How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hypoacusia

Barrero, Jesús P.; Herrero, Susana Garcı́a; Saldaña, Miguel Ángel Mariscal; Gutiérrez, José Manuel

doi:10.1016/j.ssci.2018.07.011

Cited by 7 publications

(5 citation statements)

References 29 publications

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“…The research resulted that time on the job is an influential factors for its spreading. 24 These results are discussed from both an applied and theoretical perspective. Memoli et al 25 worked on noise-related traffic, that is, noise related to railway, road traffic, and airplane noises and also with industries.…”

Section: Literature Reviewmentioning

confidence: 97%

Excess noise reduction with ear protector applying mathematical algorithm: A case of medium density fiber industry

Khan

Noor

Habib

et al. 2020

Noise & Vibration Worldwide

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Consistent exposure to elevated sound levels results in noise health effects. The industrial environment represents a major source of such effects. There is significant variation in noise at different sections of such industries due to which most of the workers are exposed to these sounds at one or another level. In this study, a noise level measuring methodology is used for fixed and moving workers. This article introduces an algorithm for optimum selection of earmuff and earplug for different working places depending upon the exposure to noise. Medium density fiber industry is considered as a case for this study. It considers workers who are busy at a single point and face a consistent amount of noise as well as the workers who move and are exposed to a varying level of the noise. Noise level meters are used to measure the noise level at different points. At each point, the average value of the samples is taken. Based on the data collected, earmuff with high noise reduction rate is assigned to the workers closed to the machines. Implementation of the developed algorithm reduced the effect of noise on workers by 6.9%, 5%, and 16.3% for the chipper machine, pneumatic fan, and sanding machine, respectively, that were identified as the major source of noise at medium density fiber industry. This percentage reduction helped the workers to bring them to the optimum safe level of noise that is 85 dB and protect them from hearing loss severity due to frequency variations.

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Section: Literature Reviewmentioning

confidence: 97%

Excess noise reduction with ear protector applying mathematical algorithm: A case of medium density fiber industry

Khan

Noor

Habib

et al. 2020

Noise & Vibration Worldwide

View full text Add to dashboard Cite

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“…The percentage of binaural loss (%Bl) is used for evaluating hearing acuity based on audiometric tests [13,44] that rely on a "social" evaluation of hearing loss. It is an index of considerable legal importance for assessing hearing impairment or hypoacusia that is used in Spain to obtain, pursuant to R.D.…”

Section: Percentage Of Binaural Lossmentioning

confidence: 99%

“…In order to do this, a 10-fold cross-validation [50] is proposed by dividing the full sample into 10 disjoint data subsets, containing N/10 elements each. The data subsets will be used once as a test set, and the remaining data will be used to train the model [13]. Note that by joining the 10 folds, a prediction for the whole is obtained that could be compared to the data.…”

Section: Model Performance Receiver-operating Characteristicsmentioning

confidence: 99%

“…Although the most common trigger for this disease is noise [9], in terms of the risk factors for developing hypoacusia as a professional disease, the first-order factors can generally be considered to be physical characteristics such as sound pressure, the type of noise, and length of exposure as well as other factors such as age and some personal characteristics of the worker [9,13,14]. Other aspects to be considered are position relative to the sound source and the distance, the work environment, diseases, osteosclerosis, and gender, among others.…”

Section: Introductionmentioning

confidence: 99%

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Assessment and Modeling of the Influence of Age, Gender, and Family History of Hearing Problems on the Probability of Suffering Hearing Loss in the Working Population

Barrero

López-Perea

Herrera

et al. 2020

IJERPH

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Hearing loss affects hundreds of millions of people all over the world, leading to several types of disabilities, ranging from purely physical to psychological and/or social aspects. A proper analysis to ascertain the main risk factors is essential in order to diagnose early and treat adequately. An exploratory analysis based on a heterogeneous sample of 1418 workers is presented in order to identify the main trigger factors for hearing loss. On the one hand, we recorded several medical and environmental parameters, and on the other, we created a model based on Bayesian networks in order to be able to infer the probability of hearing loss considering different scenarios. This paper focuses on three parameters: gender, age, and a family history of hearing problems. The results obtained allow us to infer or predict the best or worst auditory level for an individual under several different scenarios. The least relevant factor is the existence of a family history of deafness, followed by the gender factor, which slopes considerably toward better hearing for females, and most prominent of all, the age factor, given the large differences identified between the various age groups when the gender and family history of deafness variables remain constant.

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“…The dataset was designed to answer the basic questions of how and why some workers develop hypoacusia. The variables are classified as demographic and personal factors (meaning those that characterise a specific population) occupational factors (those related to the working conditions in different companies) and non-occupational factors (those that are manifested outside the work environment) [1] .…”

Section: Datamentioning

confidence: 99%

Data on the main working conditions with influence on the development of hearing loss amongst the occupational population in Spain

et al. 2018

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Obtaining reliable and objective data on certain working conditions is necessary to analyse the causes and variables that can influence the development of hearing loss amongst the working population. Objective occupational data have been collected from a heterogeneous sample of 1418 workers in Spain, see “How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hipoacusia” (Barrero et al., 2018) [1]. Among the main factors analysed are the noise levels to which these workers are exposed, measured at their respective workstations, and the assessment of their hearing status, evaluated by audiometric medical tests. These factors provide information to predict the development of hypoacusia.

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How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hypoacusia

Cited by 7 publications

References 29 publications

Excess noise reduction with ear protector applying mathematical algorithm: A case of medium density fiber industry

Excess noise reduction with ear protector applying mathematical algorithm: A case of medium density fiber industry

Assessment and Modeling of the Influence of Age, Gender, and Family History of Hearing Problems on the Probability of Suffering Hearing Loss in the Working Population

Data on the main working conditions with influence on the development of hearing loss amongst the occupational population in Spain

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