Computer-aided prediction of hearing loss based on auditory perception
| Autor: | Muhammad Ilyas, Amine Nait-Ali, Alice Othmani |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Auditory perception
medicine.medical_specialty Computer Networks and Communications Computer science Hearing loss 020207 software engineering 02 engineering and technology Audiology Noise exposure Hardware and Architecture Age estimation Prediction methods otorhinolaryngologic diseases 0202 electrical engineering electronic engineering information engineering Media Technology medicine Computer-aided Active listening medicine.symptom Software Loud music |
| Zdroj: | Multimedia Tools and Applications. 79:15765-15789 |
| ISSN: | 1573-7721 1380-7501 |
| DOI: | 10.1007/s11042-020-08910-w |
| Popis: | Hearing loss is the principle cause behind hearing impairment and deafness around the world. It is a significant health problem affecting our world today and it is growing exponentially among young and adults due to aging, hearing impairment, listening to music and noise exposure. Treatment options for hearing loss are very limited and it can only be controlled by taking precautions in the early stages. Thus, proper education is required to spread awareness among people to use hearing protections, reduce exposure to loud music and other risk factors. In this paper, we present a computer-aided method to predict and then prevent hearing loss. Three predictive models (human age estimation, prediction of hearing loss and level of hearing loss) based on auditory perception are presented. Our predictive model of human age estimation is very robust with a Mean Absolute Error (MAE) value of 4.1 years, while the accuracy of the second predictive model of hearing loss is equal to 94% and the third predictive model of the level of hearing loss present an accuracy of 90%. Our computer-aided prediction methods of hearing loss is found very promising and can be used in real application systems and 503 subjects participated to conduct the experiment. |
| Databáze: | OpenAIRE |
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