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The TTP™ is a non-sterile temperature monitoring system intended to measure and monitor core body temperature of patients of all ages, by applying a sensor unit on the forehead.

The TTP™ system monitors the body core temperature through continuous measurements of the patient. The system is non-sterile and comprised of a disposable Sensor Unit, attached to the patient temple, and connected to a Monitor Connecting Unit which is connected to a power supply and to any YSI-400 input vital signs monitor, through which, the patient temperature is presented. The MCU is able to present the patient temperature as a standalone unit.

The provided text describes the Medisim Temple Touch Pro™ (TTP™) – Temperature monitoring system, a clinical electronic thermometer. Here's a breakdown of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Clinical Study (Test Set): 181 subjects (95 males, 86 females) with a total of 4591 temperature samples.
• Data Provenance: The document does not explicitly state the country of origin for the clinical study data. It mentions the applicant is Medisim Ltd. based in Neve Ilan, Israel, so it's likely the study was conducted in Israel or a closely associated region. The study was conducted according to GCP standards, implying a prospective and controlled approach.

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 used to establish the ground truth for the clinical study. It states that the TTP™ measurements were compared to "various reference measurements" from "other invasive thermometers," implying that these reference measurements served as the ground truth.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method for the test set. The clinical study aimed to show "no statistically significant difference" between the TTP™ and reference thermometers, suggesting a direct comparison without an independent adjudication process for each reading.

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 as the device is a temperature monitoring system and not an AI-assisted diagnostic tool that requires human reader interpretation. No MRMC study was mentioned or performed.

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

Yes, a standalone performance evaluation was done through the clinical study. The device's accuracy and performance were assessed by comparing its measurements directly to established reference thermometers. The study did not involve human interpretation or assistance in the measurement process itself, beyond the initial application of the sensor.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The ground truth for the clinical study (test set) was based on measurements from "other invasive thermometers." These invasive thermometers are considered the gold standard for core body temperature measurement.

8. The Sample Size for the Training Set

The document does not explicitly mention a separate "training set" or its sample size. The description focuses on validation and performance testing. For a device like a thermometer, the "training" (calibration, algorithm development) would likely occur during the device development phase, and the provided clinical study serves as a final validation (test set).

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

As no specific training set is mentioned in the document, details on how its ground truth was established are not available. It's inferred that the device's measurement algorithms were developed and refined against established temperature measurement standards and reference methods during its engineering and design phases.

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The UGFT3 is a non-sterile, reusable clinical thermometer intended for the determination of human's body temperature using the temple (forehead); and/or underarm (axilla); and/or behind the ear as measurement sites.

The UGFT3 is a non-sterile, reusable clinical thermometer intended for the determination of human's body temperature using the forehead and/or underarm and/or behind the ear as measurement sites. The UGFT3 is utilizing the Rapid Accurate Temperature Establishment (R.A.T.E.TM) technology, a technology based on the heat conduction principle, for determination of body temperature. Utilizing the R.A.T.E.TM technology, the device rapidly samples the heat flowing from the blood vessels to the skin surface. Then, based on the heat flow, the device calculates the blood vessel temperature, and then corrects this value to the body core temperature. User operation of the UGFT3 is identical to the operation of the Dual Mode Up Grade Forehead/Underarm Thermometer, cleared under K051422. The device allows user control by use of buttons located on the front panel of the device and the measured body temperature is displayed on an LCD screen, in Co or Fo units. The UGFT3 has an identical hardware as the UGFT2, as it uses the same thermistor sensor and electronic processing unit, however, the UGFT3 has a modified proprietary software algorithms. Device is made of ABS plastic and silicone rubber.

The Medisim UGFT3 thermometer is a non-sterile, reusable clinical thermometer intended for the determination of human body temperature using the forehead, underarm, and/or behind-the-ear as measurement sites. The device utilizes Rapid Accurate Temperature Establishment (R.A.T.E.TM) technology, which is based on the heat conduction principle, to determine body temperature by sampling heat flowing from blood vessels to the skin surface.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The submission primarily focuses on technical accuracy according to ASTM standards and clinical validation for the new "behind the ear" measurement site.

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

• Test Set Sample Size: 239 subjects for the clinical study.
• Data Provenance: The document does not explicitly state the country of origin for the clinical study. It is implied to be prospective since it's a clinical study conducted for the validation of the new device.

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

The document does not provide details on the number of experts or their qualifications for establishing ground truth within the clinical study. The clinical study compares the UGFT3 to a predicate device (Vicks Behind Ear Thermometer), which likely serves as the reference standard. The "ground truth" seems to be generated by a legally marketed and cleared device rather than expert consensus on individual readings.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method for the test set. Given that the clinical study compares the UGFT3's readings to those of a predicate device, it's implied that the predicate device's reading acts as the reference. There's no mention of multiple readers or an adjudication process for discrepancies.

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

No, an MRMC comparative effectiveness study was not conducted. The clinical study performed was a direct comparison of the UGFT3's temperature readings to those of a predicate thermometer for the behind-the-ear site. There is no mention of evaluating how human readers' performance improves with or without AI assistance, as this is a standalone device validation, not an AI-assisted diagnostic tool.

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

The clinical study was a standalone assessment of the UGFT3's performance (algorithm and hardware). The device takes a measurement and displays a temperature. While human interaction is required to operate the thermometer, the reported "accuracy" pertains to the device's ability to measure temperature correctly, independent of a human's interpretative skill. The study directly compares the UGFT3's output to that of another thermometer, which qualifies as a standalone performance evaluation.

7. The Type of Ground Truth Used

The ground truth for the clinical study was established by comparison to a legally marketed and cleared predicate device, specifically the Vicks Behind Ear Thermometer cleared under K103839. This serves as a reference standard for clinical accuracy. Further, technical accuracy bench testing used ASTM E-1112-00 as the standard for performance.

8. The Sample Size for the Training Set

The document makes no mention of a "training set" in the context of machine learning or AI models. The UGFT3 uses "modified proprietary software algorithms" based on a heat conduction principle, but it's not described as a machine learning model that requires a labeled training set in the typical sense. The term "training set" is not applicable based on the provided information.

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

As noted above, the concept of a training set as typically understood in machine learning/AI is not explicitly addressed. The device's "modified proprietary software algorithms" are based on a physical principle (heat conduction). It's likely that these algorithms were developed and refined through engineering, physics modeling, and potentially internal calibration data, rather than a publicly disclosed, labeled "training set" with ground truth in the context of expert annotations or pathology.

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The NIR is non-sterile non-invasive infrared thermometer intended for the intermittent calculation of human body temperature of people of all ages for home and professional use.

The device is built of one or more infrared thermopile sensors that is/are designed to measure a temperature above the artery on the skin. Each of the sensor/s is mounted on a reflector which is used to reduce the sensor field of view. In order to minimize distance effects on the readouts the device is equipped with a distance measurement sensor. Each of the thermopile/s has its own thermistor which is used for calculating the self temperature of each sensor. In addition there is another external thermistor which is used for measuring the ambient temperature and to asses the thermal condition of the thermal equilibrium of the device and to correct the result according to its value and the difference between the external sensor and the internal termistors readout.

Here's a breakdown of the acceptance criteria and study information for the Medisim Ltd. NIR Electrical Thermometer, based on the provided text:

Acceptance Criteria and Reported Device Performance

Study Details

Due to the nature of this submission (510(k) for a non-invasive infrared thermometer), the study design is focused on demonstrating substantial equivalence to a predicate device and adherence to industry standards, rather than proving efficacy through a typical clinical trial comparing intervention vs. control.

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

   • Test Set Sample Size: Not explicitly stated in the provided text. The submission mentions "comparative testing with market-cleared devices," and "clinical and bench tests." However, the exact number of participants or measurements in these tests is not quantified.
   • Data Provenance: Not explicitly stated. The manufacturer is Medisim Ltd. in Israel, and the Israeli Institute of Standards was involved in safety validation. It's reasonable to infer that testing occurred in Israel, but this is not definitively stated for the clinical performance. The submission refers to "clinical and bench tests," which implies prospective data collection for the purpose of this submission.

2. 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):

   • This information is not provided in the text. For a thermometer, "ground truth" would typically refer to a highly accurate reference thermometer (e.g., a rectal thermometer or a laboratory-grade temperature measurement device), not expert consensus.

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

   • This concept of "adjudication" is not applicable to the type of device and study described. Adjudication methods like 2+1 or 3+1 are typically used in studies where subjective interpretation (e.g., of medical images) requires multiple experts to reach a consensus for ground truth. For a thermometer, objective measurements against a reference are performed.

