DocumentCode :
2224404
Title :
Differentiation of perceived sound levels by electroencephalographic data : A novelty detection approach using habituation correlates
Author :
Mariam, Mai ; Delb, Wolfgang ; Strauss, Daniel J.
Author_Institution :
Comput. Diagnostics & Biocybernetics Unit, Saarland Univ. Hosp., Homburg, Germany
fYear :
2009
fDate :
April 29 2009-May 2 2009
Firstpage :
570
Lastpage :
573
Abstract :
Unsolved problem of cochlear implant as well as hearing aid fitting, i.e., to determine the threshold of most comfortable loudness level motivated our study. In the present study, we apply a single-sweep processing method which employs a hybrid approach of adaptive frame decomposition and the kernel based novelty detection machine for the detection of auditory habituation in late auditory evoked potentials (LAEPs) to differentiate the sweeps at 60 dB sound pressure level (SPL), 70 dB SPL, 80 dB SPL, and 90 dB SPL stimulation level. A significance difference among the habituation correlates in LAEPs of these stimulation levels was observed. It is concluded that the new approach provides a reliable method in the detection of habituation as well as differentiation of stimulation levels. It can be further used in more clinically oriented studies related to an objective fitting of hearing aids or cochlear implants.
Keywords :
auditory evoked potentials; cochlear implants; electroencephalography; hearing aids; medical signal processing; adaptive frame decomposition; auditory evoked potential; auditory habituation; cochlear implant; electroencephalographic data; habituation correlates; hearing aid; hearing aid fitting; kernel based novelty detection machine; perceived sound level; single-sweep processing method; Acoustic materials; Auditory system; Biological materials; Cochlear implants; Cybernetics; Ear; Hospitals; Kernel; Neural engineering; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
978-1-4244-2073-5
Type :
conf
DOI :
10.1109/NER.2009.5109360
Filename :
5109360
Link To Document :
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