Search Results

The Test of Variables of Attention (T.O.V.A.) provides healthcare professionals with objective measurements of attention and inhibitory control. The visual T.O.V.A. aids in the assessment of, and evaluation of treatment for, attention deficits, including attention-deficit/hyperactivity disorder (ADHD). The auditory T.O.V.A. aids in the assessment of attention deficits, including ADHD. T.O.V.A. results should only be interpreted by qualified professionals.

The Test of Variables of Attention (T.O.V.A.) is an accurate and objective continuous performance test (CPT) that measures the key components of attention and inhibitory control. The T.O.V.A. is used by qualified healthcare professionals in the assessment of attention deficits, including attention-deficit/hyperactivity disorder (ADHD), in children and adults. In addition, the visual T.O.V.A. is used to evaluate treatment for attention deficits, including ADHD.

The T.O.V.A. is a culture- and language-free, sufficiently long computerized test that requires no left/right discrimination or sequencing. Responses to visual or auditory stimuli are recorded with a specially designed, highly accurate (±1 ms) microswitch. The T.O.V.A. calculates response time variability (consistency), response time (speed), commissions (impulsivity), and omissions (focus and vigilance). These calculations are then compared to a large age- and gender-matched normative sample (over 1,700 individuals for the visual test, and over 2,500 individuals for the auditory test), as well as to a sample population of individuals independently diagnosed with ADHD. These comparison results are used to create an immediately available, easy-to-read report.

The T.O.V.A. system includes: a USB flash drive with software installer for Mac and Windows PCs, a T.O.V.A. USB device, a T.O.V.A. Microswitch, an Installation Guide, a User's Manual, a Clinical Manual, and accessory cables (USB, VGA, and audio cables).

This document is a 510(k) premarket notification for the Test of Variables of Attention (T.O.V.A.) version 9.0. It primarily focuses on demonstrating substantial equivalence to a predicate device (QbTest) rather than outlining specific clinical trials to prove device performance against acceptance criteria in the manner one might find for an AI/ML medical device.

Therefore, many of the requested details about acceptance criteria and a study proving those criteria are not explicitly present in the provided text, as the submission relies on demonstrating equivalence through technical specifications, safety, and functionality, rather than novel clinical performance endpoints.

However, I can extract and infer information relevant to the various sections of your request based on the provided document:

Acceptance Criteria and Device Performance (Inferred from Substantial Equivalence Claim)

Since this is a 510(k) submission, the "acceptance criteria" are primarily established by demonstrating substantial equivalence to a predicate device, meaning the new device performs at least as safely and effectively as the predicate for its stated indications for use. There isn't a table of specific clinical performance metrics with numerical targets as would be seen for a new AI/AD.

The "device performance" is primarily assessed against regulatory standards (electrical safety, EMC) and functional verification, as well as the comparison to the predicate device's established performance (which is implicitly "accepted" by prior FDA clearance).

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set (for the K173915 submission specifically to demonstrate substantial equivalence): The document primarily refers to technical testing (IEC 60601-1, IEC 60601-1-2, T.O.V.A. Verification Testing) and a comparison with the predicate device's specifications. These are not "test sets" in the sense of a clinical performance study with patient data against a ground truth.
  • For the technical verification, there isn't a specified "sample size" of devices, but rather laboratory testing of the device system.
  • The "normative samples" used to establish the large age- and gender-matched comparison data for the T.O.V.A. itself are:
    • Visual Test: Over 1,700 individuals (stated as 1,714 in the comparison table)
    • Auditory Test: Over 2,500 individuals (stated as 2,680 in the comparison table)
  • Data Provenance: Not specified in terms of country of origin or retrospective/prospective. The description of normative samples and "sample population of individuals independently diagnosed with ADHD" suggests pre-existing or collected data, but the collection methodology (retrospective/prospective) is not detailed for this specific 510(k) summary.

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

• This is not applicable as there isn't a "test set" in the context of clinical images or patient cases requiring expert interpretation for ground truth. The device measures objective quantities (response time, omissions, commissions).
• For the normative data, the document mentions comparison to a "sample population of individuals independently diagnosed with ADHD." This implies that clinical diagnoses (established by qualified healthcare professionals) served as a form of "ground truth" for the ADHD sample, but the number or specific qualifications of these diagnosing professionals are not provided. The T.O.V.A. itself is intended to "aid in the assessment" and "results should only be interpreted by qualified professionals."

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

• Not applicable. There is no clinical imaging or interpretative "test set" here that would require an adjudication process.

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 not an AI-assisted diagnostic tool that aids human readers in interpreting complex data like medical images. It's a continuous performance test that generates objective measurements.

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

• The T.O.V.A. is inherently a "standalone" device in terms of its measurement capabilities, as it directly calculates various performance metrics (response time, omissions, etc.). However, it is explicitly stated that "T.O.V.A. results should only be interpreted by qualified professionals." This means it's a tool for professionals, not a standalone diagnostic that provides a final diagnosis without human interpretation. So, while the measurement itself is algorithmic, the clinical utility is human-in-the-loop.

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

• For the "sample population of individuals independently diagnosed with ADHD," the ground truth was clinical diagnosis (presumably by qualified professionals).
• For the normative data, the "ground truth" is simply a large, healthy normative population against which patient results are compared.

8. The sample size for the training set:

• The term "training set" doesn't strictly apply in the sense of an AI/ML algorithm being trained on data to learn patterns.
• However, the normative samples which the device uses for comparison can be considered analogous to a "training set" for establishing statistical norms. These are:
  • Visual T.O.V.A.: Over 1,700 individuals (1,714)
  • Auditory T.O.V.A.: Over 2,500 individuals (2,680)

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

• For the normative samples, the "ground truth" was established by collecting data from a large population of individuals, presumably healthy or without a pre-existing ADHD diagnosis at the time of data collection for the normative comparison. The document states they are "age- and gender-matched normative sample."
• For the "sample population of individuals independently diagnosed with ADHD" (used for comparison to distinguish ADHD from normative data), the ground truth was established by independent clinical diagnoses of ADHD. The specifics of how these diagnoses were confirmed (e.g., DSM criteria, multiple clinicians, etc.) are not provided in this 510(k) summary.

Ask a specific question about this device