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

• Neck Pad is used in back of neck.
• Meridian Pad is used in shoulder, waist, back, and arm.

This instrument is a new generation of household multifunctional device based on physics, modern microelectronics and clinical practices, it uses low frequency electrotherapy, and circular traction vibration to temporarily alleviate the pain associated with sore and aching muscles in the shoulder, waist, back of neck, back, arm, and leg. The Neck Pad is used in for back of neck and it accord with human body cervical physiological curvature of streamlined ring design accord with human body cervical physiological curvature of streamlined ring design. The Meridian Pad is used in shoulder, waist, back, and arm. The device has one operation modes which has 2 modes and 50 output Intensity Level, so the device can give certain electrical pulse through 2 pairs of electrode pads or the Neck Pad on the skin to help users to enjoy body massage and sole massage.

The remote control of this device is user-friendly controlled because it has the operating elements of ON/OFF knob, left or right button and increase or decrease button.

The device is equipped with accessories of electrode pads and an electrode wire is used to connect the pads to the main unit.

The LCD display screen can show selected mode, output intensity of body and/or sole, and time remaining of an application mode.

The device can be successfully opened only when switch button of the remote control and Neck Pad turned on at the same time.

The remote control is the only controller to select the pulse intensity and adjust the treatment time.

The provided text is a 510(k) Summary for a medical device (Neck Care Therapy, Model: SYK-509B) and does not contain a study that proves the device meets acceptance criteria in the manner described by your request (e.g., a clinical trial with a test set, ground truth established by experts, MRMC studies, or standalone performance evaluation).

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Health Expert Electronic Stimulator, K133929) primarily through bench testing for safety and performance specifications, and a comparison of technical characteristics and intended use.

Here's an analysis based on the information provided, highlighting what is and is not present:

Key Takeaways from the document:

• This device is a Transcutaneous Electrical Nerve Stimulator (TENS) for pain relief, intended for Over-The-Counter Use.
• The primary method of demonstrating equivalence is through engineering bench tests of electrical safety, EMC, biocompatibility, usability, software verification, and waveform output.
• There is no mention of a clinical study involving human subjects or expert readers to evaluate the device's therapeutic effectiveness for pain relief, nor is there a direct assessment of its performance against a predefined "acceptance criteria" for clinical outcomes. The "acceptance criteria" in this context are primarily related to meeting safety standards and having comparable technical specifications to the predicate device.

Detailed Breakdown based on your Request (with notations on missing information):

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set: Not applicable in the context of a clinical performance study. The "test set" here refers to samples of the device undergoing engineering and bench testing. The document does not specify the number of units tested for each engineering test.
• Data Provenance: The tests were conducted by the manufacturer, Shenzhen OSTO Technology Co., Ltd., and/or their contracted labs as part of the 510(k) submission process for market clearance. This is not clinical data provenance (e.g., country of origin, retrospective/prospective).

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

• Not applicable. Ground truth as typically understood in AI/clinical studies (e.g., diagnostic labels) was not established. The "ground truth" here is compliance with engineering standards and performance specifications, verified by testing against established international and FDA guidelines.

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

• Not applicable. There was no clinical adjudication panel or similar process described. Compliance was assessed against technical standards.

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 comparative effectiveness study was not done. This device is a direct-to-consumer TENS unit, not an AI-assisted diagnostic or therapeutic tool that would involve human "readers" or image interpretation.

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

• Not applicable in the AI context. The device is a standalone TENS unit. Its "standalone performance" was evaluated through the various engineering and bench tests for safety and electrical characteristics.

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

• The "ground truth" here is the technical specifications and safety standards defined by international standards (IEC, ISO) and FDA guidance for TENS devices. The device's performance was compared against these established technical benchmarks and the specifications of an already cleared predicate device. There is no clinical "ground truth" (e.g., pain reduction measured by a clinical scale, confirmed by expert consensus, or pathology) indicated in this submission.

8. The sample size for the training set:

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

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

• Not applicable, as there is no training set for an AI/ML algorithm.

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