Objective: To present audiometric data in 3 dimensions by considering age as an addition dimension.
Methods: Audioprofile surfaces (APSs) were fitted to a set of audiograms by plotting each measurement of an audiogram as an independent point in 3 dimensions with the x, y, and z axes representing frequency, hearing loss in dB, and age, respectively.
Results: Using the Java-based APS viewer as a standalone application, APSs were pre-computed for 34 loci. By selecting APSs for the appropriate genetic locus, a clinician can compare this APS-generated average surface to a specific patient's audiogram.
Conclusion: Audioprofile surfaces provide an easily interpreted visual representation of a person's hearing acuity relative to others with the same genetic cause of hearing loss. Audioprofile surfaces will support the generation and testing of sophisticated hypotheses to further refine our understanding of the biology of hearing.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4821702 | PMC |
| http://dx.doi.org/10.1177/0003489415614863 | DOI Listing |
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Audioprofile Surfaces: The 21st Century Audiogram.
Ann Otol Rhinol Laryngol
May 2016
Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA Center for Bioinformatics and Computational Biology, University of Iowa, Iowa City, Iowa, USA Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, Iowa, USA.
Objective: To present audiometric data in 3 dimensions by considering age as an addition dimension.
Methods: Audioprofile surfaces (APSs) were fitted to a set of audiograms by plotting each measurement of an audiogram as an independent point in 3 dimensions with the x, y, and z axes representing frequency, hearing loss in dB, and age, respectively.
Results: Using the Java-based APS viewer as a standalone application, APSs were pre-computed for 34 loci.
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