A personalized automated system designed to assign hazardous noise exposures to tasks among agricultural workers.
Farming is a noisy occupation, resulting in a high prevalence of hearing loss among agricultural workers. The aim of this study was to improve the accuracy of an automatic algorithm designed to cluster individual sound events into tasks. This work is part of the HearSafe Study, which aimed to increa...
| Publicado en: | Journal of Occupational & Environmental Hygiene Vol. 23; no. 3; pp. 133 - 142 |
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| Autores principales: | , , , , , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Mar2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192585215&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192585215 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15459624 V1L jtl: Journal of Occupational & Environmental Hygiene issn: 15459624 maglogo: Y pubinfo: dt: Mar2026 vid: 23 iid: 3 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 192585215 189586464 192585215 192585215 10.1080/15459624.2025.2573667 192585215 ppf: 133 ppct: 9 formats: tig: atl: A personalized automated system designed to assign hazardous noise exposures to tasks among agricultural workers. aug: au: Peters, Thomas M. Griffis, Misha A. Stroh, Oliver Brown, Noah Curnick, Jacqueline Tatum, Marcus McCullagh, Marjorie C. Thomas, Geb affil: Occupational and Environmental Health, College of Public Health, University of Iowa, Iowa City, Iowa sug: subj: Hearing Loss, Noise-Induced Prevention and Control Farmworkers Psychosocial Factors Agriculture Automation Algorithms Noise Adverse Effects Occupational Exposure Analysis Task Performance and Analysis Human Female Male Descriptive Statistics One-Way Analysis of Variance Two-Way Analysis of Variance Post Hoc Analysis Data Analysis Software Ear Protective Devices Work Research Personnel Acoustics Methods Reproducibility of Results Sensitivity and Specificity Cluster Analysis Health Information Time Communication Funding Source Female Male ab: Farming is a noisy occupation, resulting in a high prevalence of hearing loss among agricultural workers. The aim of this study was to improve the accuracy of an automatic algorithm designed to cluster individual sound events into tasks. This work is part of the HearSafe Study, which aimed to increase agricultural workers' use of hearing protection devices by providing personalized information on hazardous noise to workers. Participants in the study interacted with the HearSafe System: a small sound level meter, a website, and an algorithm to associate noise with tasks. They wore the sound level meter that recorded loud (≥ 80 dBA) sound "events," their location, and audio clips. They interacted with the website to view where and when participants were exposed to hazardous noises during the day. To simplify interpretation, an algorithm clustered individual sound events into tasks based on their proximity in time and location. The system's effectiveness hinges on the accuracy of this clustering algorithm. In Phase I, the accuracy was determined using parameters for time between events (2, 5, and 10 min) and distances between tasks (5, 9, and 18 m). In Phase II, the algorithm was refined to account for pauses in work and riding on equipment. Researchers manually clustered events into tasks by listening to the audio clips. Algorithm accuracy was measured as the percentage of events matching the manual clustering. The automating accuracy was improved from 57% with the base algorithm to 87% with the most accurate algorithm (p = 0.02; 10 min between events, 9 m average distance between tasks, and added the condition to combining consecutive tasks that were within 9 m of each other). Increased accuracy in identifying noisy tasks will improve the efficacy of the HearSafe System to communicate when and where use of hearing protection devices are needed among agricultural workers. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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