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The Compact II is indicated for:

• Relaxation of muscle spasms;
• Prevention or retardation of disuse atrophy;
• Increasing local blood circulation;
• Muscle re-education;
• Immediate post-surgical stimulation of calf muscles to prevent venous thrombosis; and
• Maintaining or increasing range of motion.

The Compact II device generates (or induces) electric current in targeted tissues. affected by a high induction magnetic field to stimulate those tissues to treat the indicated conditions.

The device includes a transducer, which is used to provide the magnetic stimulation, which creates electrical fields by pulse current flowing from a capacitor according to the principle of Faraday's Law. Whenever the capacitor bank is discharged by the action of the control system, a pulse of current flows through the stimulating coil. The magnetic stimulation creates intense, rapidly changing magnetic electrical fields.

The Compact II device consists of a console and transducer for magnetic stimulation. The function of magnetic stimulation is operated by adjusting parameters such as Mode, Intensity and Time. These parameters can be controlled by users on the LCD Touch Screen.

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The Curapuls 670 is indicated to be used for applying therapeutic deep heat in body tissues for the treatment of selected medical conditions such as:

1. Relieving pain;
2. Reducing muscle spasm;
3. Increasing range of motion of contracted joints using heat and stretch techniques; and
4. Increasing blood flow to tissues in the treatment area.

The Curapuls 670 is a two-channel microprocessor-controlled unit for pulsed shortwave therapy. Through inductive electrodes (Circuplodes), high-frequency electric currents are produced within the body. Pulsed energy at 27.12 MHz is absorbed by soft tissues. Three sizes of Circuplodes (140mm, 90mm and elliptical) are available to accommodate different size treatment areas.

Deep heating of tissue is achieved with ease by means of inductive electrodes. The user can connect two applicators. Activation of each applicator can be controlled from the console menu.

This device is a prescription equipment. Use by any persons other than physicians is prohibited.

This document is a 510(k) clearance letter for a medical device called Curapuls 670, a shortwave diathermy unit. It details the device's characteristics, its comparison to a predicate device (BTL-703), and the non-clinical testing performed to establish its substantial equivalence.

However, the provided text does not contain information related to an AI/ML-driven device or a study involving human-in-the-loop performance, such as a multi-reader multi-case (MRMC) study. It describes a physical therapy device used for applying therapeutic deep heat. Therefore, most of the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI/ML evaluation (e.g., sample size for test/training sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance) is not applicable to this document.

The "acceptance criteria" and "study" described in this document are focused on demonstrating the safety and effectiveness of the Curapuls 670 as a medical device for therapeutic deep heating, primarily through non-clinical testing and comparison to a predicate device.

Let's extract what is available regarding acceptance criteria and the "study" (non-clinical testing) from the provided text:

Acceptance Criteria and Study for Curapuls 670 (Non-AI Device)

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

The document doesn't present a formal table of quantitative acceptance criteria for performance in the way one might expect for an AI model (e.g., specific sensitivity/specificity thresholds). Instead, the "acceptance criteria" for this device are primarily met by demonstrating compliance with recognized medical device safety and performance standards and showing substantial equivalence to a legally marketed predicate device.

The reported "device performance" is primarily qualitative and centered around its stated indications for use and its electrical/thermal properties.

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

• Sample Size: Not applicable in the context of a dataset for an AI model. The document refers to "final, finished devices" undergoing testing. The number of physical devices tested isn't specified, but it's a small manufacturing sample for validation, not a large patient data sample.
• Data Provenance: Not applicable for an AI dataset. The "data" here refers to test results from physical devices.

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

• Not applicable as this is not an AI/ML device requiring expert labeling of data. The ground truth for performance is based on established engineering and medical device standards (e.g., temperature measurements, electrical safety parameters, usability assessments).

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

• Not applicable. This is not a study involving human reader interpretations that require adjudication.

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:

• No. An MRMC comparative effectiveness study was not done. This is not an AI-assisted diagnostic or interpretative device.

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

• Not applicable. This is not an algorithm. The device's performance is inherently "standalone" in the sense that it performs its physical function (producing heat) independently, but it is operated by a human user (a physician).

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

• The "ground truth" for this device's performance is based on:
  • Engineering specifications and regulatory standards: Compliance with IEC, ISO, and ANSI/AAMI standards for electrical safety, EMC, biocompatibility, and software quality.
  • In vivo thermal measurements: Direct measurement of tissue temperature increase (40-45°C) to validate the therapeutic heating capability.
  • Usability assessments: Evaluation of the user interface and safety features by presumably qualified personnel to ensure satisfactory operation.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device trained on a dataset.

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

• Not applicable. There is no training set for an AI model.

In summary, the provided FDA 510(k) clearance letter pertains to a non-AI medical device (Shortwave Diathermy). Therefore, the detailed questions appropriate for an AI/ML device's validation study are largely irrelevant to this document. The "acceptance criteria" are met by demonstrating compliance with established safety and performance standards relevant to physical therapy equipment and showing substantial equivalence to a predicate device.