4. 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:

   • Not applicable. The NIR Electrical Thermometer is a direct measurement device; it does not involve "human readers" or "AI assistance" in the interpretation of complex data in the way an MRMC study would apply (e.g., for diagnostic imaging). The device provides a direct temperature reading.

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

   • Yes, implicitly. The device itself is a standalone system that measures and displays temperature. The "clinical and bench tests" would have evaluated the device's accuracy in isolation, independent of human interpretation beyond recording the displayed temperature.

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

   • The ground truth would have been established using reference temperature measurements from highly accurate and calibrated thermometers, either in a controlled laboratory ("bench tests") or clinical setting. This is implied by the nature of temperature measurement device testing and the reference to ASTM E1965-98, which outlines standards for infrared thermometers, including accuracy testing against known temperatures.

7. The sample size for the training set:

   • Not applicable/Not provided. The NIR thermometer is not described as a device that uses machine learning or AI that requires a "training set" in the conventional sense. Its function is based on established physical principles of infrared thermometry. Any internal calibration or algorithm development would fall under engineering validation rather than an AI training set.

8. How the ground truth for the training set was established:

   • Not applicable. As stated above, there is no "training set" for an AI or machine learning algorithm described for this device.

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The Dual Mode Up-Grade Forehead/ Underarm Thermometer device is intended for determination of body temperature.
The Dual Mode Up-Grade Forehead/ Underarm Thermometer device is a non-sterile, reusable clinical thermometer intended for the determination of human's body temperature using the forehead and axilla as measurement sites.

The Dual Mode Up-Grade Forehead/ Underarm Thermometer is a clinical electronic thermometer used for determination of body temperature. The over-the-counter Dual Mode Up-Grade Forehead/ Underarm Thermometer is designed to calculate the maximum temperature of a probe in contact with the body site, without waiting for thermal equilibrium to occur, by heat transfer data and mathematical algorithm. The temperature reading range is from 35.0°C to 42.0°C (95.5°F to 107.6°F) and the time of measurement is 6-10 seconds.

The provided text does not contain enough information to fully describe the acceptance criteria and the study that proves the device meets them as per your requested format.

Here's why and what information is missing:

• Acceptance Criteria Detail: The document states "The technological characteristics, e.g., overall design, materials, mechanism of action, mode of operation, performance characteristics, etc., and the intended use of the Dual Mode Up-Grade Forehead/ Underarm Thermometer device are substantially equivalent to the predicate devices cited above." This is a general statement of substantial equivalence, not a list of specific performance acceptance criteria (e.g., accuracy +/- X degrees Celsius, precision Y degrees Celsius). While it implies the device must perform similarly to the predicates, it doesn't quantify "performance characteristics."
• Study Details: There is no description of a specific study conducted to demonstrate that the device meets any performance criteria. It mentions "heat transfer data and mathematical algorithm" but doesn't elaborate on any study validating this.

Therefore, I cannot populate the table or answer most of the questions.

Information I can extract/infer from the provided text:

• Device Name: Dual Mode Up-Grade Forehead/ Underarm Thermometer
• Intended Use: Determination of body temperature, non-sterile, reusable clinical thermometer, using forehead and axilla as measurement sites.
• Temperature Reading Range: 35.0°C to 42.0°C (95.5°F to 107.6°F)
• Time of Measurement: 6-10 seconds
• Ground Truth Type (Inferred): For a thermometer, the ground truth would typically be established by a highly accurate reference thermometer or a precise temperature measurement standard. However, the document does not explicitly state how accuracy was verified or what "ground truth" was used in any testing.

Missing Information (and why it's missing from this type of document):

This document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It typically summarizes findings and often refers to internal company documentation or recognized standards for the detailed study results. The specific performance testing and its criteria, methodology, and results are usually found in the full 510(k) submission, not the publicly available summary.

Therefore, I cannot complete the table or answer most of the questions you've posed based on the provided text.

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The UP-GRADE FOREHEAD THERMOMETER is a non-sterile, reusable clinical thermometer intended for the determination of human's body temperature using the forehead as measurement site.

The over-the-counter Up-Grade Forehead Thermometer is a compact predictive clinical thermometer designed to measure human body temperature by detecting heat flow from the temporal artery, by using the heat conduction principle and prediction. The over-the-counter Up-Grade Forehead Thermometer is designed to calculate the maximum temperature of a probe in contact with the body site. without waiting for thermal equilibrium to occur, by heat transfer data and mathematical algorithm. The temperature reading range is from 35.0ºC to 42.0°C (95.5°F to 107.6°F) and the time of measurement is 6-10 seconds.

