Comparison of three different frequency-lowering technologies in Arabic speaking hearing loss children
Introduction Frequency-lowering is the generic term that refers to current technologies that take high-frequency input signals, typically considered speech sounds, and deliver them to a lower frequency region for improved speech understanding. Manufacturers of hearing aids (HAs) introduced frequency...
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Veröffentlicht in: | The Egyptian journal of otolaryngology 2018-04, Vol.34 (2), p.149-154 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Introduction
Frequency-lowering is the generic term that refers to current technologies that take high-frequency input signals, typically considered speech sounds, and deliver them to a lower frequency region for improved speech understanding. Manufacturers of hearing aids (HAs) introduced frequency-lowering techniques to compensate in part for the perceptual effects of high-frequency hearing impairments, which include linear frequency transposition scheme, nonlinear frequency compression, and spectral IQ.
Objectives
To find which of the three frequency-lowering technologies is more beneficial in amplifying high-frequency sounds in children with high-frequency hearing. We also aimed to find which technology gives the best aided Arabic speech score in our Egyptian children patients.
Patients and Methods
A total of 10 children with moderately severe to profound high-frequency sensory neural hearing loss using conventional methods of amplification were included. Aided threshold and word discrimination score were done four times using conventional HA once and other three trails using HAs with different frequency-lowering technology.
Results
Significant differences were found between conventional amplification and the three frequency-lowering technologies, where the spectral IQ was considered the best regarding functional gain and speech discrimination abilities.
Conclusion
Spectral IQ is better for children as a fitting strategy, giving more gain in the high frequencies and better speech identification. |
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ISSN: | 1012-5574 2090-8539 |
DOI: | 10.4103/ejo.ejo_51_17 |