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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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