Here's a breakdown of the acceptance criteria and study information for the UP-GRADE FOREHEAD THERMOMETER based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document refers to compliance with voluntary standards, but does not explicitly state the specific acceptance criteria or provide a table of performance metrics. However, it does state that the device's acceptable performance was established through comparative testing with market-cleared devices and compliance with the following standards:

Note: The specific performance metrics (e.g., accuracy, repeatability) that would typically be detailed within compliance to ASTM E1112 are not explicitly listed in the summary. The summary only states that performance was "established" through testing and standard compliance.

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

The document does not specify the sample size used for the clinical or non-clinical test set. It mentions "comparative testing with market-cleared devices," implying a clinical validation, but provides no details on the number of subjects or the nature of the data (prospective/retrospective or country of origin).

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

This information is not provided in the 510(k) summary.

4. Adjudication Method for the Test Set

This information is not provided in the 510(k) summary.

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

No MRMC study is mentioned in the 510(k) summary. The device is a standalone thermometer, not an AI-assisted diagnostic tool for human readers.

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

Yes, a standalone performance assessment was effectively done. The device itself is an "algorithm only" in the sense that it uses a "mathematical algorithm" to calculate maximum temperature. The non-clinical and clinical tests performed were to establish the safe and effective performance of this device in a standalone manner, without human interpretation of its output beyond reading the displayed temperature.

7. The Type of Ground Truth Used

The document doesn't explicitly state the "ground truth" method. However, for clinical thermometers, the standard practice for establishing accuracy typically involves comparison against a reference thermometer (e.g., a rectal thermometer) considered the gold standard for core body temperature measurement in a clinical setting. Given the mention of "comparative testing with market-cleared devices" and compliance with ASTM E1112 (which defines accuracy requirements for electronic thermometers), it's highly probable that the ground truth was established by comparing the device's readings to those of a validated reference thermometer.

8. The Sample Size for the Training Set

The document does not specify any training set size. As a non-AI or machine learning-driven device in the modern sense, it likely does not have a "training set" in the way an image recognition algorithm would. Its "mathematical algorithm" for prediction would have been developed and validated, but not "trained" on a specific dataset in the typical AI/ML context.

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

As no "training set" in the AI/ML context is implied or mentioned, the method for establishing its ground truth is not applicable or provided. The "mathematical algorithm" would have been designed based on heat transfer principles and validated against actual temperature measurements.

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The M5T is non-sterile, reusable clinical thermometer intended for the determination of oral, rectal and axillary body temperature determination in humans.

The M5T is a compact predictive clinical thermometer designed to measure human body temperature by detecting heat from three different body sites: axilla, rectum and mouth, by using the heat conduction principle and prediction.

The M5T is designed to calculate the maximum temperature of a probe in contact with the body site. The temperature reading range is from 35.0℃ to 42.0℃ (95.5°F to 107.6°F) and the time of measurement varies between 8 to 10 seconds.

The LCD, push button, battery, microprocessor and the PCB are located in one housing, which includes upper cover, lower cover and the battery cover. The entire device is compact, lightweight, small in size, easy to use and portable,

Here's an analysis of the provided text regarding the M5T Instant Fever Thermometer, focusing on acceptance criteria and study details:

The provided document is a 510(k) summary, which largely focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed acceptance criteria and a comprehensive study report with specific performance metrics and statistical analyses. Therefore, much of the requested information regarding detailed acceptance criteria, specific performance numbers, multi-reader studies, and training set details is not present in this document.

Acceptance Criteria and Reported Device Performance

The document states: "A clinical study was performed in order to evaluate the safety and performance of the M5T following the heater removal. The study results demonstrated that the M5T is safe and effective without raising new safety and/or effectiveness issues."

This is a very high-level statement and does not provide specific quantitative acceptance criteria or detailed performance metrics. The implicit acceptance criterion is that the device is "safe and effective" and comparable to the predicate device. Without further details, we cannot create a table with specific numerical acceptance criteria and reported performance values.

However, based on the general context of clinical thermometers, typical acceptance criteria would involve accuracy (e.g., within a certain deviation from a reference standard) and precision. The document doesn't provide these specific values for the M5T or its predicate.

