Browse > Article
http://dx.doi.org/10.9718/JBER.2013.34.2.47

Evaluation of Stimulus Strategy for Cochlear Implant Using Neurogram  

Yang, Hyejin (Biomedical Engineering, School of Electrical Engineering, University of Ulsan)
Woo, Jihwan (Biomedical Engineering, School of Electrical Engineering, University of Ulsan)
Publication Information
Journal of Biomedical Engineering Research / v.34, no.2, 2013 , pp. 47-54 More about this Journal
Abstract
Electrical stimulation is delivered to auditory nerve (AN) through the electrodes in cochlear implant system. Neurogram is a spectrogram that includes information of neural response to electrical stimulation. We hypothesized that the similarity between a neurogram and an input-sound spectrogram could show how well a cochlear implant system works. In this study, we evaluated electrical stimulus configuration of CIS strategy using the computational model. The computational model includes stochastic property and anatomical features of cat auditory nerve fiber. To evaluate similarity between a neurogram and an input-sound spectrogram, we calculated Structural Similarity Index (SSIM). The results show that the dynamic range and the stimulation rate per channel influenced SSIM. Finally, we suggested the optimal configuration within the given stimulus CIS. We expect that the results and the evaluating procedure could be employed to improve the performance of a cochlear implant system.
Keywords
computational model; electrical stimulation; neurogram; electrodogram; SSIM;
Citations & Related Records
연도 인용수 순위
  • Reference
1 P. C. Loizou, "Introduction to cochlear implants," IEEE Eng Med Biol Mag, vol. 18, pp. 32-42, 1999.
2 M. W. White, M. M. Merzenich, and J. N. Gardi, "Multichannel Cochlear ImplantsChannel Interactions and Processor Design," Arch Otolaryngol, vol. 110, pp. 493-501, 1984.   DOI
3 M. W. Skinner, L. K. Holden, L. A. Whitford, K. L. Plant, C. Psarros, and T. A. Holden, "Speech recognition with the nucleus 24 SPEAK, ACE, and CIS speech coding strategies in newly implanted adults," Ear Hear, vol. 23, pp. 207-223, 2002.
4 김진호 and 김경환, "청각신경 시냅스의 적응 효과를 이용 한 인공와우 어음처리 알고리즘의 개선에 대한 시뮬레이션 연구," 대한의용생체공학회 의공학회지, vol. 28, pp. 205- 211, 2007.
5 M. F. Dorman, P. C. Loizou, and D. Rainey, "Simulating the effect of cochlear-implant electrode insertion depth on speech understanding," J. Acoust. Soc. Am, vol. 102, pp. 2993- 2996, 1997.   DOI   ScienceOn
6 Q. J. Fu and R. V. Shannon, "Effect of stimulation rate on phoneme recognition by nucleus-22 cochlear implant listeners," J Acoust Soc Am, vol. 107, pp. 589-597, 2000.   DOI   ScienceOn
7 Q. J. Fu and R. V. Shannon, "Effects of dynamic range and amplitude mapping on phoneme recognition in Nucleus-22 cochlear implant users," Ear Hear, vol. 21, pp. 227-235, 2000.   DOI
8 J. Woo, C. A. Miller, and P. J. Abbas, "Biophysical model of an auditory nerve fiber with a novel adaptation component," IEEE Trans Biomed Eng, vol. 56, pp. 2177-2180, 2009.   DOI   ScienceOn
9 A. L. Hodgkin and A. F. Huxley, "Currents carried by sodium and patassium ions through the membrane of the giant axon of Loligo," J. Physiol., vol. 116, pp. 449-472, 1952.   DOI
10 M. C. Liberman and M. E. Oliver, "Morphometry of intracellularly labeled neurons of the auditory nerve: correlations with functional properties," J Comp Neurol, vol. 223, pp. 163-176, 1984.   DOI   ScienceOn
11 H. Mino, J. T. Rubinstein, and J. A. White, "Comparison of algorithms for the simulation of action potentials with stochastic sodium channels," Ann Biomed Eng, vol. 30, pp. 578-587, 2002.   DOI   ScienceOn
12 C. v. d. Honert and J. T. Mortimer, "The response of the myelinated nerve fiber to short duration biphasic stimulating currents," Ann Biomed Eng, vol. 7, pp. 117-125, 1979.   DOI
13 P. Loizou, "Mimicking the human ear," IEEE Signal Process. Mag., vol. 15, pp. 101-130, 1998.   DOI   ScienceOn
14 B. Kelly, "Continuous Interleaved Sampled (CIS) Signal Processing Strategy for Cochlear Implant : MATLAB Simulation Program," B.S., Bioengineering, Syracuse University, 2006.
15 Cochlear., "Nucleus Cochlear Implants:Physicians Package Insert," ed, 2010.
16 J. Woo, C. A. Miller, and P. J. Abbas, "Simulation of the electrically stimulated cochlear neuron: modeling adaptation to trains of electric pulses," IEEE Trans Biomed Eng, vol. 56, pp. 1348-1359, 2009.   DOI   ScienceOn
17 Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," IEEE Trans Image Process, vol. 13, pp. 600-612, 2004.   DOI   ScienceOn
18 F. Zhang, C. A. Miller, B. K. Robinson, P. J. Abbas, and N. Hu, "Changes across time in spike rate and spike amplitude of auditory nerve fibers stimulated by electric pulse trains," J Assoc Res Otolaryngol, vol. 8, pp. 356-372, 2007.   DOI
19 H. T. Bunnell. (1999). Available: www.asel.udel.edu/speech/tutorials/synthesis
20 D. H. Klatt, "Software for a cascade/parallel formant synthesizer," J Acoust Soc Am, vol. 67, pp. 971-995, 1980.   DOI   ScienceOn
21 P. C. Loizou, O. Poroy, and M. Dorman, "The effect of parametric variations of cochlear implant processors on speech understanding," J Acoust Soc Am, vol. 108, pp. 790-802, 2000.   DOI   ScienceOn