Multidimensional Active Testing

Videos to Illustrate Multidimensional Active Testing (MAT)

Example of traditional, inefficient method of independent threshold testing for each test condition:

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Audiometry is the measurement of sound thresholds at different frequencies. Here, the different plot symbols indicate whether or not a test tone was heard. Tones adaptively zero in on the threshold at one frequency before moving on to the next. Test batteries of any sort generally employ a similar approach. The test battery proceeds one test at a time, and information is not shared across tests. This type of testing has little or no capacity to improve in efficiency or predictive value.

Example of MAT as a more efficient method of testing that shares information across tests:

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Machine learning audiometry enables information to be shared across all the input variables. Here, the conventional audiometric threshold values are superimposed as a line over a fully predictive machine learning model that improves after each new tone. A faster and more informative test results.


Song XD, Wallace BM, Gardner JR, Ledbetter NM, Weinberger KQ, Barbour DL. “Fast, continuous audiogram estimation using machine learning.” Ear and Hearing, 2015 Nov-Dec;36(6):e326-35, PMID: 26258575, PMCID: PMC4709018, DOI: 10.1097/AUD.0000000000000186

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