A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation
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 expand...
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| Format: | Article |
| Language: | English |
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Korean Society of Otorhinolaryngology-Head and Neck Surgery
2017-03-01
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| Series: | Clinical and Experimental Otorhinolaryngology |
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| Online Access: | http://www.e-ceo.org/upload/pdf/ceo-2015-01690.pdf |
| _version_ | 1811195923181600768 |
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| author | Sung Hoon Yoon Kyoung Won Nam Sunhyun Yook Baek Hwan Cho Dong Pyo Jang Sung Hwa Hong In Young Kim |
| author_facet | Sung Hoon Yoon Kyoung Won Nam Sunhyun Yook Baek Hwan Cho Dong Pyo Jang Sung Hwa Hong In Young Kim |
| author_sort | Sung Hoon Yoon |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T00:50:17Z |
| format | Article |
| id | doaj.art-647a061f92d84354ac8b54192b236519 |
| institution | Directory Open Access Journal |
| issn | 1976-8710 2005-0720 |
| language | English |
| last_indexed | 2024-04-12T00:50:17Z |
| publishDate | 2017-03-01 |
| publisher | Korean Society of Otorhinolaryngology-Head and Neck Surgery |
| record_format | Article |
| series | Clinical and Experimental Otorhinolaryngology |
| spelling | doaj.art-647a061f92d84354ac8b54192b2365192022-12-22T03:54:45ZengKorean Society of Otorhinolaryngology-Head and Neck SurgeryClinical and Experimental Otorhinolaryngology1976-87102005-07202017-03-01101566510.21053/ceo.2015.01690513A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening SituationSung Hoon Yoon0Kyoung Won Nam1Sunhyun Yook2Baek Hwan Cho3Dong Pyo Jang4Sung Hwa Hong5In Young Kim6 Institute of Biomedical Engineering, Hanyang University, Seoul, Korea Department of Biomedical Engineering, Hanyang University, Seoul, Korea Department of Medical Device Management & Research, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Korea S/W Solution Lab, Samsung Advanced Institute of Technology, Yongin, Korea Department of Biomedical Engineering, Hanyang University, Seoul, Korea Department of Otolaryngology-Head and Neck Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea Institute of Biomedical Engineering, Hanyang University, Seoul, KoreaObjectives 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.http://www.e-ceo.org/upload/pdf/ceo-2015-01690.pdfHearing AidClassificationPatient PreferenceDigital Signal Processing |
| spellingShingle | Sung Hoon Yoon Kyoung Won Nam Sunhyun Yook Baek Hwan Cho Dong Pyo Jang Sung Hwa Hong In Young Kim A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation Clinical and Experimental Otorhinolaryngology Hearing Aid Classification Patient Preference Digital Signal Processing |
| title | A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation |
| title_full | A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation |
| title_fullStr | A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation |
| title_full_unstemmed | A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation |
| title_short | A Trainable Hearing Aid Algorithm Reflecting Individual Preferences for Degree of Noise-Suppression, Input Sound Level, and Listening Situation |
| title_sort | trainable hearing aid algorithm reflecting individual preferences for degree of noise suppression input sound level and listening situation |
| topic | Hearing Aid Classification Patient Preference Digital Signal Processing |
| url | http://www.e-ceo.org/upload/pdf/ceo-2015-01690.pdf |
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