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Fast, Continuous Audiogram Estimation Using Machine ...
https://pubmed.ncbi.nlm.nih.gov/26258575/
Objectives: Pure-tone audiometry has been a staple of hearing assessments for decades. Many different procedures have been proposed for measuring thresholds with pure tones by systematically manipulating intensity one frequency at a time until a discrete threshold function is determined. The authors have developed a novel nonparametric approach for estimating a …
Fast, Continuous Audiogram Estimation using Machine …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709018/
Békésy’s proposed automated audiogram, often referred to as “Békésy audiometry,” implemented a method of adjustment, giving listeners control of an attenuator used to identify the intensity at which they could not hear the presented stimulus.
Audiometry and Audiometric Testing Equipment | MAICO ...
https://www.maico-diagnostics.com/products/audiometers
What Is an Audiometer? An audiometer is a subjective device that is used to evaluate the hearing threshold of a person. An audiologist or other trained personnel uses an audiometer together with special audiometric testing techniques to determine the hearing threshold and to identify as well as quantify the degree of hearing loss of a person. From these results the appropriate referral …
Audiometry Procedures Manual
https://www.cdc.gov/nchs/data/nhanes/nhanes_05_06/AU.pdf
Increase the use of appropriate ear protection devices, equipment and practices (28.16); Reduce noise-induced hearing loss in children and adolescents under age 17 years (28.17); and Reduce adult hearing loss in the noise-exposed public (28.18). The current protocol for the hearing examination component of the NHANES was developed
Performance and Potential of Machine Learning …
https://journals.lww.com/thehearingjournal/fulltext/2021/03000/performance_and_potential_of_machine_learning.11.aspx
On the other hand, a machine learning audiogram can use information theory to determine the most informative next tone every step of the way, culminating in a considerably faster audiogram procedure. 4-7 This ability to extract more information from each tone is just the tip of the iceberg for machine learning audiometry.
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