Reference number : GC-2017-Q2-04292, amendment number : , agreement type : G, recipient legal name : Green, James (Carleton University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Clearwater Clinicals ShoeBOX product enables audiometry testing to be completed in the field and outside of the sound booth. It_x000D_
has already been widely adopted, including monitoring hearing in the context of occupational health and safety in industrial_x000D_
settings. Once a subjects hearing sensitivity has been quantified at various frequencies, the next step is to classify the audiogram_x000D_
in order to characterize any detected hearing loss. Classifications such as flat, sloping, rising and notched are further specified as_x000D_
being symmetric/asymmetric, the site of lesion, and the overall severity of hearing loss. Automating such audiogram classification_x000D_
is the first step towards a fully automated testing and diagnostic audiology system. This project will leverage machine learning and_x000D_
signal processing techniques to create data-driven automated and semi-automated audiogram classification systems, suitable for_x000D_
deployment as part of the ShoeBOX system. Thanks to ShoeBOXs wide deployment, Clearwater Clinical now possesses a large_x000D_
dataset of unclassified audiograms. A rapid audiogram annotation system will be developed such that expert audiologists can_x000D_
classify these audiograms. This rich gold standard dataset will be mined to develop an intelligent automated classification system_x000D_
using methods from machine learning including rule extraction and others. A semi-automated classification system will also be_x000D_
developed, where users are able to view the recommended classification and make rapid adjustments based on their own_x000D_
expertise and additional contextual information. Final deliverables will include working software prototypes of the audiogram_x000D_
annotation environment, semi- and fully-automated classification systems, as well as technical documentation detailing their_x000D_
development and evaluation._x000D_
._x000D_
Ontario, program purpose french : Clearwater Clinicals ShoeBOX product enables audiometry testing to be completed in the field and outside of the sound booth. It_x000D_
has already been widely adopted, including monitoring hearing in the context of occupational health and safety in industrial_x000D_
settings. Once a subjects hearing sensitivity has been quantified at various frequencies, the next step is to classify the audiogram_x000D_
in order to characterize any detected hearing loss. Classifications such as flat, sloping, rising and notched are further specified as_x000D_
being symmetric/asymmetric, the site of lesion, and the overall severity of hearing loss. Automating such audiogram classification_x000D_
is the first step towards a fully automated testing and diagnostic audiology system. This project will leverage machine learning and_x000D_
signal processing techniques to create data-driven automated and semi-automated audiogram classification systems, suitable for_x000D_
deployment as part of the ShoeBOX system. Thanks to ShoeBOXs wide deployment, Clearwater Clinical now possesses a large_x000D_
dataset of unclassified audiograms. A rapid audiogram annotation system will be developed such that expert audiologists can_x000D_
classify these audiograms. This rich gold standard dataset will be mined to develop an intelligent automated classification system_x000D_
using methods from machine learning including rule extraction and others. A semi-automated classification system will also be_x000D_
developed, where users are able to view the recommended classification and make rapid adjustments based on their own_x000D_
expertise and additional contextual information. Final deliverables will include working software prototypes of the audiogram_x000D_
annotation environment, semi- and fully-automated classification systems, as well as technical documentation detailing their_x000D_
development and evaluation._x000D_
._x000D_
Ontario, agreement title english : Automating classification of ShoeBOX audiograms, agreement title french : Automating classification of ShoeBOX audiograms, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-09-20, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada