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Wearable Digital Thermometer is a battery-operated electronic device with intended use of measuring and monitoring human armpit temperature continuously via wireless signal transmission of the measuring result. Wearable Digital Thermometer is reusable and intended for armpit temperature monitoring for persons of all age. The temperature data of device is not intended to replace the advice, diagnosis, nor treatment recommendations of doctor. Wearable Digital Thermometer can be used at home and healthcare center.

The Wearable Digital Thermometer consists of a host, App software and stickers. A comprehensive Android and iOS App are provided to access the host from a smart device. It is used for measuring and monitoring armpit temperature in real-time continuously and remotely via Bluetooth to smart device. The medical double-sided sticker are used to fix and stick the host in the user`s axilla. The NTC temperature sensor is located closely to the stainless steel sheet that make sure the accuracy of temperature data measured. The subject device could measure and monitor temperature in real-time continuously and remotely via Bluetooth to smart phone. The Temp Pal is the combination device of thermometer and Bluetooth communication unit intended to be worn at axilla to monitor the armpit temperature continuously. The subject device is a direct mode clinical thermometer where the output temperature is not adjusted. For the monitoring operation, switch the thermometer on and stick the thermometer in the user's axilla. The thermometer will make a Bluetooth connection between the thermometer and the receiver automatically (User should setup Bluetooth properly on receiver). Then the thermometer starts to measure the body temperature. The wireless thermometer uses a rechargeable battery for operation. When the battery is low, internal circuit will detect the low battery condition automatically and send "low battery" signal through Bluetooth communication unit to receiver.

The provided document is a 510(k) summary for the Wearable Digital Thermometer (T31). While it lists performance data and standards met, it does not contain a detailed study report with specific acceptance criteria beyond general accuracy requirements, nor does it provide sample sizes, ground truth establishment methods for a test set, or information about expert involvement typically found in clinical validation studies for AI/ML devices.

The document refers to the device as a "Clinical Electronic Thermometer" and a "Wearable Digital Thermometer." It doesn't describe an AI or Machine Learning component. The "Performance Data" section primarily focuses on engineering and regulatory compliance testing rather than clinical study results that would typically be detailed for an AI/ML product.

Here's a breakdown of the information that can be extracted, and what is missing:

1. Table of acceptance criteria and the reported device performance:

Study Details:

Since the device is a "Wearable Digital Thermometer" and not an AI/ML-driven diagnostic or prognostic tool, the "study" described is a series of engineering and regulatory compliance tests rather than a clinical trial in the traditional sense for AI/ML validation.

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

• Sample size for accuracy testing: Not specified. The document only states that "Performance test" was conducted and "meet the specification of the product and the relevant standards." It doesn't explicitly mention the number of subjects or measurements for clinical accuracy validation.
• Data provenance: Not specified if a specific clinical test set was used, beyond the general standards compliance.

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

• Not applicable / Not specified. For a digital thermometer, ground truth is typically established by comparing the device's readings against a highly accurate reference thermometer, rather than expert consensus on images or clinical assessments. The specific methodology for this comparison (e.g., how many reference measurements were taken) is not detailed.

4. Adjudication method for the test set:

• Not applicable / Not specified. Adjudication methods like 2+1 or 3+1 are relevant for interpreting subjective data (e.g., radiology images) where experts might disagree. For a quantitative measurement like temperature, the ground truth is typically a direct measurement from a calibrated reference.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No. An MRMC study is relevant for AI systems that assist human readers in interpreting complex data (e.g., medical images). This document describes a digital thermometer, not an AI-assisted diagnostic tool.

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

• Yes, in essence. The performance tests described (accuracy, electrical safety, EMC, biocompatibility, shelf life, usability) are evaluating the device's inherent function, without human interpretation as part of its core measurement capability. The "algorithm" here is the device's internal temperature measurement and display mechanism.

7. The type of ground truth used:

• Reference standard/calibration: For accuracy testing, the ground truth would be established by comparing the device's temperature readings against a certified reference thermometer or a temperature standard, as outlined in standards like ISO 80601-2-56 and ASTM E1112. The specific details beyond "met the requirement" are not provided.

8. The sample size for the training set:

• Not applicable / Not specified. This device, as described, is a traditional electronic thermometer. It does not appear to utilize machine learning or need a "training set" in the context of AI/ML. Its function is based on fixed physical principles (NTC resistor).

