A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation

연성훈; 남경원; 욱선현; 조백환; 장동표; 홍성화; 김인영

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자료유형: 학술저널

저자정보: 연성훈 남경원 욱선현 조백환 장동표 홍성화 김인영

저널정보: 대한이비인후과학회 Clinical and Experimental Otorhinolaryngology Clinical and Experimental Otorhinolaryngology 제10권 제1호

발행연도: 2017.1

수록면: 56 - 65 (10page)

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Objectives. In an effort to improve hearing aid users’ satisfaction, recent studies on trainable hearing aids have attempted to implement one or two environmental factors into training. However, it would be more beneficial to train the device based on the owner’s personal preferences in a more expanded environmental acoustic conditions. Our study aimed at developing a trainable hearing aid algorithm that can reflect the user’s individual preferences in a more extensive environmental acoustic conditions (ambient sound level, listening situation, and degree of noise suppression) and evaluated the perceptual benefit of the proposed algorithm. Methods. Ten normal hearing subjects participated in this study. Each subjects trained the algorithm to their personal preference and the trained data was used to record test sounds in three different settings to be utilized to evaluate the perceptual benefit of the proposed algorithm by performing the Comparison Mean Opinion Score test. Results. Statistical analysis revealed that of the 10 subjects, four showed significant differences in amplification constant settings between the noise-only and speech-in-noise situation (P<0.05) and one subject also showed significant difference between the speech-only and speech-in-noise situation (P<0.05). Additionally, every subject preferred different β settings for beamforming in all different input sound levels. Conclusion. The positive findings from this study suggested that the proposed algorithm has potential to improve hearing aid users’ personal satisfaction under various ambient situations.

#Hearing Aid #Classification #Patient Preference #Digital Signal Processing

참고문헌 (24)

참고문헌 신청

Boymans M / 2012 / Audiologist-driven versus patient-driven fine tuning of hearing instruments / Trends Amplif 16 (1) : 49 ~ 58

Buchler M / 2005 / Sound classification in hearing aids inspired by auditory scene analysis / EURASIP J Appl Signal Process 18 : 2991 ~ 3002

Byrne D / 2001 / NAL-NL1 procedure for fitting nonlinear hearing aids: characteristics and comparisons with other procedures / J Am Acad Audiol 12 (1) : 37 ~ 51

Chalupper J / 2009 / Algorithm lets users train aid to optimize compression, frequency shape, and gain / Hearing J 62 (8) : 26 ~

Dillon H / 2006 / The trainable hearing aid : what will it do for clients and clinicians? / Hearing J 59 (4) : 30 ~

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