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The Rapid Reboot REGEN+, REGEN, or GENESIS Compression Therapy Systems are indicated for the temporary relief of minor muscle aches and pains and for temporary increase in circulation to the treated areas in people who are in good health. The Rapid Reboot REGEN, or GENESIS Compression Therapy Systems simulate kneading and stroking of tissues by using an inflatable garment.

The Rapid Reboot GENESIS, REGEN, and REGEN+ model systems are powered inflatable tube massagers (Product Code IRP). They are indicated for the temporary relief of minor muscle aches and pains and for the temporary increase in circulation to the treated areas in people who are in good health. They simulate kneading and stroking of tissues by using an inflatable garment. The air pump is connected to the dedicated sleeves via a series of hoses, and each sleeve has four (4) compression chambers. The compression massage direction is from limb end to body center (distal to proximal). By inflating the air chambers sequentially and then deflating as one cycle, the pressure can be adjusted to avoid any discomfort to the user. The sleeve works under the action of sensors and microprocessors. Software controls the timing and pressure reflected by the sensor, cycling airflow into and out of the sleeves to compress the body in a controlled and specific manner. Each unit also has a user interface that allows users the ability to control several aspects of the massage: i.e., intensity (pressure), session duration, and mode. The devices are powered by an external IEC 60601-1 compliant power supply and can also be powered by an internal IEC 62133-compliant lithium-ion battery.

The user interface on the GENESIS, REGEN, and REGEN+ models is a 6" HD LED touchscreen with capacitive sensors identical to most smartphones. The user interface provides for:

• Starting and stopping the massage treatment;
• Adjusting the time, intensity (pressure), and type of distal-to-proximal sequence (Mode).

While the main functions, indications for use, and parameters of settings are the same on the three models, there are differences in non-crucial features and resolution of settings that are intended for marketing differentiation and user preferences: e.g., the REGEN and REGEN+ models offer pressure resolution of 5 mmHg from 0 to 200 mmHg for a total of 40 potential pressure settings, while the GENESIS only offers 7 pressure settings. Similarly, the REGEN and REGEN+ allow the user to set the session duration, or time, to the minute between 1 and 179 minutes (2 hrs and 59 minutes), the GENESIS only allows the user to set a session duration of 10, 20, 30, 40, 50, or 60 minutes.

In addition to the user interface on these respective devices, these proposed models have Bluetooth Low Energy (BLE) capability that allows the use of a Rapid Reboot app to control a device. The app mimics the device interface graphics and buttons, allowing the user to use a compatible Android or iOS powered smartphone or tablet to control the devices core functions just as if they were using the interface on the device. The app functionality is limited to mimicking the device interface and does not provide additional settings that alter the therapy provided by the device. When paired with a REGEN or REGEN+, the app does offer additional, non-critical and non-function related for marketing differentiation and user preferences: e.g., informational features in the menu, programs (i.e., saved settings) that can be saved and quickly applied to future sessions, and the ability to access logs showing usage.

The provided document is a 510(k) Pre-market Notification for the Rapid Reboot REGEN+, REGEN, and GENESIS Compression Therapy Systems. This document is a regulatory submission to the FDA, demonstrating substantial equivalence to a predicate device, rather than a study designed to establish acceptance criteria or device performance with a specific study design for diagnostic accuracy.

Therefore, many of the requested elements (e.g., acceptance criteria table with reported performance, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, type of ground truth) typically found in studies for diagnostic devices are not applicable to this submission.

However, I can extract information regarding overall performance testing and conclusions used to support the substantial equivalence claim.

Here's a summary based on the provided text, addressing the applicable points:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria for diagnostic performance or specific numerical performance metrics in the way one would for a diagnostic AI. Instead, it demonstrates compliance with recognized standards and successful completion of various types of engineering and usability testing to show the new devices are as safe and effective as the predicate device (K182668). The "performance" here refers to engineering performance rather than diagnostic accuracy.

