Pickens Adam W, Robertson Lakshmi Dakuri, Smith Matthew Lee, Zheng Qi, Song Sejun
Texas A&M Ergonomics Center, Department of Environmental and Occupational Health, Texas A&M Health Science Center (TAMHSC) School of Public Health, College Station, TX, United States.
Center for Population Health and Aging, Department of Environmental and Occupational Health, Texas A&M Health Science Center (TAMHSC) School of Public Health, College Station, TX, United States.
Int Arch Otorhinolaryngol. 2018 Oct;22(4):358-363. doi: 10.1055/s-0037-1607438. Epub 2017 Dec 6.
With the need for hearing screenings increasing across multiple populations, a need for automated options has been identified. This research seeks to evaluate the hardware requirements for automated hearing screenings using a mobile application. Evaluation of headphone hardware for use with an app-based mobile screening application. For the purposes of this study, hEAR, a Bekesy-based mobile application designed by the research team, was compared with pure tone audiometric tests administered by an audiologist. Both hEAR and the audiologist's test used 7 frequencies (125 Hz, 250 Hz, 500 Hz, 1,000 Hz, 2000 Hz, 4,000 Hz and 8,000 Hz) adopting four different sets of commercially available headphones. The frequencies were regarded as the independent variable, whereas the sound pressure level (in decibels) was the dependent variable. Thirty participants from a university in Texas were recruited and randomly assigned to one of two groups, whose only difference was the order in which the tests were performed. Data were analyzed using a generalized estimating equation model at α = 0.05. Findings showed that, when used to collect data with the mobile app, both the Pioneer HDJ-2000 (Pioneer, Bunkyo, Tokyo, Japan) ( > 0.05) and the Sennheiser HD280 Pro (Sennheiser, Wedemark, Hanover, Germany) ( > 0.05) headphones presented results that were not statistically different from the audiologist's data across all test frequencies. Analyses indicated that both headphones had decreased detection probability at 4kHz and 8kHz, but the differences were not statistically significant. Data indicate that a mobile application, when paired with appropriate headphones, is capable of reproducing audiologist-quality data.
随着多个群体对听力筛查的需求不断增加,人们已经认识到对自动化选项的需求。本研究旨在评估使用移动应用程序进行自动听力筛查的硬件要求。
评估用于基于应用程序的移动筛查应用程序的耳机硬件。
在本研究中,研究团队设计的基于贝凯西的移动应用程序hEAR与听力学家进行的纯音听力测试进行了比较。hEAR和听力学家的测试都使用了7个频率(125Hz、250Hz、500Hz、1000Hz、2000Hz、4000Hz和8000Hz),采用了四套不同的市售耳机。频率被视为自变量,而声压级(以分贝为单位)是因变量。从德克萨斯州的一所大学招募了30名参与者,并将他们随机分配到两个组中的一组,两组的唯一区别是测试执行的顺序。使用广义估计方程模型在α = 0.05的水平上对数据进行分析。
结果表明,当用于通过移动应用程序收集数据时,先锋HDJ - 2000(先锋,日本东京文京区)( > 0.05)和森海塞尔HD280 Pro(森海塞尔,德国汉诺威市韦德马克)( > 0.05)耳机在所有测试频率上呈现的结果与听力学家的数据在统计学上没有差异。分析表明,两款耳机在4kHz和8kHz时检测概率均有所下降,但差异无统计学意义。
数据表明,移动应用程序与合适的耳机配对时,能够再现听力学家质量的数据。