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Therapeutic Ultrasound is indicated for:
• Pain Relief
• Reduction of muscle spasms
• Localized increase in blood flow
• Increase range of motion of contracted joints using heat and stretch techniques

This device is a multi-frequency ultrasound therapy equipment. The mounted applicators provide both 1 and 3 MHz operation. Depending on the area of treatment, two different types of applicators, large and small, are available. They are suitable for treatment under water.
Contact control suspends the application of ultrasound energy when acoustical contact with the treatment area becomes insufficient. The user can connect two ultrasound applicators. Activation of each applicator can be controlled from the ultrasound menu.
This device is a prescription equipment. Use by any persons other than physicians is prohibited.

This document is a 510(k) Summary for the Sonopuls 190 medical device, which is an ultrasound therapy equipment. It aims to demonstrate substantial equivalence to a predicate device (Sonomed IV/V).

Here's a breakdown of the requested information based on the provided text, focusing on the study that proves the device meets acceptance criteria:

The context of the provided document is a 510(k) submission for a non-AI-powered therapeutic ultrasound device. Therefore, many of the requested elements specifically pertaining to AI/ML device performance and testing (e.g., sample size for training set, number of experts for ground truth, MRMC studies, standalone algorithm performance) are not applicable or explicitly mentioned in this type of submission. The "acceptance criteria" here primarily refer to meeting regulatory standards and demonstrating substantial equivalence to a predicate device, rather than a specific performance metric for a diagnostic AI model.

However, I will extract what is available and note where the information is not present due to the nature of the device and submission.

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

The document doesn't provide specific quantitative "acceptance criteria" for the device's therapeutic performance in a table format with corresponding "reported device performance" in the way one might expect for a diagnostic AI device (e.g., sensitivity/specificity targets). Instead, it relies on demonstrating compliance with various electrical safety, performance, biocompatibility, and software standards, and showing that any differences from the predicate device do not raise new questions of safety or effectiveness.

The closest equivalent to "performance" for this type of device relates to its physical output parameters (e.g., intensity, frequency, temperature rise, penetration depth) and compliance with safety standards. The "acceptance criteria" are implied by adherence to the listed standards and the conclusion of substantial equivalence.

Here's a table based on the "7. Technological Characteristics" and "8. Discussion of Differences", which details the device's specifications and compares them to the predicate, and serves as an indirect form of "performance" demonstration in this context. The "acceptance criteria" are implied to be "comparable to or not raising new questions of safety/effectiveness compared to the predicate device, and compliant with relevant standards."

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

This document is for a physical medical device (ultrasound therapy equipment), not an AI/ML diagnostic device. Therefore, there isn't a "test set" in the sense of a dataset of medical images or patient data. The "testing" refers to bench testing, electrical safety testing, biocompatibility testing, and software assessment.

• Sample size for test set: Not applicable in the context of a dataset for an AI model. For physical product testing, it would typically relate to the number of devices tested, which isn't specified but typically follows established engineering test protocols (e.g., testing multiple units to confirm reproducibility). The text mentions "final, finished devices" were tested.
• Data provenance (country of origin, retrospective/prospective): Not applicable for this type of device testing. Testing was done on the physical device itself.

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 this context is established by engineering measurements, compliance with international standards, and verification against known physical parameters. There are no human experts classifying data for ground truth in the way there would be for a diagnostic AI model.

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

Not applicable. This is not a study involving human reader adjudication of data.

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 is a physical therapy device, not an AI-assisted diagnostic tool. No MRMC study was performed or required.

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

Not applicable. This is a physical therapy device, not an AI algorithm. Its "standalone performance" refers to its ability to meet its specifications and safety standards as tested in the lab, which was done as indicated under "9. Summary of Testing."

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

The "ground truth" for this device's performance is established through:

• Compliance with international standards: IEC 60601-1, IEC 60601-1-2, IEC 60601-2-5, IEC 62304, ISO 10993-1. These standards define acceptable safety limits, performance parameters, and testing methodologies for medical electrical equipment and specifically ultrasonic physiotherapy equipment.
• Bench testing/Laboratory measurements: Demonstrated electrical safety, electromagnetic compatibility, and ultrasonic physiotherapy equipment requirements.
• Biocompatibility testing: According to ISO 10993-1.
• Software assessment: In accordance with FDA software validation guidelines (IEC 62304).
• Thermal tissue testing: For parameters related to temperature rise and penetration depth, using a "reference device" with identical (or similar and proven safe) parameters to support the submission where direct predicate data was not available (e.g., for maximum output power, contact temperature, penetration depth, timer range). This implicitly serves as the "outcomes data" for thermal effects, demonstrating that the device operates safely within thermal limits.

8. The sample size for the training set

Not applicable. This device does not use an AI/ML algorithm that requires a training set.

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

Not applicable. There is no training set for this device.

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