An ontology to support hearing protection device selection and reduce noise-induced hearing loss

Abstract

Noise-induced hearing loss (NIHL) is widespread. Hearing protection devices (HPDs) are intended to reduce noise exposure and limit NIHL. However, rigorous HPD selection is complex as HPDs often impede auditory functions necessary to maintain situation awareness, and selection is dependent upon diverse user needs, environmental contexts, and behavioral factors. This research employs a modular ontology method to develop a knowledge representation to unify conceptual understanding and the availability of passive HPD data among industrial hygienists and experts across the United States Department of Defense and the National Institute of Occupational Safety and Health. The objective of the study was to harmonize standard terminology, identify a comprehensive set of metrics, and create a searchable repository to facilitate HPD selection. By capturing human, environmental, and device-related attributes in a structured, machine-readable format, the ontology lays the foundation for a sharable repository to support user-centered, and context-specific HPD selection. Unfortunately, detailed technical data to support selection is not readily available. Data collection efforts are recommended to populate the ontology, providing practitioners with access to metrics and data to support analytic HPD selection.