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Applied BioPhotonics® Phototherapy System ABPT1003 is intended to provide phototherapeutic light to the body. The device emits:

• Red and infrared light to provide topical heating for the purpose of elevating tissue temperature; for the temporary relief of minor muscle and joint pain, arthritis, sprains, strains, and muscle spasm, as well as back, neck and shoulder pain; relieving stiffness; promoting the relaxation of muscle tissue; and to temporarily increase local blood circulation where applied.

The Applied BioPhotonics® Phototherapy System ABPT1003 is a light therapy device using specific wavelengths of polychromatic energy produced by super-luminous light emitting diodes (LEDs) to treat a variety of skin and body conditions.
The device can be described as a Class II Low Level Light treatment process employing the application of light and heat, which penetrates the skin surface to the underlying tissues, triggering normal cellular functions. This technology is commonly referred to as photobiostimulation, light emitting diode therapy (LEDT), LLLT, or LED's. The application of LED's to tissue is non-invasive.
Using patent pending and proprietary techniques and computational processes, the Applied BioPhotonics® Phototherapy System ABPT1003 is composed of:

• Proprietary hardware (i.e. ABLM1002 LightMachine)
• LightOS software (running in the LightMachine)
• LightPad sets (ABLP103) comprising flexible, aseptic, polymeric LED pads
• Cables (for connecting LightPads and LightMachines)
  The IR and red spectrum emitted from LEDs in the ABLP103 LightPad sets is intended to provide topical heating for the purpose of elevating tissue temperature; for the temporary relief of minor muscle and joint pain, arthritis, sprains, strains, and muscle spasm, as well as back, neck and shoulder pain; relieving stiffness; promoting the relaxation of muscle tissue; and to temporarily increase local blood circulation where applied.
  The LightMachine control panel displays to the operator what treatment is being performed and provides the user with a choice of driving one or two LightPad sets with any chosen treatment protocol.
  The software component of the device controls the user's selection of specific treatment protocols on the LightMachine's control panel. The treatment may be set manually by entering LED-operating conditions (i.e. wavelength, duration, and pulse frequency) or by selecting preset treatment protocols. The software is revision-controlled and can be upgraded by the manufacturer.
  This is a prescription use only device. The labeling, instructions and user operations are designed for health care professionals.

This document is a 510(k) Summary for the Applied BioPhotonics® Phototherapy System ABPT1003. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than presenting a standalone study proving the device meets specific performance criteria. Therefore, most of the requested information regarding acceptance criteria, study design, and ground truth establishment is not explicitly detailed in this type of submission.

Based on the provided text, here's what can be extracted and what is not available:

Acceptance Criteria and Reported Device Performance

The document states that "All the test results demonstrate that Applied BioPhotonics Phototherapy System ABPT1003 meets the requirements of its predefined acceptance criteria and intended uses." However, the specific acceptance criteria are not explicitly listed or quantified in the provided text.

The "reported device performance" is essentially that the device passed various safety and compatibility tests, and is substantially equivalent to predicate devices. No quantifiable performance metrics for "efficacy" (e.g., specific pain reduction percentages, increase in blood circulation metrics) are provided from a clinical study for this device.

Additional Requested Information:

1. Sample sizes used for the test set and the data provenance:

   • Test set sample size: Not applicable/not stated. The non-clinical testing appears to refer to engineering verification and validation testing of the device itself (e.g., EMC, electrical safety, software V&V) rather than a clinical "test set" of patients.
   • Data provenance: The document mentions "All laboratory tests and measurements were performed by an independent test lab certified to make such assessments." The country of origin for this testing is not specified, but the device submitter is from Hong Kong, China SAR. The testing is non-clinical.

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

   • Not applicable. This was primarily non-clinical engineering and software testing. Ground truth in the context of clinical expert review is not relevant here.

3. Adjudication method for the test set:

   • Not applicable as no clinical test set requiring expert adjudication is described.

4. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs. without AI assistance:

   • No MRMC clinical comparative effectiveness study was done. The device is a phototherapy system, not an AI diagnostic tool that assists human readers.

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

   • While software verification and validation were performed, this relates to the device's operational software and controls, not an AI algorithm performing a specific diagnostic or clinical task. The "standalone performance" of the device is demonstrated by its compliance with safety and technical standards as an independent medical device.

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

   • For the non-clinical testing, the "ground truth" would be established by the specifications and standards the device was designed to meet (e.g., specific voltage tolerances, current levels, electromagnetic emissions limits, software functional requirements). It's based on engineering specifications and regulatory standards. No clinical ground truth (like pathology or outcomes data) was used or required for this type of submission.

7. The sample size for the training set:

   • Not applicable. This device does not incorporate machine learning or AI that requires a "training set" in the conventional sense of data-driven model training.

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

   • Not applicable, as there was no training set for an AI algorithm.

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