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Balance Evaluation and Rehabilitation

The Balance Rehabilitation Unit (BRUTM) is a system that enables the functional assessment and training/retraining of patients with balance disorders, vertigo or instability.

The Balance Rehabilitation Unit (BRUTM) is composed of a static force platform, virtual reality projection goggles, a head tracker for sensing head movements, a safety frame, a harness, an accessory kit for different exercises, and a computer to generate stimuli.

The system performs a sequence of posturographies while the patient is receiving different visual stimuli (images displayed on the projection goggles). By using the different stimuli to identify the patient's weakness a tailored rehabilitation program with specific perceptual cues can be designed for each patient.

The Balance Rehabilitation Unit (BRUTM) performs an assessment of the impaired postural skills of patients through a series of posturographies with different sensory stimuli. The posturographies are performed using a forcemeasuring platform, which helps the physician evaluate the patient's performance. The sensory stimuli used with the Balance Rehabilitation Unit (BRUTM) include visual stimuli, through virtual reality projection goggles, somatosensorial stimuli, and vestibular stimuli.

The provided text does not contain acceptance criteria or a detailed study sufficient to fulfill your request comprehensively.

The document, K070085 for the WEIDMANN (Medicaa) BRUTM - Balance Rehabilitation Unit, is a 510(k) summary for premarket notification to the FDA. Its primary purpose is to demonstrate substantial equivalence to a predicate device, not to present a detailed performance study with acceptance criteria.

Here's what can be extracted based on your request, along with what is explicitly missing:

The key statement regarding testing is:

"A clinical study has confirmed the clinical efficacy of the Balance Rehabilitation Unit (BRUTM)."

This is a very high-level statement and lacks all the specific details you've asked for.

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

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.
• Data Provenance: The document states Medicaa is based in Montevideo, Uruguay. It doesn't explicitly state the country of origin for the clinical study data or whether it was retrospective or prospective.

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)

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

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

• Adjudication Method: Not specified.

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

• MRMC Study: The device is a 'Balance Rehabilitation Unit' and not an AI-assisted diagnostic tool for "human readers." Therefore, an MRMC study in the context of human readers improving with AI assistance is not applicable to this device type. The document does not mention any MRMC study.
• Effect Size: Not applicable/not specified.

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

• The device performs "posturographies" and "helps the physician evaluate the patient's performance." While it uses a computer to generate stimuli, it's presented as a tool for assessment and training that would involve a physician/human in the loop. The concept of "standalone algorithm performance" as typically applied to AI diagnostic tools is not directly relevant or discussed in the context of this device. No standalone performance study is mentioned.

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

• The document implies the device measures "imparied postural skills" and assesses "clinical efficacy." This suggests the "ground truth" would likely be related to clinical observations or outcomes regarding balance disorders, vertigo, or instability but the specific methodology for establishing this is not detailed.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This device does not inherently describe a machine learning model with a distinct "training set" in the way an AI diagnostic tool would. The "clinical study" mentioned would be for validation, not training.

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

• How Ground Truth Established: Not applicable, as there's no mention of a training set for an AI model.

In summary: The provided text is a regulatory submission focused on substantial equivalence to a predicate device for marketing purposes. It briefly mentions a "clinical study" to confirm "efficacy" but lacks the detailed methodologies, acceptance criteria, sample sizes, expert qualifications, and ground truth definitions that would typically be found in a comprehensive study report or a more detailed technical overview of device performance.

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