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The LED Light Therapy Mask (Model: FCM902, FCM905, FCM906, FCM908, 11-001-RBMASK, FCM910) is an Over-the-Counter (OTC) device intended for treatment of wrinkles and mild to moderate inflammatory acne.

FCM902, FCM905, FCM906, FCM908:
a.Red light: Treatment of full-face wrinkles.
b.Blue+Infrared light: Treatment of mild to moderate inflammatory acne.
c.Yellow+Infrared light: Treatment of full-face wrinkles.

11-001-RBMASK:
a.Red+Infrared light: Treatment of full-face wrinkles.
b.Blue light: Treatment of mild to moderate inflammatory acne.

FCM910:
a.Red+Infrared light: Treatment of full-face wrinkles.
b.Blue light: Treatment of mild to moderate inflammatory acne.
c.Yellow+Infrared light: Treatment of full-face wrinkles.

The LED Light Therapy Mask (FCM902, FCM905, FCM906, FCM908, 11-001-RBMASK, FCM910) adopts light emitting diodes (LED) in the red (630nm ±5nm) , infrared (880nm±5nm) and blue (415±5nm) spectrum to irradiate on the face to realize its therapeutic effect.

For FCM902, FCM905, FCM906, FCM908 and FCM910, it also contain yellow (590±5nm) spectrum and green (520±5nm) spectrum.

The LED Light Therapy Mask adopts the form of a mask that contains LEDs on the inner surface of the main unit. A controller is connected to the main unit to control the device, such as turn on/off the device, switch mode (LED color). To use the device, user should place the mask over the face and use the controller to operate. The device will automatically turn off after each treatment. To prevent irradiation of LED lights to eyes during the treatment, LED Light Therapy Mask has incorporated protective eye-shield which blocks light energy from LEDs.

a. Red light: Treatment of full-face wrinkles.
b. Blue+Infrared light: Treatment of mild to moderate inflammatory acne.
c. Yellow+Infrared light: Treatment of full-face wrinkles.
d. Green Light: light in wavelength 520nm(±5nm). Green light makes users feel like they are outside in a green world, which may make users relax, which has no medical therapeutic effect.
e. Red+Infrared light: Treatment of full-face wrinkles.
f. Blue light: Treatment of mild to moderate inflammatory acne.

The provided FDA 510(k) Clearance Letter concerns an LED Light Therapy Mask for treating wrinkles and mild to moderate inflammatory acne. However, this document is a clearance letter and a 510(k) summary, not a clinical study report. It primarily focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and non-clinical testing.

Therefore, the document does NOT contain the details required to answer many of the specific questions about acceptance criteria and the study that proves the device meets those criteria, particularly those related to clinical performance, human reader studies, or expert ground truth.

The information provided is mostly about device specifications, comparison to predicates, and compliance with non-clinical safety standards (electrical safety, biocompatibility, photobiological safety). It states that "Non-clinical testings have been conducted to verify that the LED Light Therapy Mask meets all design specifications which supports the conclusion that it's Substantially Equivalent (SE) to the predicate device."

Based on the provided text, I can only address what is explicitly mentioned or can be reasonably inferred. Most of the questions below would require a separate clinical study report, which is not part of this 510(k) summary.

Acceptance Criteria and Device Performance (Based only on the provided 510(k) Summary):

The acceptance criteria for this device, as inferred from the 510(k) summary, are primarily centered around Substantial Equivalence (SE) to legally marketed predicate devices for the specified indications for use, and compliance with relevant safety and performance standards for an OTC device. The "performance" reported is largely in terms of meeting these technical and safety standards, rather than clinical efficacy metrics from a new human study.

1. Table of Acceptance Criteria and Reported Device Performance

Regarding the study that proves the device meets the acceptance criteria:

Based solely on the provided 510(k) summary, the "study" proving the device meets acceptance criteria appears to be a non-clinical testing program focused on product safety and performance standards for substantial equivalence. There is no mention of a human clinical study, an AI component requiring a test set for diagnostic accuracy, or experts establishing ground truth in a clinical context within this document.

