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

Collection with item attached
2017
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/474109.do
DOI
10.21053/ceo.2015.01690
Title
A Trainable Hearing Aid Algorithm Reflecting Individual Preferences forDegree of Noise-Suppression, Input Sound Level, and Listening Situation
Description
This research was supported by a grant of the Korea Health TechnologyR&D Project through the Korea Health Industry Development Institute(KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea(grant no.: HI14C0771).
abstract
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 0 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.
provenance
Made available in Cube on 2018-09-28T10:37:27Z (GMT). No. of bitstreams: 0
language
English
author
Yoon, Sung Hoon
Nam, Kyoung Won
Yook, Sunhyun
Cho, Baek Hwan
Jang, Dong Pyo
Hong, Sung Hwa
Kim, In Young
accessioned
2018-09-28T10:37:27Z
available
2018-09-28T10:37:27Z
issued
2017
citation
CLINICAL AND EXPERIMENTAL OTORHINOLARYNGOLOGY(10): 1
issn
1976-8710
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/474109.do
Funder
보건복지부
Funding Program
의료기기기술개발
Project ID
1465023582
Jurisdiction
Rep.of Korea
Project Name
development of a system to predict cardiac arrest using complex biosignals.
rights
openAccess
subject
Hearing Aid
Classification
Patient Preference
Digital SignalProcessing
type
article


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