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

• The document does not describe a "test set" in the context of diagnostic data. The "testing" refers to engineering and usability evaluations.
• For usability testing, a "Usability Study" was conducted, but the sample size of users is not specified.
• The data provenance (country of origin, retrospective/prospective) for any specific performance study is not provided, as the studies are primarily engineering validation rather than clinical data collection.

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

• Not applicable. This device is a physical therapy/recovery device, not a diagnostic AI. There is no concept of "ground truth" established by medical experts for a test set in this context. The "truth" lies in compliance with engineering standards and usability.

4. Adjudication method for the test set

• Not applicable. There is no diagnostic test set requiring expert 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

• Not applicable. This device is not an AI diagnostic tool and does not involve human readers interpreting images or data with or without AI assistance.

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

• Not applicable. This device is a physical therapy system. While it has software, its "performance" is based on its functional operation, safety, and effectiveness in delivering compression therapy, not on an algorithm making standalone diagnostic interpretations.

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

• Not applicable. See point 3. The "truth" for this device's performance is compliance with electrical, mechanical, biocompatibility, software, and usability standards and functional specifications.

8. The sample size for the training set

• Not applicable. This device does not use machine learning in a way that requires a "training set" for diagnostic algorithm development. The software capabilities are for controlling the device's functions, not for learning from data to make predictions or classifications.

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

• Not applicable. See point 8.

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The Rapid Reboot Compression Therapy System is indicated for the temporary relief of minor muscle aches and pains and for temporary increase in circulation to the treated areas in people who are in good health. The Rapid Reboot Compression Therapy System simulates kneading and stroking of tissues by using an inflatable garment.

Rapid Reboot Compression Therapy System ("Rapid Reboot") consists of an air pump, air pressure sensor, and sleeves working together as one unit. The air pump is connected to the dedicated sleeves via a series of hoses; each sleeve has four (4) compression chambers. The compression massage direction is from limb end to body center. By inflating the air chambers sequentially and then deflating as one cycle, the pressure can be adjusted to avoid any discomfort to the patient. The sleeve works under the action of sensor and microprocessor. Software controls the timing and pressure reflected by the sensor, cycling airflow into and out of the sleeves to compress body

The provided text describes the "Rapid Reboot Compression Therapy System" and its substantial equivalence determination. However, it does not include detailed acceptance criteria or a specific study proving the device meets those criteria in the way typically found for AI/ML-driven medical devices (e.g., performance metrics like sensitivity, specificity, or AUC, alongside sample sizes for test and training sets, expert qualifications for ground truth, etc.). This document solely focuses on demonstrating substantial equivalence to predicate devices based on indications for use, technological characteristics, and compliance with general medical device standards.

Therefore, most of the requested information regarding acceptance criteria and performance study details for an AI/ML device is not present in the provided text.

Here's an attempt to answer based only on the available information:

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

The document does not specify quantitative acceptance criteria in terms of performance metrics (e.g., sensitivity, specificity, accuracy) or device performance against such metrics. Instead, it demonstrates compliance with general medical device standards and substantial equivalence to predicate devices.

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

Not applicable. The document describes performance testing based on compliance with general safety, EMC, and biocompatibility standards for the device itself, not on analyzing patient data or clinical images. It's a physical device, not an AI/ML diagnostic or prognostic system.

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. This is not a study requiring expert-established ground truth on patient data.

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

Not applicable.

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 study was not done. The device is a compression therapy system, not an AI-assisted diagnostic tool.

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

Not applicable. The device is a physical therapy system, not an algorithm.

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

Not applicable. Ground truth as typically understood for AI/ML performance on clinical data is not relevant here. The "ground truth" equivalent would be the established requirements of the referenced IEC and ISO standards that the device was tested against.

8. The sample size for the training set

Not applicable. The device is not an AI/ML model trained on data.

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

Not applicable.

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