Study Details

Given the limited information in a 510(k) summary, much of the requested detail is not available.

Additional Notes:

• Device Type: The M5T is an electronic clinical thermometer. The "prediction" mentioned ("using the heat conduction principle and prediction") likely refers to an internal algorithm that extrapolates the final stable temperature from a short measurement period, rather than a complex AI model requiring extensive training with labeled data.
• 510(k) Context: This document is a 510(k) premarket notification. Its primary goal is to show "substantial equivalence" to a currently marketed device, not to provide an exhaustive clinical trial report with all statistical details and raw data. The level of detail often found in publications for novel AI algorithms is typically not present in these regulatory submissions for established device types.
• Missing Information: The lack of specific numerical data for clinical performance (e.g., accuracy, bias, precision against a reference standard in degrees Celsius/Fahrenheit) means we cannot fully assess the device's adherence to typical thermometer performance expectations. A more detailed clinical study report would contain such data.

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The Up-Grade is an over-the-counter, non-sterile, reusable clinical thermometer intended for the determination of oral, rectal and axillary body temperature determination in humans.

The Up-Grade is a compact predictive clinical thermometer designed to measure human body temperature by detecting heat from three different body sites: axilla, rectum and mouth, by using the heat conduction principle and prediction. The device is designed to calculate the maximum temperature of probe tip in contact with the body site, without waiting for thermal equilibrium to occur, by heat transfer data and mathematical algorithm. The temperature reading range is from 35.5℃ to 42.0℃ (95.5℃ to 107.6℃F) and the time of measurement varies between 4 to 6 seconds.

The provided 510(k) summary for the Medisim Ltd. Up-Grade Electrical Thermometer does not contain specific acceptance criteria, detailed study results, or the other requested information regarding sample sizes, expert qualifications, and ground truth establishment in the level of detail typically associated with medical device studies.

However, based on the limited information provided, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) states that the device conforms to "acceptable voluntary standards" and that "safety and efficacy performance of the device has been non-clinically and clinically established through comparative testing with market-cleared devices." It also explicitly mentions compliance with ASTM E1112 and IEC 601-1. These voluntary standards would contain the specific acceptance criteria for accuracy and performance of an electronic thermometer.

Without the actual standards document or a detailed study report, the precise numerical acceptance criteria are not available in this 510(k) submission. However, assuming compliance with these standards, the reported device performance implicitly meets those criteria.

2. Sample Size and Data Provenance

• Test Set Sample Size: Not specified in the provided text.
• Data Provenance: Not specified. It's unclear if the data was collected in Israel (where the applicant is located) or elsewhere, nor if it was prospective or retrospective.

3. Number of Experts and Qualifications

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

4. Adjudication Method

• Adjudication Method: Not specified.

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

• MRMC Study: Not applicable for this device. A clinical thermometer measures a direct physiological parameter and does not involve human readers interpreting complex images or data in a diagnostic context that would typically necessitate an MRMC study. Its performance is evaluated against reference standards or predicate devices.

6. Standalone Performance Study

• Standalone Performance Study: Yes, implicitly. The statement "The Up-Grade Electrical Thermometer conforms with the following voluntary standards: ASTM E1112 and IEC 601-1" and "safety and efficacy performance of the device has been non-clinically and clinically established through comparative testing with market-cleared devices" indicates that the device's performance was evaluated on its own merits against established standards and other similar devices. The comparison "with market-cleared devices" serves as the clinical data point for substantial equivalence.

7. Type of Ground Truth Used

• Ground Truth: For a clinical thermometer, the "ground truth" would typically be established by highly accurate reference thermometers (e.g., traceable to national standards) or by the performance of the predicate devices themselves in comparative studies. The focus would be on accuracy, precision, and response time.

8. Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a predictive clinical thermometer, using a "mathematical algorithm" to predict temperature. The development of such an algorithm would involve data for calibration and optimization, which could be considered an internal "training set." However, the 510(k) does not provide details on the size or nature of this data. The submission focuses on the validation against standards and predicate devices.

9. How Ground Truth for the Training Set Was Established

• Ground Truth for Training Set: Not specified. For a predictive thermometer, the "ground truth" for developing its algorithm would be actual body temperatures measured with a highly accurate, often slower, reference thermometer over a wide range of conditions and body sites, against which the predictive model is trained to correlate its rapid measurements.

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