Search Results

The HeTaiDa electronic thermometers HTD8818A, HTD8808C are infrared thermometers which use infrared sensor to detect human body temperature of all ages. It is intended to be used on one's forehead to detect body temperature. The HTD8816C, HTD8816C, HTD8808C are intended for use in home and clinical environment.

The HeTaiDa infrared body thermometer, Models HTD8818A,HTD8816C,HTD8808C are hand-held device powered by batteries and designed to measure human body temperature without contacting patient's forehead. The thermometer can switch modes between "Body Mode" and "Surface Mode". The "Surface Mode" is DIRECT MODE and the "Body Mode" is ADJUSTED MODE. Forehead temperature of the ADJUSTED MODE is calculated by converting the measured temperature of the DIRECT MODE to an axillary equivalent temperature without contacting the patients' forehead.

The provided text describes the acceptance criteria and the studies conducted to prove that the "Non-contact Infrared Body Thermometer" (Models HTD8808C, HTD8818A, HTD8816C) meets these criteria.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

The document refers to a clinical accuracy test (referenced as "Appendix 11" and compliant with ASTM E1965-98) for evaluating operating environment and measurement range changes.

• Sample Size: The document indicates that clinical bias was calculated for three groups:

  • Group I (Infants)
  • Group II (Children)
  • Group III (Adults)
    However, the specific number of subjects within each group or the total sample size for the clinical test is not explicitly stated in the provided text.

• Data Provenance: The document does not explicitly state the country of origin of the data or whether the study was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document provides very limited information regarding the clinical study, particularly concerning the establishment of ground truth. It states that "the bias of the test thermometer is non-inferior to the bias of the predicate thermometer when compared to the reference thermometer." This implies a comparison to a "reference thermometer," which would typically be a highly accurate, calibrated device used to establish true body temperature.

• Number of Experts: Not mentioned.
• Qualifications of Experts: Not mentioned.

4. Adjudication method for the test set

The document does not describe any adjudication method (like 2+1 or 3+1). The evaluation of clinical accuracy seems to be based on direct comparison to a "reference thermometer" and statistical analysis of bias and repeatability.

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 device is a non-contact infrared body thermometer, not an AI-assisted diagnostic tool involving "human readers" or "cases" in the typical sense of medical imaging or clinical decision support systems. Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers is not applicable to this device and was not performed.

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

The device itself is a standalone thermometer. The "standalone" performance is assessed by various bench tests (IEC 60601-1, IEC 60601-1-11, IEC 60601-1-2, ISO 80601-2-56) and a clinical accuracy test comparing its readings directly to a reference thermometer. These tests evaluate the device's accuracy and functionality without human intervention outside of operating the device for measurement.

7. The type of ground truth used

The ground truth for the clinical accuracy tests appears to be established by comparison to a "reference thermometer." This indicates a highly accurate, calibrated device used to obtain the true body temperature against which the performance of the non-contact infrared thermometer is measured.

8. The sample size for the training set

The document primarily focuses on substantiation of modifications and performance testing, not on the development of the core algorithm. It does not provide information on a "training set" in the context of machine learning, as this is an infrared thermometer and not a learning-based algorithm. The device's "algorithm" likely refers to its internal logic for converting infrared readings to a displayed temperature, which would be developed through engineering and calibration, not a machine learning training set.

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

As there is no mention of a traditional "training set" for a machine learning algorithm, this question is not directly applicable. The device's calibration and accuracy are established through laboratory and clinical testing against reference standards and methods, as detailed under points 1, 2, and 7.

Ask a specific question about this device

The device is intended to be used for measuring, storing, and to generate prompts for, multiple physiological parameters of adults and pediatrics. The device is intended for use by trained healthcare professionals in hospital environments.

Parameters include: NIBP, SpO2, PR (pulse rate), TEMP.

The F3000 Quick TEMP module is not intended for neonates.

The device is not intended for MRI environments.

The iM3s series vital signs monitors including iM3s\iM3As\iM3Bs\ iHM3s are intended to be used for measuring, storing, reviewing of, and generating prompts for multiple physiological parameters of adults, pediatrics and neonates.

Here's an analysis of the provided text regarding the acceptance criteria and study data for the Vital Signs Monitor (iM3s, iM3As, iM3Bs, iHM3s).

Please note: The provided document is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It primarily presents performance specifications and shows that the new device meets those, often by referencing existing standards or previous clearances. It does not typically include detailed experimental setups for clinical or performance studies in the way a research paper would. Therefore, some information requested (like sample size for training sets, specific adjudication methods, MRMC studies, or detailed ground truth establishment for training data) is not present in this type of regulatory document.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally implied by the predicate device's specifications and compliance with relevant ISO/IEC standards. The "Reported Device Performance" for the subject device is stated as meeting these same specifications.

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

• Sample Size for Test Set: Not specified in the document. The performance is validated through "functional and system level testing" and compliance with standards, not a clinical trial with a specified patient sample size for device comparison.
• Data Provenance: The studies are described as "non-clinical data" and "bench testing." No country of origin is mentioned for patient data, as no clinical studies with human subjects are detailed. The nature of the testing implies it's retrospective, based on existing standards and validation procedures, rather than prospective clinical data.

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

• This information is not provided in the document. The "ground truth" for these performance tests would typically be established by highly calibrated reference instruments or simulated physiological signals according to the requirements of the cited ISO/IEC standards, rather than expert human interpretation in a clinical context.

4. Adjudication Method for the Test Set

• This information is not applicable and not provided. As no clinical studies with human subjects or interpretation tasks are described, there is no need for an adjudication method. The assessment is against technical specifications and standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, an MRMC comparative effectiveness study was not done. The document explicitly states "Clinical data: Not applicable." The focus is on the device's standalone performance against engineering and international standards.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, the performance reported is essentially standalone. The "bench testing" and "software verification and validation testing" assess the device's accuracy and functionality in isolation, without an explicit human-in-the-loop component for interpreting outputs in the context of the device's core physiological measurements (NIBP, SpO2, PR, TEMP).

7. The Type of Ground Truth Used

• The ground truth for the performance testing is based on:
  • Reference measurements from calibrated equipment: For parameters like SpO2, NIBP, and TEMP, the "ground truth" would be simulated physiological signals or measurements from highly accurate, traceable reference devices as mandated by the respective ISO/IEC standards.
  • Compliance with international standards: The device is tested against the specific requirements and accuracy tolerances defined in standards such as IEC 80601-2-30 (NIBP), ISO 80601-2-56 (thermometers), and ISO 80601-2-61 (pulse oximeters).

8. The Sample Size for the Training Set

• This information is not provided and is not applicable in the context of this device and document. This device is a vital signs monitor, not typically an AI/machine learning diagnostic device that relies on "training sets" in the conventional sense of machine learning algorithms. Its parameters are measured directly through hardware and firmware, validated against physical standards.

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

• This information is not provided and is not applicable as there is no "training set" for an AI algorithm described for this device. The device's fundamental operational principles are based on established physiological measurement techniques, not on learning from a dataset.

Ask a specific question about this device