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

The TENS is an electrical nerve stimulator indicated for use for pain relief by applying an electrical current to electrodes on a patient's skin to treat pain.

The TENS consists of LCD, Control Key, Switch, Battery, Output jack and USB port, its accessories includes electrode, electrode cable, USB wire and Battery charger. Only the electrode pads cleared in submission, K092546, are to be used with this device

The proposed device has six models: SM9066, SM9088, SM9090, SM9098, SM9128 and SM9198. The six models have the same design principle and functional components, including battery, LCD, Control Key, Switch, channel number and USB port and accessories. The difference between the six models specifically expressed in the battery specification, LCD dimension, the position of Control key, Switch, and USB port on the proposed device, PCB(Printed Circuit Board) dimension and the number of Output jack numbers.

This document describes a 510(k) submission for Transcutaneous Electrical Nerve Stimulator (TENS) devices. It focuses on demonstrating substantial equivalence to a predicate device, rather than a standalone study proving a device meets specific acceptance criteria based on clinical outcomes or accuracy metrics for a diagnostic device.

Therefore, much of the requested information regarding acceptance criteria, reported performance, sample sizes for test/training sets, expert ground truth, adjudication methods, and MRMC studies is not directly applicable or available in this type of regulatory submission. This document is a premarket notification (510(k)), which aims to demonstrate that a new device is as safe and effective as a legally marketed predicate device, not necessarily to prove efficacy through a clinical trial with acceptance criteria for performance.

However, I can extract information related to the device's technical specifications and the testing done to support its substantial equivalence.

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

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

• Acceptance Criteria (implicit from comparison to predicate and standards): The implicit acceptance criteria are that the device's technological characteristics are substantially equivalent to the predicate device and that it complies with relevant electrical safety and EMC standards. Specifically, for electrical output parameters, the proposed device's values should be covered by or deemed substantially equivalent to the predicate's values. For current/frequency, they must also meet IEC 60601-2-10 limits.
• Reported Device Performance:

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

• Test Set Sample Size:
  • Bench Testing: Not specified explicitly for each test. The tests were run on the "proposed device" (TENS Models SM9066, SM9088, SM9090, SM9098, SM9128 and SM9198).
  • Biocompatibility: The electrode pads were cleared under K092546. The sample size for those biocompatibility tests is not detailed in this document.
  • Usability Study: Conducted with "a variety of 'patients'" in America. The specific number of participants is not provided.
• Data Provenance:
  • Bench Testing: Performed by the manufacturer (presumably in Hong Kong/China, given the sponsor location) to verify design specifications and compliance with international standards.
  • Biocompatibility: Refers to results from a prior 510(k) submission (K092546) for the electrode pads.
  • Usability Study: Conducted in "America" for the US market. Presumed to be prospective for the purpose of this submission.

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 submission relies on technical comparisons to a predicate device and compliance with recognized standards. There is no "ground truth" to be established by experts in the sense of diagnostic accuracy or clinical outcomes being assessed by human readers. The "ground truth" here is the established safety and effectiveness of the predicate device and the requirements of the standards.

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

• Not applicable. See point 3.

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 TENS unit for pain relief, not a diagnostic AI system with human-in-the-loop performance. Therefore, no MRMC study was conducted or is relevant.

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

• Partially applicable, but not for an "algorithm" in the AI sense. The bench tests (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-10) are "standalone" in that they assess the device's technical performance against engineering specifications and international standards, independently of a human user. However, this is not an 'algorithm-only' performance study as understood in AI/diagnostic device contexts.

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

• For the technical and safety aspects, the "ground truth" is adherence to international electrical safety and performance standards (IEC 60601 series) and the demonstrated safety and effectiveness of the legally marketed predicate device (K102598).
• For biocompatibility, the ground truth is established by the results of standardized ISO 10993 cytotoxicity, sensitization, and irritation tests.
• For usability, the "ground truth" is measured by whether "a variety of 'patients'" understood the labeling sufficiently for safe and proper use.

8. The sample size for the training set:

• Not applicable. This device does not employ machine learning or AI algorithms that require a "training set."

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

• Not applicable. See point 8.

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