompt based on the provided text.

The text does not contain:

1. A table of acceptance criteria and reported device performance.
2. Sample size used for the test set or data provenance.
3. Number or qualifications of experts used to establish ground truth.
4. Adjudication method for the test set.
5. Information on any multi-reader multi-case (MRMC) comparative effectiveness study.
6. Details about a standalone (algorithm only) performance study.
7. The type of ground truth used.
8. The sample size for the training set.
9. How the ground truth for the training set was established.

The document is a letter from the FDA to Valeo Corporation granting 510(k) clearance for their Clinical Electronic Thermometer, indicating it is "substantially equivalent" to legally marketed predicate devices. The "Indications for Use" document specifies the purpose of the device (measures body temperature via a sensor, amplification, and digital display, reusable, intended for oral, axillary, or rectal measurements).

To provide the requested information, you would need a clinical study report or a detailed 510(k) summary that includes performance data and validation methodology for the device.

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