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The Doctor Tecar Plus and Doctor Tecar Smart devices are intended to provide topical heating for the purpose of elevating tissue temperature for treatment of selected medical conditions such as: relief of pain, muscle spasms, increase in local circulation.

Doctor Tecar Plus and Doctor Tecar Smart are devices for diathermy. This therapy develops an increase in temperature in the area of the body which is treated through the passage of a particular electrical current. Through twin delivering modes, capacitive and resistive, the operator can set a specific treatment. The purpose of the treatment is to raise the temperature inside the tissue at a value maximum to 45 °C. The device is composed by a touch screen and a Multi-Function knob (only Plus model) for managing all the device's functions, a plate, an handpiece for the delivery of radiofrequency energy, software and an on/off button to activate and deactivate the energy emission.

The provided text does not contain detailed acceptance criteria or a study proving the device meets specific performance criteria in the typical sense of an AI/ML medical device submission. Instead, it describes a 510(k) submission for a non-AI medical device (radiofrequency device) and its general safety and performance testing.

The document primarily focuses on establishing substantial equivalence for the "Doctor Tecar Plus" and "Doctor Tecar Smart" devices to a predicate device (NuEra Tight RF Family, K200359). The "study" mentioned is a "Bench Test" to demonstrate the device's capability to maintain skin temperature.

Given the information, I will interpret the request within the context of the provided document, even though it doesn't involve AI/ML or comparative effectiveness studies with human readers.

Here's an attempt to extract and present the information based on the provided text:

Acceptance Criteria and Device Performance (Based on provided "Bench Test")

1. Table of Acceptance Criteria & Reported Device Performance

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

• Sample Size: 3 different people.
• Data Provenance: The document does not specify the country of origin of the data. The test was conducted for each person in three different places on the body. It included participants with light and dark skin, and different somatotypes. The test was performed in automatic mode (using electrodes) and in manual mode (with nine different applicators) for each person and each body place. The nature of the study appears to be a prospective bench test, as it describes actively performing measurements.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Not Applicable (N/A): This type of information is not relevant to the described "Bench Test." The test focuses on physical measurements (temperature) directly from the device and human skin, not on subjective expert interpretation of output (like image diagnosis with AI). There's no mention of experts establishing a "ground truth" in the diagnostic sense.

4. Adjudication Method for the Test Set

• Not Applicable (N/A): No adjudication method is mentioned or required for this type of quantitative bench test. The temperature measurements are objective.

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

• No: A MRMC comparative effectiveness study was not done. This document describes a 510(k) submission for a radiofrequency medical device, not an AI/ML diagnostic aid. Therefore, there is no discussion of human readers improving with or without AI assistance.

6. Standalone (Algorithm Only) Performance

• Not Applicable (N/A): This is a physical medical device, not an algorithm. The "Bench Test" describes the device's direct physical performance; thus, the concept of "standalone algorithm performance" is not relevant.

7. Type of Ground Truth Used

• Physical Measurements/Observed Performance: The "ground truth" in this context is the actual temperature measured on the skin and the device's ability to maintain that temperature within a specified range, as observed directly during the bench test. It's not a diagnostic "ground truth" derived from expert consensus, pathology, or outcomes data.

8. Sample Size for the Training Set

• Not Applicable (N/A): This document describes testing of a physical medical device, not the development or training of an AI algorithm. Therefore, there is no concept of a "training set" in this submission.

9. How Ground Truth for Training Set Was Established

• Not Applicable (N/A): As there is no training set, this question is not applicable to the provided document.

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The Doctor Tecar device is intended to provide topical heating for the purpose of elevating tissue temperature for the treatment of selected medical conditions such as relief of pain, muscle spasms, and increase in local circulation.