Therefore, I cannot provide answers for many of the following questions as the requested information is not present in the provided text.

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

• Not applicable / Not provided. The document describes non-clinical testing of the device itself (electrical, photobiological, biocompatibility, software V&V), not a clinical test set from patients.

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

• Not applicable / Not provided. There is no mention of a test set requiring expert-established ground truth for performance evaluation in this 510(k) summary. This typically applies to AI/CADe devices or clinical efficacy studies, neither of which are detailed here.

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

• Not applicable / Not provided. Since no clinical test set or expert ground truth process is described, an adjudication method is irrelevant.

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, not done / Not applicable. This device is an LED light therapy mask, not an AI-assisted diagnostic tool. An MRMC study is completely irrelevant to this type of device and its 510(k) clearance.

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

• Not applicable. There is no "algorithm only" performance study as this is a physical light therapy device, not a diagnostic algorithm.

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

• Not applicable / Not provided for clinical efficacy. For the non-clinical tests, the "ground truth" would be the specified parameters and limits of the IEC/ISO standards (e.g., maximum allowable leakage current, certified photobiological safety levels, biocompatibility thresholds). There is no mention of a clinical ground truth (e.g., for wrinkle reduction or acne treatment) from a study in this document.

8. The sample size for the training set:

• Not applicable / Not provided. This device is cleared based on substantial equivalence and compliance with non-clinical performance standards. It implies a known or existing mechanism of action (light therapy) rather than a newly developed AI algorithm that requires a training set of data.

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

• Not applicable / Not provided. As no training set for an algorithm is mentioned, the method for establishing its ground truth is also not applicable.

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The s-Clean Tapered II RBM Implant System is an endosseous dental implant is indicated for surgical placement in the upper and lower jaw arches, to provide a root form means for single or multiple-units prosthetic appliance attachment to restore a patient's chewing function. Implants can be placed with a conventional two stage surgical process with an option for transmucosal healing or they can be placed in a single stage surgical process for immediate loading. Immediate loading is restricted to the anterior mandible based on four splinted Interforaminal placed implants.

The s-Clean Tapered II RBM Implant System is a dental implant made of titanium metal (Titanium grade 4) intended to be surgically placed in the bone of the upper or lower jaw arches. This implant system has internal hex connection, 1.5° tapered body, bone level and submerged type that are similar to other commercial available products based on the intended use, technology used, the claims, the material composition employed and performance characteristics. The fixture has been treated with RBM (Resorbable Blasted media).

The s-Clean Tapered II RBM Implant System diameter and lengths are below:

• Diameter Ø 3.7 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• Diameter 0 4.1 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• Diameter Ø 4.3 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• -Diameter Ø 4.8 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm

The packaging has composed of fixture with cover screw. The fixtures are supplied sterile by gamma sterilization. The fixtures are provided as set-packing with the cover screw. The purpose of this submission is to add new fixtures.

The provided text describes a 510(k) premarket notification for a dental implant system. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving safety and effectiveness through extensive standalone studies and acceptance criteria for performance metrics.

Therefore, the information requested (acceptance criteria, specific study design for meeting these criteria, sample sizes, ground truth establishment, expert roles, MRMC studies, and standalone performance) is largely not applicable in the context of this 510(k) submission as it is presented.

Here's why and what information can be extracted:

• No specific acceptance criteria listed for device performance: The document does not define numerical performance targets (e.g., specific accuracy, sensitivity, specificity values) for the "s-Clean Tapered II RBM Implant System." Instead, it aims to demonstrate that its characteristics are "substantially equivalent" to predicate devices.
• No standalone study to "prove" device meets acceptance criteria: The submission relies on comparison to predicate devices and existing test data from those predicates.
• No sample sizes, data provenance, expert ground truth, adjudication, or MRMC studies for "device performance" in the AI sense: These concepts are typically relevant for AI/ML device submissions where classification, detection, or other diagnostic performance metrics are being evaluated. This document concerns a physical medical device (dental implant).

However, I can extract information related to the non-clinical testing that was performed to support substantial equivalence. While these are not performance metrics in the AI sense, they serve as the "proof" that the device is equivalent to its predicate.

Here's a summary of the relevant information from the document, tailored as much as possible to your request, but highlighting the differences in context:

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

As mentioned, there are no acceptance criteria for "performance" as one might expect for a diagnostic AI device. Instead, the "performance" demonstrated is substantial equivalence to predicate devices, supported by adherence to manufacturing standards and existing test data.

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

• Sample Size for Test Set: Not specified in terms of clinical subjects. The non-clinical tests (fatigue, sterilization, shelf-life) would have involved specific numbers of implant units or samples, but these are not disclosed in this summary. The submission references data from predicate devices, implying those predicate devices underwent testing.
• Data Provenance: Not explicitly stated as "country of origin for data." However, the device manufacturer (Dentis Co., Ltd.) is from South Korea. The predicate devices are also manufactured by Dentis Co., Ltd. The testing referenced aligns with FDA guidance documents, suggesting it would meet U.S. regulatory expectations. The type of data is non-clinical testing data rather than patient data (e.g., retrospective or prospective clinical data).

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 pertains to clinical ground truth, often for diagnostic devices. For a physical implant, "ground truth" is established by manufacturing specifications, material properties, and engineering standards. There is no mention of human experts establishing "ground truth" in this context; instead, the evaluation is based on engineering tests and comparison to established, legally marketed devices.

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

• Not Applicable: This is relevant for subjective assessments, particularly in clinical or imaging studies where multiple readers' opinions need to be reconciled. For a physical device undergoing non-clinical engineering tests (like fatigue or sterilization), the "adjudication" is based on objective measurements against predetermined 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

• Not Applicable: MRMC studies are specific to evaluating diagnostic performance, especially for AI-assisted systems, and typically involve human readers interpreting cases. This submission is for a physical dental implant and does not involve AI or human interpretation of medical images/data.

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

• Not Applicable: This refers to the performance of an AI algorithm. This device is a physical dental implant.

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

• For Non-Clinical Testing: The "ground truth" for non-clinical tests like fatigue, sterilization, and shelf-life is defined by established engineering standards, material specifications, and regulatory guidance documents. For instance, a fatigue test determines if the implant can withstand a certain number of stress cycles without fracture, as dictated by standards like ASTM or ISO. The "truth" is the device's physical response measured against a quantitative standard, not expert consensus on a diagnosis.
• For Substantial Equivalence: The ultimate "ground truth" for this 510(k) submission is that the device is as safe and effective as a legally marketed predicate device. This is established through the detailed comparison of design, materials, indications for use, and existing testing data.

8. The sample size for the training set

• Not Applicable: This refers to training data for AI/ML algorithms. This submission is for a physical device and involves no "training set."

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

• Not Applicable: As above, no training set or AI involved.

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SM-Extra Wide(RBM) Implant Fixture is intended to be surgically placed in the maxillary or mandivular molar areas for the purpose of providing prosthetic support for dental restoration (Crown, Bridges, and overdentures) in partially or fully edentulous individuals. These Fixtures can be used where smaller implants have failed.

SM-Extra Wide(RBM) Implant System consists of SM-Extra Wide(RBM) fixtures, abutments, prosthetics and surgical instruments.

SM-Extra Wide(RBM) Implant Fixtures are made of commercial pure titanium, grade 4 which have a sand-blasted, RBM(Resorbable Blast Media) treated surface. These fixtures are the onestage implant and two-stage implant and surgically inserted in the maxillary or mandibular molar areas or where smaller implants have failed.