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

• Not applicable. As a non-AI/ML device, there is no "training set" for an algorithm.

In summary: The provided document is a regulatory submission for a conventional medical device (a digital thermometer), not an AI/ML-powered one. Therefore, many of the questions asking for specifics related to AI/ML study design (like training/test sets, expert adjudication, MRMC studies) are not applicable or not detailed in this type of submission. The performance data focuses on demonstrating compliance with relevant electrical, safety, biocompatibility, and measurement accuracy standards for clinical thermometers.

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The digital thermometer is intended for the measurement and monitoring of human body temperature through or axillary as the measurement site on people of all ages by doctor or user in the hospital or home.

Digital Thermometer, Model T28, T28L

The provided document is an FDA 510(k) clearance letter for a Digital Thermometer, Model T28, T28L. This device is a standard medical instrument for measuring body temperature and does not involve AI or complex algorithms requiring extensive studies as described in the prompt's request.

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment, which are typical for AI/ML-driven medical devices, are not applicable to this specific product.

Here's a breakdown based on the characteristics of the device and the provided document:

1. A table of acceptance criteria and the reported device performance

• Not applicable in the context of AI/ML performance. For a digital thermometer, acceptance criteria would typically involve accuracy, precision, response time, and environmental operating limits, as defined by international standards (e.g., ISO 80601-2-56 for clinical thermometers). These technical performance specifications are usually provided in the device's design and testing documentation submitted to the FDA, but they are not detailed in this clearance letter. The letter confirms substantial equivalence, implying these technical specifications meet regulatory requirements.

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

• Not applicable for AI/ML performance. For a digital thermometer, testing would involve physical measurements on a range of test subjects or using calibrated thermal sources, not a "test set" of data in the AI sense. The document does not provide details on the sample sizes for these physical performance tests or their provenance.

3. 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)

• Not applicable. "Ground truth" in the context of expert consensus is not relevant for a digital thermometer. Accuracy is typically validated against highly calibrated reference thermometers (e.g., in a metrology lab) or in clinical trials against established methods, not by expert consensus on data interpretation.

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

• Not applicable. Adjudication methods are used to resolve disagreements among multiple experts interpreting complex data, which is not relevant for the direct measurement function of a digital thermometer.

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

• Not applicable. This device is not an AI-assisted diagnostic tool. An MRMC study is completely irrelevant.

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

• Not applicable. This device does not have an "algorithm only" component that operates independently for diagnosis or prediction. It's a measurement device.

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

• Not applicable in the context of expert consensus/pathology/outcomes data. For a digital thermometer, the "ground truth" for its accuracy and performance testing would be highly accurate reference measurements from certified calibration equipment or established clinical comparison methods, not subjective expert assessment.

8. The sample size for the training set

• Not applicable. This device does not use machine learning, therefore, there is no "training set."

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

• Not applicable. As there is no training set, there is no ground truth to establish for it in this context.

In summary: The FDA 510(k) clearance letter for the Digital Thermometer, Model T28, T28L, indicates a device that does not leverage AI/ML algorithms. Therefore, the detailed questions about acceptance criteria, study design, and ground truth establishment specific to AI-driven devices are not applicable to the information provided in this document. The clearance signifies that the device has demonstrated substantial equivalence to a legally marketed predicate device based on its intended use and conventional performance standards for clinical thermometers.

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The Digital Blood Pressure Monitor is intended to measure (systolic and diastolic) and pulse rate of adults.

Not Found

This FDA 510(k) clearance letter for the Digital Blood Pressure Monitor, Model GT-701, does not contain the detailed information required to describe acceptance criteria and a study proving the device meets those criteria.

The document is a regulatory clearance stating that the device is substantially equivalent to legally marketed predicate devices. It lists the regulation number, name, and product code, along with general information about FDA regulations and contact information.

