The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Mimicking the human ear
Abstract
A prosthetic device, called a cochlear implant, can be implanted in the inner ear and can restore partial hearing to profoundly deaf people. Some individuals with implants can now communicate without lip-reading or signing, and some can communicate over the telephone. The success of cochlear implants can be attributed to the combined efforts of scientists from various disciplines including bioengineering, physiology, otolaryngology, speech science, and signal processing. Each of these disciplines contributed to various aspects of the design of cochlear prostheses. Signal processing, in particular, played an important role in the development of different techniques for deriving electrical stimuli from the speech signal. Designers of cochlear prosthesis were faced with the challenge of developing signal-processing techniques that would mimic the function of a normal cochlea. The purpose of this article is to present an overview of various signal-processing techniques that have been used for cochlear prosthesis over 25 years. The signal-processing strategies described are only a subset of the many that have been developed for cochlear prosthesis.
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Citations
Cites
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Cited by
Music Perception with Temporal Cues in Acoustic and Electric Hearing
Kong, Y.-Y., Cruz, R., Jones, J. A., & Zeng, F.-G. (2004) · Ear and Hearing · doi:10.1097/01.aud.0000120365.97792.2f · Cited by 377
Temporal considerations for stimulating spiral ganglion neurons with cochlear implants.
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Design Guideline for Developing Safe Systems that Apply Electricity to the Human Body
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Metadata
- Authors
- Loizou, P. C.
- Venue
- IEEE Signal Processing Magazine
- Published
- 1998
- Volume
- 15
- Issue
- 5
- Pages
- 101-130
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W2104220500
- Cited by
- 326
- References
- 40
- FWCI
- 2.53
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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