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510(k) Data Aggregation
(148 days)
The LightStim Elipsa is a LED light therapy device which uses specific wavelengths of light emitting diodes (LEDs). It is intended to emit energy in the red and infrared region of the light spectrum to provide treatment for full face wrinkles. The blue and red light spectrum is intentent of mild to moderate inflammatory acne.
The LightStim Elipsa is an over-the-counter light emitting diode (LED) device that emits energy for use in dermatology for the treatment of acne and wrinkles. The device uses four types of LEDs for Wrinkles: 612nm amber, 645nm red, 655nm red, and 850nm infrared and two types of LEDs for Acne: 410nm and 645nm. The treatment time is controlled by the user. There are no user settings or adjustments required. The LightStim Elipsa system components include the device containing the LED module, power supply, goggles, and travel case. The LightStim Elipsa does not contain any user serviceable components. The device is sold as Over-the-counter (OTC)
The provided text describes a 510(k) premarket notification for the LightStim Elipsa device, an over-the-counter LED light therapy device for treating full-face wrinkles and mild to moderate inflammatory acne.
Based on the provided information, the document does not contain acceptance criteria or a study that directly proves the device meets specific performance criteria related to clinical efficacy (e.g., reduction in wrinkles or acne). Instead, the performance testing focuses on safety, electrical compatibility, software validation, and usability for regulatory clearance.
Here's a breakdown of the available information and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
As mentioned, there are no reported clinical performance acceptance criteria (e.g., percentage reduction in wrinkles, or acne lesion count reduction) or corresponding clinical efficacy results in this document. The "Performance Testing" section describes compliance with various safety and electrical standards.
| Acceptance Criteria Category | Specific Criteria (from document) | Reported Device Performance (from document) |
|---|---|---|
| Electrical Safety | Conformance to AAMI/ANSI ES60601-1:2005(R) 2012 and A1:2012 4th Edition: Medical Electrical Equipment - Part 1: General requirements for basic safety and essential performance. | Device was tested for conformance and passed. |
| Electromagnetic Compatibility | Conformance to IEC 60601-1-2:2014 4th Edition Medical Electrical Equipment – Part 1-2: General Requirements for Safety and Essential Performance- Collateral standard: Electromagnetic Compatibility-Requirements and tests. | Device was tested for conformance and passed. |
| Usability/Human Factors | Conformance to IEC 60601-1-6:2010, IEC 60601-1-11:2015, IEC 60601-2-83:2019 including gap analysis demonstrating conformance to IEC 60601-2-57:2011. | Device was tested for conformance and passed. |
| Label Comprehension | Evaluation and measurement of labeling comprehension, device usability, self-selection component, and training effectiveness by "intended users" of the Elipsa device. | "The results of this testing on the final version of the labeling and instruction plan showed that the instructions were effective and intended users were able to understand the labeling and apply this information to device use for the primary operating functions of the device." |
| Software Verification/Validation | Documentation as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software in Medical Devices," for a minor (A) level of concern (malfunction of software could not lead to patient injury). | "Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software in Medical Devices. The minor (A) level of concern was determined because malfunction of, or a latent design flaw in the software could not lead to a patient injurv [sic]." |
2. Sample size used for the test set and the data provenance
- For Usability/Label Comprehension Study: The document states "The sponsor conducted a Usability/Label Comprehension study to acquire data..." but does not specify the sample size of participants or the data provenance (e.g., country of origin, retrospective/prospective).
- For Clinical Efficacy: No clinical test set or efficacy data is presented in this document. The 510(k) submission relied on substantial equivalence to predicate devices, which means they are claiming the new device is as safe and effective as already legally marketed devices, rather than conducting new clinical trials for efficacy.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- For Usability/Label Comprehension Study: This type of study typically involves user feedback, not expert ground truth establishment for medical diagnosis. The document does not mention experts establishing ground truth for this study.
- For Clinical Efficacy: Not applicable, as no clinical efficacy test set or ground truth is described in this document.
4. Adjudication method for the test set
- Not applicable, as no clinical efficacy test set or adjudication process is described.
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 an LED light therapy device, not an AI-powered diagnostic or interpretive device that would involve human readers or AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This is a physical LED light therapy device, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- For Usability/Label Comprehension Study: The "ground truth" here would be the actual comprehension and successful use of the device by the study participants based on the instructions. This is assessed directly through observation and user feedback, not by expert consensus or pathology.
- For Clinical Efficacy: Not applicable, as no clinical efficacy ground truth is described in this document.
