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The Reprieve by Regenesis™ device is indicated to generate deep heating within body tissues for the treatment of conditions such as relief of pain and muscle spasms.

The Reprieve by Regenesis™ device (Reprieve) is a prescription shortwave diathermy (SWD) device consisting of a single base unit connected to one or two treatment applicators. The device connects to A/C power through an external, off-the-shelf, power supply generating radiofrequency energy which delivers SWD through the treatment applicator(s).

The base unit houses an LCD screen with four raised buttons, two on each side of the LCD screen, and an LED light bar. The back of the base unit has a molded slot to accommodate the treatment applicator(s), a pouch to store the power supply, and a cable wrapping loop to organize the treatment applicator cables. The bottom of the base unit has an opening to connect the A/C power supply. The treatment factory-affixed coaxial cables. The top is the treatment side of the applicator is a darker color to distinguish it from the lighter-colored bottom, the non-treatment side. The top also has circular imagery denoting the center of the applicator. The Reprieve device generates a 27.12 MHz RF signal that has a 100% duty cycle when programmed to continuous wave (CW) mode. When prescribed for pulsed wave (PW) mode, the pulse rate (e.g., pulses per second) can be varied from 200Hz to 1000Hz in 200Hz increments, and the pulse width (e.g., the elapsed time the pulse is on) from 20µsec to 100µsec in 20µsec increments.

The provided text describes the acceptance criteria and the studies performed for the Reprieve by Regenesis™ device, a shortwave diathermy system.

Here's a breakdown of the requested information:

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

The document does not explicitly present a table of acceptance criteria and reported device performance in the format of specific numerical values for each criterion. Instead, it states that the device "complies with" or "meets the requirements" of various standards and that usability results were "positive" and demonstrated effectiveness. The thermal performance is given as achieving a "4°C temperature rise at 25 minutes," which matches the predicate.

Below is a table summarizing the mentioned performance aspects and the statements regarding their compliance/results:

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

• Sample Size for Test Set:
  • Usability/Human Factors: "representative naïve users" were used. A specific number is not provided.
  • Bench Testing: An "in vitro muscle phantom" was used. This is not a human sample size.
  • Other tests (Electrical Safety, Biocompatibility, Software V&V) are compliance or engineering tests and do not involve human test sets in the same way.
• Data Provenance:
  • The document does not specify the country of origin of the data or whether the studies were retrospective or prospective. Given the nature of these tests (bench, usability validation), they would typically be prospective studies.

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)

• For the technical tests (electrical safety, EMC, biocompatibility, software V&V, bench testing), the ground truth is established by adherence to recognized international standards and guidances (e.g., IEC, ISO, FDA guidances). These are not typically evaluated by human experts establishing ground truth in a clinical sense, but by qualified personnel performing the testing and analyses according to standard protocols.
• For the Usability/Human Factors study, "representative naïve users" were observed performing tasks. The "ground truth" here is compliance with usability principles and demonstration that mitigations were effective. There is no mention of external experts defining ground truth for the users' performance; rather, the study itself assesses user performance against predefined objectives.

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

• The document does not describe any adjudication method for the test sets. The studies conducted are primarily performance, safety, and compliance tests against engineering standards and usability goals, rather than studies requiring expert consensus on clinical diagnoses or outcomes.

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.
• The device described is a medical device for therapeutic deep heating, not an AI-assisted diagnostic tool for human readers. Therefore, there is no discussion of human readers, AI assistance, or effect sizes related to such a study.

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

• The concept of "standalone" algorithm performance without human-in-the-loop is relevant to AI/imaging devices. This device is a shortwave diathermy system. Its performance evaluation involves bench testing (e.g., thermal performance in a phantom) and usability studies with human users, but not an "algorithm-only" performance in the context of diagnostic AI.

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

• Electrical Safety and EMC: Ground truth is defined by the requirements of the specified IEC standards.
• Usability/Human Factors: Ground truth is established by predefined success criteria for tasks performed by users and adherence to FDA guidance and IEC standards for usability.
• Biocompatibility: Ground truth is defined by meeting the requirements of ISO 10993-1:2018 and FDA guidances.
• Software Verification and Validation: Ground truth is defined by compliance with FDA guidance documents and IEC 62304.
• Bench Testing: Ground truth for thermal performance is established by objective temperature measurements within an in vitro muscle phantom against predefined therapeutic temperature ranges and safety limits.

8. The sample size for the training set

• This device is a physical medical device (shortwave diathermy system), not an AI/machine learning algorithm that requires a training set in that context. Therefore, the concept of a "training set" for an algorithm is not applicable here. The design and development of the device would involve engineering, prototyping, and iterative testing, but not an AI training set.

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

• As explained in point 8, the device does not employ an AI/machine learning algorithm in the sense that would require a "training set" with ground truth data for model learning. Thus, this question is not applicable.

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