An Ontology-Based Expert System Approach for Hearing Aid Fitting in a Chaotic Environment DOI Creative Commons

Guy Merlin Ngounou,

Anne Marie Chana, Bernabé Batchakui

и другие.

Audiology Research, Год журнала: 2025, Номер 15(2), С. 39 - 39

Опубликована: Апрель 8, 2025

Background/Objectives: Hearing aid fitting is critical for hearing loss rehabilitation but involves complex, interdependent parameters, while AI-based technologies offer promise, their reliance on large datasets and cloud infrastructure limits use in low-resource settings. In such cases, expert knowledge, manufacturer guidelines, research findings become the primary sources of information. This study introduces DHAFES (Dynamic Aid Fitting Expert System), a personalized, ontology-based system fitting. Methods: A dataset common patient complaints was analyzed to identify typical auditory issues. multilingual self-assessment questionnaire developed efficiently collect user-reported complaints. With input, were categorized mapped corresponding solutions. An ontology, Ontology (HAFO), using OWL 2. DHAFES, decision support system, then implemented process inputs generate recommendations. Results: supports 33 core complaint classes ensures transparency traceability. It operates offline remotely, improving accessibility resource-limited environments. Conclusions: scalable, explainable, clinically relevant solution Its design enables adaptation diverse clinical contexts provides foundation future AI integration.

Язык: Английский

An Ontology-Based Expert System Approach for Hearing Aid Fitting in a Chaotic Environment DOI Creative Commons

Guy Merlin Ngounou,

Anne Marie Chana, Bernabé Batchakui

и другие.

Audiology Research, Год журнала: 2025, Номер 15(2), С. 39 - 39

Опубликована: Апрель 8, 2025

Background/Objectives: Hearing aid fitting is critical for hearing loss rehabilitation but involves complex, interdependent parameters, while AI-based technologies offer promise, their reliance on large datasets and cloud infrastructure limits use in low-resource settings. In such cases, expert knowledge, manufacturer guidelines, research findings become the primary sources of information. This study introduces DHAFES (Dynamic Aid Fitting Expert System), a personalized, ontology-based system fitting. Methods: A dataset common patient complaints was analyzed to identify typical auditory issues. multilingual self-assessment questionnaire developed efficiently collect user-reported complaints. With input, were categorized mapped corresponding solutions. An ontology, Ontology (HAFO), using OWL 2. DHAFES, decision support system, then implemented process inputs generate recommendations. Results: supports 33 core complaint classes ensures transparency traceability. It operates offline remotely, improving accessibility resource-limited environments. Conclusions: scalable, explainable, clinically relevant solution Its design enables adaptation diverse clinical contexts provides foundation future AI integration.

Язык: Английский

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