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Wi-Fi body scale, model HS5 is indicated to measure body weight, estimate body fat, body water percentage, body muscle mass, bones mass, visceral fat rating and daily calorie intake (DCI) using BIA (bioelectrical impedance analysis). This product is for use by generally healthy adults,,who are not ill, feverish, have a chronic or acute disease, or a condition that affect the level of hydration such as pregnancy.

The patient steps on the scale device, where four electrodes are located. The patient must step on the electrodes with bare feet, with normal moisture. Through harmless current stimulation of 500 uA, at 50 kHz, the Wi-Fi body scale calculates the body fat percentage. This calculation is done via the Bioelectrical Impedance Method. The current is passed through the body and the impedance of the body determines the body fat. The calculation is based upon electrical impedance, height, weight, age, and gender. The calculation is performed via internal software, which uses the variables programmed in by the user. Wi-Fi body scale, model HS5 can be used with an iPod Touch, iPhone or iPad.

The provided text does not contain information about acceptance criteria or a study that specifically proves the device meets such criteria. The document is a 510(k) summary for a Wi-Fi body scale, focusing on its substantial equivalence to a predicate device and its intended use.

Here's what can be extracted based on your request, highlighting the missing information:

1. Table of acceptance criteria and reported device performance:

This information is not present in the provided text. The document states that "Clinical testing was used to validate the effectiveness and accuracy of the device. All test results were satisfactory," but it does not specify what those "satisfactory" results were in terms of acceptance criteria or performance metrics.

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

This information is not present in the provided text.

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

This information is not present in the provided text.

4. Adjudication method for the test set:

This information is not present in the provided text.

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

This information is not present in the provided text. The device is a "body analysis scale" and doesn't involve human readers interpreting medical images or data that would typically require an MRMC study.

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

The device description implies standalone performance as it "calculates the body fat percentage" via internal software. However, there is no separate study explicitly described as a "standalone" evaluation with specific performance metrics. The statement "Clinical testing was used to validate the effectiveness and accuracy of the device" might refer to this, but details are lacking.

7. The type of ground truth used:

This information is not explicitly stated. For a body fat scale using Bioelectrical Impedance Analysis (BIA), the "ground truth" for validation would typically be a more accurate body composition measurement method (e.g., DEXA, hydrostatic weighing). However, the document only broadly mentions "Clinical testing was used to validate the effectiveness and accuracy of the device."

8. The sample size for the training set:

This information is not present in the provided text. The device uses "internal software" with "variables programmed in by the user," but there's no mention of a machine learning model that would require a separate training set.

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

This information is not present in the provided text, as there is no mention of a training set or machine learning model that would require such a ground truth. The device relies on a "Bioelectrical Impedance Method" calculation based on pre-programmed variables.

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