8. The sample size for the training set
- Not applicable. This document pertains to regulatory clearance for a physical device, not an AI/ML algorithm that requires a training set.
9. How the ground truth for the training set was established
- Not applicable. (See #8)
In summary, the provided document focuses on regulatory compliance through substantial equivalence to predicate devices and performance testing related to electrical safety, electromagnetic compatibility, software validation, and usability. It does not contain information about clinical efficacy studies, clinical acceptance criteria, or clinical performance data for wrinkle reduction or acne treatment beyond the general indications for use established by the predicates.
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(224 days)
The LightStim Professional LED Bed is an over-the-counter device intended to emit energy in the visible and IR spectrum intended to provide topical heating for the purpose of elevating tissue temperature for a temporary relief of minor muscle and joint pain and stiffness, minor arthritis pain or muscle spasm, the temporary increase in local blood circulation, and the temporary relaxation of muscles.
The LightStim Professional LED Bed is a device that is similar in design to the bottom half of a tanning bed. It is approximately 6.5 feet in length and 3 feet wide. It has 18,240 LEDs. There is an on/off switch that turns off after 30 minutes of use, and an AC to DC power supply.
This document is a 510(k) premarket notification for the LightStim Professional LED Bed. It focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than a de novo clinical study with specific acceptance criteria and detailed performance metrics as one might find for a novel, higher-risk device.
Therefore, the requested information, particularly regarding specific acceptance criteria, a standalone study demonstrating performance against those criteria, sample sizes for test and training sets, and expert-adjudicated ground truth, is not present in this document in the typical format for a clinical effectiveness study. The focus here is on demonstrating the new device performs similarly to existing, legally marketed devices.
However, based on the provided text, I can infer and extract some relevant points:
1. Table of Acceptance Criteria and Reported Device Performance
Strict "acceptance criteria" for a clinical outcome are not explicitly stated in this document as it's a substantial equivalence submission. Instead, the performance is demonstrated by showing similar characteristics and results to predicate devices, particularly regarding temperature elevation which is linked to the intended use for pain relief and circulation.
| Acceptance Criteria (Inferred from Predicate Equivalence) | Reported Device Performance (LightStim Professional LED Bed) |
|---|---|
| Output in milliwatts: 60mW cm$^2$ (matching predicates) | 60mW cm$^2$ (Matches predicates, procured from same manufacturer with exact same specifications) |
| Treatment Time: 5-30 minutes (matching predicates) | 5-30 minutes (Matches predicates) |
| Wavelengths (nm): 630nm, 660nm, 855nm, 940nm (matching predicates) | 630nm, 660nm, 855nm, 940nm (Matches predicates) |
| Skin Temperature Elevation: Within FDA guidelines for ILY category (implied by predicate success) | Fluctuation between 40-41.3 degrees Celsius during 30-minute test. ("almost identical to the readings of the predicate devices") |
2. Sample size used for the test set and the data provenance
The document mentions "The LightStim Professional LED Bed device was tested using the same skin temperature testing as all of the predicate devices. The participants skin temperature was measured..." This implies a test set was used, but the sample size is not specified. The data provenance is implied to be prospective for this specific device's temperature testing, conducted by the manufacturer (LED Intellectual Properties, LLC). Country of origin is not explicitly stated but the manufacturer is based in Irvine, California, USA.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This type of information is not applicable here. The "ground truth" for the temperature study is the direct measurement of skin temperature. It does not involve expert adjudication or interpretation as a diagnostic or prognostic AI algorithm would.
4. Adjudication method for the test set
Not applicable. The measurement is direct physical measurement (temperature), not subjective interpretation requiring 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
No, a MRMC comparative effectiveness study was not done. This device is not an AI diagnostic or assistive tool, but a therapeutic energy emission device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
A "standalone" performance test in the context of an algorithm was not done because this is not an algorithm. However, performance testing of the device itself (e.g., temperature output, electrical safety) was conducted. The temperature testing described ("participants skin temperature was measured...") represents a form of standalone performance measurement for the device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The "ground truth" for the skin temperature testing was direct physical measurement of skin temperature using a "Mastercool, Infrared Laser Thermometer". For the substantial equivalence claim, the "ground truth" for characteristics like output, wavelengths, treatment time, and safety/performance standards is comparison to the specifications and clearances of the predicate devices.
8. The sample size for the training set
Not applicable. This device is hardware and does not involve AI or machine learning 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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