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To be used for temporary relief of pain associated with sore and aching muscles in the shoulder, waist, back, upper extremities (arm), and lower extremities (leg) due to strain from exercise or normal household work activities.

It is intended to be used to stimulate healthy muscles in order to improve and facilitate muscle performance.

The subject device is a Transcutaneous Electrical Nerve Stimulator (TENS) and Powered Muscle Stimulator (PMS), intended for the over-the-counter use to temporarily relieve pain and stimulate muscle in different body areas. The double-channel subject device, which is compact, portable, and microprocessor-controlled, delivers a gentle electrical pulse through the connecting wires and electrode pads to the user's skin for pain relief and muscle stimulation. The electrode pad used consists of gel, carbon film, cloth backing, and electrode connector, which is 510(k)-cleared and biocompatible, According to the need of users, the pulse intensity can be adjustable on the front control panel of the device.

This document describes the 510(k) summary for the IQ Technologies Pro IVs, Pro V, and Pro VI, which are Transcutaneous Electrical Nerve Stimulators (TENS) and Powered Muscle Stimulators (PMS). The core argument for acceptance is substantial equivalence to a previously cleared predicate device (IQ Technologies, K131290), rather than a study proving the device meets strict performance acceptance criteria based on clinical outcomes or diagnostic accuracy. Therefore, the provided information does not contain the typical details of a study involving a test set, ground truth, and expert adjudication as one might see for an AI/ML medical device.

Based on the provided text, here's a description framed within the context of substantial equivalence for this type of device:

Acceptance Criteria and Study for Substantial Equivalence

1. Table of Acceptance Criteria (for Substantial Equivalence) and Reported Device Performance

Instead of explicit performance metrics like sensitivity or specificity, the "acceptance criteria" here are the technical characteristics and intended use being sufficiently similar to the predicate device. The device performance is demonstrated by the comparative table showing these similarities and compliance with relevant safety standards.

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

• Test Set: The "test set" in this context refers to the subject device itself and its components undergoing non-clinical testing. There isn't a patient-level "test set" as would be used for an AI/ML algorithm or clinical trial. The testing is performed on the device prototypes/production samples.
• Data Provenance: The data provenance is from the manufacturer's non-clinical testing laboratories (implicitly, given compliance with international standards) and appears to be prospective as it involves the testing of the subject's device design. There is no mention of country of origin for the data beyond the standards being international.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This type of information is not applicable to this 510(k) submission. The "ground truth" for electrical stimulation devices is based on engineering specifications and compliance with recognized safety and performance standards (e.g., IEC standards). Expert consensus or qualifications of human readers/experts are not relevant for establishing the performance of a TENS/PMS device in this context.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies or for establishing ground truth from expert readings (e.g., for imaging studies). For electro-mechanical devices demonstrating substantial equivalence through non-clinical testing, adjudication is not a relevant concept.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not performed. This type of study is typically done for diagnostic devices, especially those involving human interpretation of data (e.g., medical images), to assess reader performance with and without AI assistance. This device is a therapeutic electrical stimulator, not a diagnostic imaging device.

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

Not Applicable. This is not a software algorithm device in the context of AI/ML or diagnostic image analysis. Its performance is inherent to its electromechanical design and functionality, which is evaluated through non-clinical bench testing for compliance with standards.

7. The Type of Ground Truth Used

The "ground truth" here is the established engineering specifications and performance values defined by international consensus standards for medical electrical equipment (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-10) and FDA regulations (21 CFR 898). Compliance with these standards indicates safe and effective performance.

8. The Sample Size for the Training Set

Not Applicable. There is no "training set" in the context of machine learning for this device. The device's design and operating parameters are fixed.

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

Not Applicable. As there is no training set, there is no ground truth to establish for it. The "ground truth" for the device's design and performance is based on established engineering principles and regulatory standards for safety and electrical characteristics.

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To be used for temporary relief of pain associated with sore and aching muscles in the shoulder, waist, back, upper extremities (arm), and lower extremities (leg) due to strain from exercise or normal household work activities.

It is intended to be used to stimulate healthy muscles in order to improve and facilitate muscle performance.

The subject device is a Transcutaneous Electrical Nerve Stimulator (TENS) and Powered Muscle Stimulator (PMS), intended for the over-the-counter use to temporarily relieve pain and stimulate muscle in different body areas. The double-channel subject device, which is compact, portable, and microprocessor-controlled, delivers a gentle electrical pulse through the connecting wires and electrode pads to the user's skin for pain relief and muscle stimulation. The electrode pad used consists of gel, carbon film, cloth backing, and electrode connector, which is 510(k)-cleared and biocompatible. According to the need of users, the pulse intensity can be adjustable on the front control panel of the device.

Here's a breakdown of the acceptance criteria and the study information based on the provided document. It's important to note that this document is a 510(k) summary for a medical device and not a clinical study report for an AI device. Therefore, many of the requested fields related to AI, human readers, and ground truth establishment from a clinical perspective will indicate "Not Applicable" or "Not Provided," as they are not relevant to this type of submission.

Device Name: IQ Technologies (Transcutaneous Electrical Nerve Stimulator (TENS) and Powered Muscle Stimulator (PMS))
510(k) Number: K131290

1. Table of Acceptance Criteria and the Reported Device Performance

This document primarily focuses on demonstrating substantial equivalence to predicate devices, rather than setting distinct "acceptance criteria" with specific performance metrics in the way one might for an AI diagnostic algorithm. The acceptance is based on meeting the same safety and effectiveness standards, functional characteristics, and intended use as the predicates, verified through non-clinical testing and comparison of specifications.

Study Information:

This document is a 510(k) Premarket Notification based on non-clinical testing for substantial equivalence to legally marketed predicate devices. It does not describe a clinical study in the traditional sense of evaluating device effectiveness on patients or evaluating an AI algorithm's performance.

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

   • Sample Size: Not applicable. The "test set" here refers to the actual subject device undergoing engineering and electrical testing, not a dataset of patient cases.
   • Data Provenance: Not applicable. The data comes from direct measurements and engineering tests of the device itself.

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

   • Not applicable. Ground truth, in the context of an AI device often referring to clinical diagnosis, is not established for this type of non-clinical engineering and electrical performance testing. Compliance with standards and comparison to predicate device specifications are the "ground truth."

4. Adjudication method for the test set:

   • Not applicable. Electrical and mechanical specifications are objectively measured and compared, not subject to 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 a Transcutaneous Electrical Nerve Stimulator (TENS) and Powered Muscle Stimulator (PMS), not an AI-powered diagnostic tool. No human reader involvement in performance evaluation.

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

   • Partially applicable, but in a different context. The device's electrical and mechanical performance was evaluated in isolation (standalone) during non-clinical testing. It's a hardware device, not an algorithm.

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

   • Ground Truth: Compliance with established industry electrical and safety standards (IEC 60601 series) and direct comparison to the physical and functional specifications of legally marketed predicate devices.

8. The sample size for the training set:

   • Not applicable. This device is not an AI algorithm that requires a training set.

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

   • Not applicable. This device is not an AI algorithm that requires a training set.

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