Tests of verbal fluency (VF) are widely used in neurological, psychiatric, mental health, and school settings. There are two main types of VF tests - phonemic and semantic. The phonemic test consists of naming as many words as possible in 60 seconds that begin with a specified letter of the alphabet. The semantic test consists of naming words belonging to a semantic category (e.g., animals). These tests have been demonstrated to be useful for characterization of cognitive impairment due to a number of conditions including neurodegenerative disease, psychiatric diagnoses, developmental disorders, as well as potentially transient impairment due to traumatic brain injury or cardiovascular accidents, and drug toxicity or metabolic effects. While clinically very useful, verbal fluency tests are currently administered manually and are too cumbersome for wide adoption on a large scale in fast-paced and overburdened health care systems. Manual VF testing is also prone to scoring subjectivity and variability, and cannot be easily self-administered.
VF-Meter automates the administration and scoring of verbal fluency tests and makes them widely accessible and cost-effective. The technology uses computerized speech analysis algorithms on recorded audio files of people responding to a standard neuropsychological test of verbal fluency. VF-Meter can be easily administered on a variety of devices including the telephone, computer, tablet or a smartphone. The test results consists of estimates of the traditional verbal fluency score as well as a number of additional speech characteristics not available with paper-and-pencil testing.
The VF-Meter app is available for the iPad from the Apple Store . It is designed for test administrators for administering tests and collecting data.
The VF-Meter Server license is available to researchers who will use the software to collect, store and analyze spoken responses to neuropsychological assessments for research.
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cognitive impairment due
traumatic brain injury
recorded audio files
additional speech characteristics
analyze spoken responses