The Doctor Tecar generates a high frequency sinusoidal current with a monopolar mode of application using two electrodes. A fixed electrode is placed in contact with the patient and a hand held electrode is manipulated by a therapist. When both electrodes are in contact with a patient the electrical circuit is closed and RF therapy can be provided. The device can be operated in a capacitor resistive monopolar mode. The product consists of a power console on a moveable trolley, LCD monitor, and accessories including capacitive resistive electrodes and multipolar electrodes. The unit can be adjusted to provide various levels of treatment frequency ranging from 460 KHz to 600 KHz.

The provided FDA 510(k) summary for the "Doctor Tecar" device focuses on demonstrating substantial equivalence to a predicate device rather than providing specific acceptance criteria and a detailed study proving the device meets those criteria. The submission is for a Radiofrequency Induced Heat device, which is an electrosurgical cutting and coagulation device.

Here's an analysis of the available information in response to your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for device performance. Instead, it relies on demonstrating that the Doctor Tecar device performs comparably to its predicate device, the Winback 3SE (K162828), and meets general safety and performance standards. The "Explanation of Differences" column in the Predicate Device Comparison Table (page 5) serves as an indirect way of stating performance equivalence rather than specific acceptance metrics.

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

The document mentions "Studies were done in Italy using volunteers of varying skin colors to assess the capacity of the device to elevate tissue temperature in the treatment areas." (page 6).

• Sample Size: Not specified. The term "volunteers" is used, but no number is given.
• Data Provenance: Italy.
• Retrospective or Prospective: Implied to be prospective as studies were "done" using volunteers.

For other tests (electrical safety, EMC, biocompatibility, usability, software) which are typically conducted in a laboratory or simulated environment, specific "test sets" in the sense of patient data are not applicable. These tests use engineering samples or components of the device.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This type of information is generally not applicable for the tests described for this device.

• Tissue Temperature Elevation Assessment: The ground truth for safe therapeutic temperature increase would be based on established medical and physiological understanding, not expert consensus in the typical sense of reading medical images. The "ground truth" here is the objective measurement of temperature and its comparison to known physiological thresholds for safety and efficacy.
• Other Tests (e.g., electrical safety, EMC, biocompatibility): Ground truth is established by compliance with international standards and validated testing methodologies, not by expert interpretation in the medical sense.

4. Adjudication Method for the Test Set

Adjudication methods (like 2+1, 3+1) are typically used in clinical studies where multiple human readers assess medical images or clinical outcomes, and their disagreements need to be resolved to establish ground truth for algorithm performance evaluation.

This information is not applicable to the type of studies presented here, which are primarily engineering and bench testing, as well as a volunteer study for temperature elevation.

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 information is not applicable. The Doctor Tecar device is a treatment device (Radiofrequency Induced Heat) and not an AI-powered diagnostic or assistive tool for human readers. Therefore, an MRMC study assessing human reader improvement with or without AI assistance is irrelevant to this device.

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

This information is not applicable. The Doctor Tecar device is a physical treatment device, not an algorithm. Its performance is evaluated through its physical characteristics, safety, and physiological effects, not as a standalone algorithm.

7. The Type of Ground Truth Used

• Tissue Temperature Elevation: The ground truth is the objective measurement of tissue temperature elevation in volunteers, compared against established physiological thresholds for safe and therapeutic heating.
• Electrical Safety & EMC: The ground truth is compliance with specific international standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60601-2-2).
• Biocompatibility: The ground truth is the absence of cytotoxic, sensitizing, or reactive responses to the device materials as defined by ISO 10993 standards.
• Usability & Risk Management: The ground truth is the successful verification of user interface and safety features against predetermined functional requirements and risk assessments.
• Software Assessment: The ground truth is compliance with FDA software validation guidelines, ensuring proper functionality, hazard analysis, and validation against specified requirements.

8. The Sample Size for the Training Set

This information is not applicable. The Doctor Tecar device is not an AI/ML algorithm that requires a training set. Its development involves engineering design and testing, not machine learning model training.

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

This information is not applicable as there is no training set for this type of device.

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