These fixtures are the integrated system of endosseous dental implants which designed to Provide prosthetics support for dental restoration (Crown, Bridges, and overdentures) in partially or fully edentulous individuals.

The screw, cemented and overdenture retained restoration, other superstructure and instruments for prosthetics that used when the SM-Extra Wide implants is surged are same with each standard type of DIO SM Implant System.

This submission, K080128, for the SM-Extra Wide(RBM) Implant System, does not describe an AI/ML powered device. Instead, it is a traditional 510(k) submission for a dental implant system. As such, the information you've requested regarding acceptance criteria and studies proving the device meets those criteria, particularly with reference to AI/ML specific performance metrics, is not present in the provided text.

The submission focuses on establishing substantial equivalence to a predicate device (Rescue Internal Dental Implant System, K063216) based on technological characteristics and intended use.

Here's an analysis of the provided text in relation to your questions, highlighting why most AI/ML-specific questions are not applicable:

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

• Acceptance Criteria: The document implies acceptance criteria are based on device functionality and conformance to design input requirements, as stated in section 8: "Laboratory testing was conducted to determine device functionality and conformance to design input requirements." However, specific numerical acceptance criteria (e.g., success rates, torque values, fatigue limits) for these "design input requirements" are not explicitly listed in the provided text.
• Reported Device Performance: The primary "performance" reported is the demonstration of substantial equivalence to the predicate device. This is shown through a direct comparison of technological characteristics in Section 12. No quantitative performance data from clinical trials or specific laboratory tests (beyond the general statement above) are provided or summarized.

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

• This information is not applicable as this is a physical medical device (dental implant) and not an AI/ML algorithm or software that operates on data. The "testing" mentioned is laboratory testing of the physical implant's functionality, not a test set of data.

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)

• This is not applicable. Ground truth, in the context of expert consensus, is relevant for evaluating the performance of diagnostic or prognostic AI/ML models. For a physical dental implant, "ground truth" would be established through established engineering and biocompatibility standards, not expert adjudication of a test set.

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

• This is not applicable. Adjudication methods are used in studies involving human interpretation or consensus for data labeling/ground truth in AI/ML performance evaluation.

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

• This is not applicable. MRMC studies are specific to evaluating diagnostic systems, particularly imaging devices or AI tools, and their impact on human reader performance. This submission is for a physical implant.

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

• This is not applicable. This refers to the standalone performance of an AI/ML algorithm.

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

• For the performance of this physical implant, the "ground truth" implicitly relies on engineering standards, material science properties, biocompatibility testing (which may involve in-vitro or animal studies, though not detailed here), and successful historical clinical use of physically similar predicate devices. No explicit "ground truth" of the types listed (expert consensus, pathology, outcomes data) for a data-driven evaluation is mentioned.

8. The sample size for the training set

• This is not applicable. There is no AI/ML algorithm being "trained" in this submission.

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

• This is not applicable. There is no AI/ML algorithm being "trained" in this submission.

In summary, the K080128 submission is a standard 510(k) for a physical medical device, demonstrating substantial equivalence to a predicate. The questions posed are primarily relevant to AI/ML powered devices, which this product is not.

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The RBM is intended for use as a suture retention device to facilitate percutaneous or endoscopic soft tissue repair. The indications for the RBM are for use as a suture retention device to facilitate percuraneous or endoscopic soft tissue procedures such as shoulder stabilization (Bankart Repar), rotator cuff repair, meniscal repair, and gastrostomy.

The RBM is a suture retention device manufactured from polyester suture, poly(L-lactide) bar, stainless steel needle and a plastic handle.

The provided text is a 510(k) summary for the RBM suture retention device. It describes the device, its intended use, and compares it to a predicate device (MR-III). However, it does not contain any information about acceptance criteria or a study proving the device meets those criteria.

Therefore, I cannot provide the requested information. The document focuses on regulatory submission for substantial equivalence based on technological characteristics and intended use alignment with a predicate device, rather than performance testing against specific acceptance criteria.

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