Comparison Study of Hamming and Kaiser Window over Band Pass Filter Banks in Cochlear Implant System

International Journal of Electronics and Communication Engineering

© 2019 by SSRG - IJECE Journal

Volume 6 Issue 5

Year of Publication : 2019

Authors : N. Jagan Mohan Reddy

10.14445/23488549/IJECE-V6I5P106

How to Cite?

N. Jagan Mohan Reddy, "Comparison Study of Hamming and Kaiser Window over Band Pass Filter Banks in Cochlear Implant System," SSRG International Journal of Electronics and Communication Engineering, vol. 6,  no. 5, pp. 35-44, 2019. Crossref, https://doi.org/10.14445/23488549/IJECE-V6I5P106

Abstract:

The cochlear implant is the successful neural prosthesis ever developed. This prosthesis is the most effective way to restore hearing purpose. The device is surgically implanted inside the cochlea (brain) to stimulate current pulses similar to neuron stimulation. The audio signal sensed through a microphone is amplified and digitized before the audio/speech signal processing. Continuous Interleaved Sampling (CIS) is one of the most important speech processing strategies used in the speech processors of Cochlear Implant. The speech processing ensures the splitting of the input signal into various frequency bands and provides the filtered signal to appropriate electrodes. The electrodes activate the auditory nerve fibers to provide hearing sensation. The focus of the paper is to design a bank of Band-pass Filters, which is used in the CIS algorithm for separating the frequencies for processing the signal and finally feeding it to different electrodes. Filters are targeted for audio frequencies from 200 to 7.5 kHz. MATLAB based Filter banks using Kaiser Window and Hamming window are considered for design. The center frequencies of the respective band-pass filters are taken into account to test the eight filters. In Xilinx ISE 14.7 Verilog based synthesis for bank of band-pass filters will be implemented.

Keywords:

CIS, FFT, FIR, IIR, LPC, RF.

References:

[1] Haichen Zhao and Songping Mai, “Simulation of ASIC/FPGA Cochlear Implant Speech Processor with SIMULINK and ModelsimCosimulation Method” IEEE 2013.
[2] B. Wilson, C. Finley, and D. Lawson, “Coding Strategies for multichannel cochlear prostheses,” American Journal for Otolaryngology, vol. 12, Suppl: pp. 56-61, 1991b.
[3] K. Rajalakshmi and A. Kandaswamy “VLSI Architecture of Digital Auditory Filter for Speech Processor of Cochlear Implant”, International Journal of Computer Applications (0975 – 8887) Volume 39– No.7, February 2012
[4] Mr. Y. Srinivas1, Mr. P. Darwin2, and Dr. V. Sailja3, “Continuous Interleaved Sampled (CIS) Signal Processing Strategy for Cochlear Implants MATLAB Simulation Program”, International Journal of Scientific & Engineering Research Volume 3, Issue 12, December-2012.
[5] P. Mahalakshmi and M. R. Reddy “Signal Analysis by using FIR Filter banks in Cochlear Implant Prostheses”, Proceedings of 2010 International Conference on Systems
in Medicine and Biology, 16-18 December 2010, IIT Kharagpur, India
[6] David B Grayden, Anthony N Burkitt, Owen P Kenny, Janine C Clarey, Antonio G Paolini, Graeme M Clark, ”A Cochlear Implant Speech Processing Strategy Based On An Auditory Model”
[7] G.M. Clark, Y.C. Tong, Q.R. Bailey, et al., “A multiple-channel cochlear implant”, J. Otolaryng. Soc. Aust., Vol. 4, 1978, pp.208-212.
[8] Ji-Jon Sit, Advanced Bionics, Rahul Sarpeshkar, “A cochlear-implant processor for encoding music and lowering stimulation power”, published by the IEEE 1536-1268/08 © 2008 IEEE.
[9] Eric D. Marsman, Gordon A. Carichner, SundusKubba, Michael S. McCorquodale, Robert M. Senger, Richard B. Brown, “A DSP Architecture for Cochlear Implants”, 0-7803-9390-2/06 ©2006 IEEE, ISCAS 2006.
[10] Blake S. Wilson, Michael F. Dorman “Cochlear implants: Current designs and future possibilities”, JRRD Volume 45, Number 5, 2008 Pages 695–730 Journal of Rehabilitation Research & Development
[11] BrankoSomek, SiniaFajt, Ana Dembitz, MladenIvkovi, JasminaOstoji, “Coding Strategies for Cochlear Implants”, ISSN 0005–1144, ATKAAF 47(1–2), 69–74 (2006).
[12] Blake S. Wilson, Ph.D.; Charles C. Finley, Ph.D.; Dewey T. Lawson, Ph.D.; Robert D. Wolford, MS; MariangeliZerbi, MSEE “Design and evaluation of a continuous interleaved sampling (CIS) processing strategy for multichannel cochlear implants”, Journal of Rehabilitation Research and Development Vol . 30 No. 1, 1993.
[13] Talha J. Ahmad, Hussnain Ali, Muhammad AsimAjaz and Shoab A. Khan, “Efficient Algorithm development of CIS Speech Processing Strategy for Cochlear Implants”, 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, September 2-6, 2009.
[14] Hussnain Ali, Feng Hong, John H. L. Hansen, and Emily Tobey “IMPROVING CHANNEL SELECTION OF SOUND CODING ALGORITHMS IN COCHLEAR IMPLANTS”, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[15] Philipos G. Loizon, “Mimicking the Human ear”, IEEE signal processing magazine.
[16] SalaheddineDerouiche and BachirDjedou, “Implementation Of The Development of a Filtering Algorithm to Improve The System of Hearing in Hearing Impaired With Cochlear Implant”, ICAITA, SAI, SEAS, CDKP, CMCA-2013, 2013. © CS & IT-CSCP 2013.
[17] Kingshuk Chowdhury, Rumana Hossain, Saif Ahmed, and Iqbal Rahman Rokon, “RC Servo and Stepper Motor Control Using Verilog HDL” SSRG International Journal of VLSI & Signal Processing 2.3 (2015): 18-24.