Specifically, the following information is NOT available in the provided text:

1. A table of acceptance criteria and the reported device performance: This document does not present any performance data, acceptance criteria (e.g., accuracy standards like ISO 81060-2 limits), or a direct comparison.
2. Sample size used for the test set and the data provenance: There is no mention of a test set, sample size, or the origin of any data (country, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and their qualifications: No information about expert involvement or ground truth establishment is present.
4. Adjudication method: Not discussed.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: This type of study is typically for evaluating AI-assisted interpretation, which is not applicable to a blood pressure monitor. As such, no such study or its effect size is mentioned.
6. Standalone performance study: While the device is a standalone product, the document does not describe the study itself or its results.
7. Type of ground truth used: Not specified, as no study details are provided. For a blood pressure monitor, the "ground truth" would typically come from a highly accurate reference measurement method.
8. Sample size for the training set: Not applicable for this type of device, as blood pressure monitors do not typically use machine learning training sets in the same way AI algorithms do. Even if it did, the information is not provided.
9. How the ground truth for the training set was established: Not applicable and not provided.

In summary, the provided FDA clearance letter confirms the regulatory status of the device but does not include the detailed technical study results or acceptance criteria that would typically be found in a performance study report or a summary of safety and effectiveness data (SSED). To answer your questions, one would need access to the actual 510(k) submission or relevant performance study reports conducted by the manufacturer.

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The devices are intended to measure the systolic blood pressure, and pulse rate of an adult more than 12 years old individual by using a non-invasive technique, in which an inflatable cuff (220mm ~ 320mm) is wrapped around the arm. It can be used in medical facilities or at home. It is supplied for OTC use.

Digital Blood Pressure Monitor (Arm Type)

I am sorry, but based on the provided document, the acceptance criteria and study details you requested are not available. The document is an FDA 510(k) clearance letter for a "Digital Blood Pressure Monitor (Arm Type)," which confirms the device's substantial equivalence to a predicate device and outlines regulatory requirements. It does not contain information about specific performance acceptance criteria or details of a study proving the device meets them.

The sections of the document discuss:

• The FDA's 510(k) review and substantial equivalence determination.
• General controls and additional regulations applicable to the device.
• Instructions for contact and further regulatory information.
• Indications for Use for the device.

There is no mention of:

• A table of acceptance criteria and reported device performance.
• Sample sizes for test or training sets.
• Data provenance.
• Number or qualifications of experts for ground truth establishment.
• Adjudication methods.
• Multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance studies.
• Type of ground truth used.
• How ground truth for a training set was established.

Blood pressure monitor clearances typically rely on adherence to recognized consensus standards for accuracy and performance (e.g., ISO 81060-2 for non-invasive sphygmomanometers) rather than complex ground truth establishment studies with expert consensus or pathology data, which are more common for diagnostic imaging or AI-based devices. However, the specific details of such compliance are not included in this general clearance letter.

Therefore, I cannot provide the requested information based on the text provided.

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The Finger Clip Pulse Oximeter is a handheld non-invasive and multi-use device intended for spot-checking of oxygen saturation of arterial hemoglobin (SpO2) and Pulse Rate in hospital-type facilities, and homecare.

This device is not recommended for use during exercise or low perfusion scenarios.

This device is not intended for use on infants and newborns. (Recommended for people over 3 years and the thickness of finger greater than or equal to 7mm).

Not Found

The provided text is an FDA 510(k) clearance letter for a Finger Clip Pulse Oximeter. It confirms that the device is substantially equivalent to legally marketed predicate devices. However, this type of document does not contain the detailed information required to answer your specific questions about acceptance criteria and the comprehensive study that proves the device meets those criteria.

The information you're asking for (acceptance criteria table, study sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, training set details) is typically found in the summary of safety and effectiveness (SSE) or clinical study reports that are part of the original 510(k) submission. These documents are generally not made public in their entirety by the FDA in the clearance letter itself.

The clearance letter only states the following relevant points:

• Device Name: Finger Clip Pulse Oximeter
• Regulation Number: 21 CFR 870.2700 (Oximeter)
• Regulatory Class: Class II
• Product Code: DQA
• Indications for Use: Handheld non-invasive and multi-use device intended for spot-checking of oxygen saturation of arterial hemoglobin (SpO2) and Pulse Rate in hospital-type facilities, and homecare. Not recommended for use during exercise or low perfusion scenarios. Not intended for use on infants and newborns (recommended for people over 3 years and finger thickness >= 7mm).

To answer your request, I would need access to the actual 510(k) submission's technical documentation, specifically the performance testing and clinical data sections, which are not included in the provided text.

Therefore, I cannot populate the table or provide details on the study as requested, as the necessary information is not present in the given document.

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