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510(k) Data Aggregation

    Why did this record match?
    Reference Devices :

    K030437, K122154, K133483, K160608, K183169, K210967

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Intended to temporarily relieve minor muscle aches and to temporarily increase circulation to the treated area in people who are in good health.

    Device Description

    Bio Compression Systems' Sequential Circulators are powered inflatable tube massagers which consist of a segmented pneumatic sleeve ("garment") connected to a pneumatic compression pump ("pump"). The pump cyclically inflates the garment's segments ("chambers") in sequence from the distal end toward the trunk of the body. The sequential inflation of the garment simulates kneading and stroking of tissues with the hands, increasing circulation on the limb worn.

    The core components of the pump are the motor, air compressor, disc valves, and micro switch. The air compressor generates air flow into a stationary disc valve. The motor moves a rotating disc valve. The geometry of the disc valve directs air flow and cyclically triggers the micro switch.

    The pump is controlled by softkeys and an LED display (models SC-1004-DL, SC-1008-DL, SC-2004-DL, SC-2008-DL) or by a touch screen LCD (models SC-4004-DL, SC-4008-DL).

    The device uses the Predicate Device's garments.

    AI/ML Overview

    The provided text is a 510(k) Pre-market Notification for a medical device (Sequential Circulators) and does not contain information about a study with acceptance criteria and reported device performance in the context of diagnostic accuracy, which would include details about sample sizes, ground truth establishment, expert qualifications, or comparative effectiveness studies (MRMC or standalone).

    This document focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and performance data for safety and electrical compatibility, and functional verification, rather than a clinical efficacy or diagnostic accuracy study.

    Therefore, many of the requested categories cannot be filled from the provided text.

    Here's a breakdown of what can be extracted and what cannot:

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

    The document doesn't present acceptance criteria in the format of diagnostic metrics (e.g., sensitivity, specificity, AUC) or a study proving those criteria are met. Instead, it lists technical standards and verification testing.

    Acceptance Criteria (Standards and Tests)Reported Device Performance and Compliance
    ANSI/AAMI ES60601-1:2005/(R)2012 and A1:2012Compliant
    ANSI/AAMI HA60601-1-11:2015-08Compliant
    IEC 60601-1:2005/AMD1:2012Compliant
    IEC 60601-1-2:2014Compliant
    IEC 60601-1-6:2010/AMD1:2013Compliant
    IEC 60601-1-11:2015Compliant
    Observation of operation (Predicate Device routine acceptance tests)Verified
    Pressure testing (Predicate Device routine acceptance tests)Verified
    HiPot (dielectric withstand test) testing (Predicate Device routine acceptance tests)Verified
    Cycle time verification and validationVerified
    Treatment time verification and validationVerified
    Pressure setting endpoint testingVerified
    Operation to confirm all modes, settings, and mode/setting changes function as intendedVerified
    Software verification and validation (minor level of concern)Verified

    2. Sample size used for the test set and the data provenance: Not applicable. The "test set" here refers to the device itself being tested against technical standards, not a dataset of patient cases.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for diagnostic accuracy is not relevant here.

    4. Adjudication method 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: Not applicable. This is not an AI/diagnostic imaging device.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm-only device.

    7. The type of ground truth used: Not applicable in the context of diagnostic accuracy. The "ground truth" for this device's performance relates to compliance with engineering and safety standards, and functional specifications.

    8. The sample size for the training set: Not applicable. This is not a machine learning/AI device requiring a training set.

    9. How the ground truth for the training set was established: Not applicable.

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    K Number
    K203552
    Device Name
    Rapid Reboot
    Date Cleared
    2020-12-22

    (18 days)

    Product Code
    Regulation Number
    890.5650
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K183169

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    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.

    Device Description

    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.

    AI/ML Overview

    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.

    Test TypeAcceptance Criteria (Implied)Reported Device Performance
    Biocompatibility TestingMaterials are biocompatible (non-cytotoxic, non-irritating, non-sensitizing).Passed Cytotoxicity, Irritation, and Sensitization testing.
    Electrical Safety (IEC 60601-1)Compliant with electrical safety standards.Passed all electrical safety tests.
    Electromagnetic Compatibility (IEC 60601-1-2)Compliant with EMC standards.Passed all EMC tests.
    Wireless Coexistence (ANSI IEEE C63.27-2017)Compliant with wireless coexistence standards.Passed all relevant tests.
    Software Verification & Validation (IEC 62304)Software is verified and validated.Conducted in accordance with IEC 62304.
    Mechanical Stress TestingDevice withstands mechanical stress (details not specified).Conducted (details not specified).
    Human Factors Engineering Usability TestingIntended users can properly use the device (safe and effective).Usability Study conducted to ensure proper use.
    Minimum, Interval, Maximum Air Pressure TestAir pressure functions within specified ranges.Test conducted (results not explicitly stated, but implied compliance).
    Maximum Electric Current Value TestElectric current values are within safe limits.Test conducted (results not explicitly stated, but implied compliance).
    Maximum Airflow Valve TestAirflow valve functions as intended.Test conducted (results not explicitly stated, but implied compliance).
    Noise Level TestNoise levels are within acceptable limits.Test conducted (results not explicitly stated, but implied compliance).
    Button and Display TestButtons and display function as intended.Test conducted (results not explicitly stated, but implied compliance).

    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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