Automating classification of ShoeBOX audiograms

点击翻译按钮获取中文摘要

Clearwater Clinicals ShoeBOX product enables audiometry testing to be completed in the field and outside of the sound booth. Ithas already been widely adopted, including monitoring hearing in the context of occupational health and safety in industrialsettings. Once a subjects hearing sensitivity has been quantified at various frequencies, the next step is to classify the audiogramin order to characterize any detected hearing loss. Classifications such as flat, sloping, rising and notched are further specified asbeing symmetric/asymmetric, the site of lesion, and the overall severity of hearing loss. Automating such audiogram classificationis the first step towards a fully automated testing and diagnostic audiology system. This project will leverage machine learning andsignal processing techniques to create data-driven automated and semi-automated audiogram classification systems, suitable fordeployment as part of the ShoeBOX system. Thanks to ShoeBOXs wide deployment, Clearwater Clinical now possesses a largedataset of unclassified audiograms. A rapid audiogram annotation system will be developed such that expert audiologists canclassify these audiograms. This rich gold standard dataset will be mined to develop an intelligent automated classification systemusing methods from machine learning including rule extraction and others. A semi-automated classification system will also bedeveloped, where users are able to view the recommended classification and make rapid adjustments based on their ownexpertise and additional contextual information. Final deliverables will include working software prototypes of the audiogramannotation environment, semi- and fully-automated classification systems, as well as technical documentation detailing theirdevelopment and evaluation..Ontario