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The Nd: YAG Laser Therapy System is indicated for the treatment of: benign cutaneous lesions, such as Warts, Scars, Striae and Psoriasis; benign pigmented lesions, such as Lentigines, Nevus, and Birthmark; and the removal of black or blue tattoos.

The Nd: YAG Laser Therapy System (Model: QN-1) is laser system which delivers laser at a wavelength 1064nm or 532nm and the pulse mode is single pulse.

In laser handpiece, there is one optical cavity containing the Nd:YAG crystal. The laser beam is directed to the treatment zone. When the laser beam contacts human tissue, the energy in the beam is absorbed, resulting in a very rapidly, highly localized temperature increase to the target tissue. The instantaneous temperature increase (thermal effect) causes the cells change of target tissue to achieve laser treatment effect.

The provided FDA 510(k) clearance letter for the Nd: YAG Laser Therapy System (QN-1) does not contain any information about acceptance criteria or a study proving that the device meets those criteria, specifically concerning AI/ML performance.

This document describes a traditional medical device (a laser therapy system) and its substantial equivalence to a predicate device based on non-clinical performance and safety standards. There is no mention of an AI/ML component or any software functionality that would require an AI/ML performance study as described in your prompt.

Therefore, I cannot provide the requested information. The document focuses on:

• Device Type: Nd: YAG Laser Therapy System (QN-1), a physical laser device.
• Regulatory Path: 510(k) pathway, demonstrating substantial equivalence to a predicate laser device (K232716).
• Testing: Non-clinical bench tests confirming compliance with electrical safety, EMC, laser safety, and biocompatibility standards.
• Clinical Studies: Explicitly states "No clinical study is included in this submission."
• Ground Truth: Not applicable in the context of this device's non-clinical submission.

To answer your prompt, an AI/ML medical device submission would typically include information on:

1. A table of acceptance criteria and the reported device performance: This would list specific metrics (e.g., Sensitivity, Specificity, AUC, F1-score) and the required numerical thresholds for device acceptance, along with the actual performance achieved in the study.
2. Sample sized used for the test set and the data provenance: Details on the number of cases (e.g., images, patient records) in the test set, country of origin, and whether the data was collected retrospectively or prospectively.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Information on how many medical professionals (e.g., radiologists, pathologists) annotated or reviewed the data to establish the definitive diagnosis, and their experience levels.
4. Adjudication method for the test set: How disagreements among experts were resolved (e.g., majority vote, senior expert arbitration).
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Whether human readers' performance with and without AI assistance was evaluated, and the measured improvement.
6. If a standalone performance (i.e. algorithm only without human-in-the loop performance) was done: The algorithm's performance without any human interaction.
7. The type of ground truth used: Whether the ground truth was based on expert consensus, pathological confirmation, long-term patient outcomes, etc.
8. The sample size for the training set: The number of cases used to train the AI model.
9. How the ground truth for the training set was established: The methodology for obtaining the labels used during the AI model's training phase.

Since the provided document does not pertain to an AI/ML medical device, none of the above questions can be answered based on the input.

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1060nm laser body slimming machine is intended for non-invasive lipolysis of the abdomen, flanks, back, and thighs in individuals with a Body Mass Index (BMI) of 30 or less. The device is intended to affect the appearance of visible fat bulges in the abdomen, flank, back, and thighs.

The 1060nm laser body slimming machine is an ultra-thermal laser fat decomposition system that uses the latest technology for non-invasive body shaping. It uses 1060mm wavelength laser penetration to target adipose tissue, selectively heats fat cells, and reduces the number of fat cells in the area through blood and lymph metabolism to achieve shaping the purpose of body contouring. It is a new generation of safe and effective way to lose weight.

The provided text is a 510(k) Summary for the "1060nm laser body slimming machine" (Model: RZ-01). This document assesses the substantial equivalence of a new medical device to a legally marketed predicate device.

It's important to understand that a 510(k) summary for a substantial equivalence determination often does not include detailed clinical study results, particularly regarding acceptance criteria for device performance in terms of patient outcomes or AI model accuracy. Instead, it focuses on demonstrating that the new device is as safe and effective as a predicate device, often relying on non-clinical tests (electrical safety, EMC, laser safety, etc.) and comparisons of technical specifications and intended use.

In this specific document, there is no information about acceptance criteria or a study proving the device meets performance criteria in the context of an AI/algorithm-driven device meeting specific accuracy metrics. The device in question is a laser body slimming machine, not an AI diagnostic or assistive tool.

Therefore, I cannot provide the requested information for an AI/algorithm-based device's performance study based on the provided text. The document states:

• "No clinical study is included in this submission." (Page 7)
• The comparison is based on technical specifications (laser type, wavelength, irradiance, etc.) and adherence to international safety standards (IEC, ISO).

If the request were about the safety and technical performance of this laser device, the "acceptance criteria" would relate to its compliance with the listed IEC and ISO standards, and the "study" would be the non-clinical tests conducted to prove this compliance. However, these are not the types of performance metrics or studies typically associated with AI/algorithm validation (e.g., accuracy, sensitivity, specificity, MRMC studies, ground truth establishment methods).

Therefore, I must state that the provided text does not contain the information requested for an AI/algorithm-driven device, as the device described is a physical laser machine, and the submission explicitly states no clinical study was included.

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Body Contouring Machine can be used to:

• Improvement of abdominal tone, strengthening of the abdominal muscles, development of firmer abdomen.
• Strengthening, Toning and Firming of buttocks, thighs and calves.
• Improvement of muscle tone and firmness, for strengthening muscles in arms.

Body Contouring Machine is a non-invasive treatment device. The device generates an electromagnetic field that interacts with human tissue. Body Contouring Machine is equipped with four handles, two each for ZH-01 and ZH-03, which can treat different parts of the same time. The device is equipped with a 15.6-inch true-color touch screen and provides two operating modes, intelligent and professional, to meet the different needs of users.
The Body Contouring Machine includes seven models in this submission, CS2,CS3,CS5,CS7, CS8,CS11, and CS13, all seven models have same principle, software, operation etc., only differences are appearance.

The provided FDA 510(k) summary (K232181) for the "Body Contouring Machine" (Models: CS2, CS3, CS5, CS7, CS8, CS11, CS13) does not include specific acceptance criteria or a study proving that the device meets such criteria in terms of clinical effectiveness. This omission is explicitly stated with "No clinical study is included in this submission."

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (BTL 799-2L, K190456) through non-clinical testing and comparison of technical specifications and indications for use.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not specify quantitative clinical performance acceptance criteria (e.g., minimum percentage improvement in muscle tone, specific reduction in abdominal circumference). The "performance" demonstrated is primarily through compliance with electrical safety, EMC, and other non-clinical standards, and by showing that its technical specifications are comparable to the predicate device.

• IEC 60601-1:2012
• IEC 60601-1-2:2014+A1:2020
• IEC 60601-2-10:2012/AMD2:2023
• IEC 62304:2015
• ISO 14971:2019
• ISO 10993-1:2018
• ISO 10993-5:2009
• ISO 10993-10:2010
• Magnetic density test results supported substantial equivalence. |
  | Technical Equivalence to Predicate | Parameters, principles of action, safety features, and indications for use should be substantially equivalent to the predicate device. | Demonstrated Substantial Equivalence:
• Same product code (NGX), regulation number (21 CFR 890.5850), regulatory class (Class II), and clinical use (Prescription use).
• Identical Indications for Use (abdominal tone, muscle strengthening, toning, firming of buttocks/thighs/calves, muscle tone/firmness in arms).
• Similar Principle of Action (initiating action potential of nerves results in muscle contraction).
• Similar electrical protection, user interface, firmware control, type of energy (Magnetic field).
• Output parameters (Magnetic Field Intensity, Pulse Repetition Rate, Pulse Duration, Therapy Time) are within comparable ranges to the predicate device, with some minor differences noted (e.g., the subject device having 4 outputs vs. 2 for the predicate, and slightly different ranges for some magnetic field intensities and pulse durations, which the submission states have "no significant influence on safety or effectiveness"). |

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size for Test Set: Not applicable. No clinical testing with a human test set was performed or submitted. The testing referenced is non-clinical (e.g., electrical safety, EMC, biocompatibility).
• Data Provenance: Not applicable for clinical data. For non-clinical testing, the data would originate from laboratory tests conducted by the manufacturer or their contracted testing facilities, likely in China (where the sponsor is located).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:

Not applicable. No clinical study or human participant test set was used for this submission to establish ground truth based on expert review.

4. Adjudication Method for the Test Set:

Not applicable. No clinical study or human participant test set was used requiring an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Human Readers Improvement with AI vs. Without AI Assistance:

Not applicable. This device is a "Body Contouring Machine" (a physical therapeutic device), not an AI-assisted diagnostic or interpretative software. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

Not applicable. The device is a physical medical device, not an algorithm or software requiring standalone performance evaluation in the context of diagnostic or interpretive tasks.

7. The Type of Ground Truth Used:

Not applicable in the clinical sense. The "ground truth" for this submission is based on adherence to recognized national and international standards for medical electrical equipment, biocompatibility, and risk management, as well as the substantial equivalence of its technical specifications and intended use to a legally marketed predicate device.

8. The Sample Size for the Training Set:

Not applicable. This device is a hardware-based medical device, not an AI/ML algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established:

Not applicable. As above, no training set was used.

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