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Signal-to-Noise Ratios Performances of Various Filtering approaches for Speech-Auditory Brainstem Responses of Human Subjects Yule-Walk multiband filter, Cascaded Yule-Walk-Comb-Peak filter, Wavelet filters, Translation-Invariant Wavelet estimation filtering

 School of Information Technology and Engineering, University of Ottawa, Canada; Department of Electronics and Communications Engineering, ICFAI Foundation for Higher Education Deemed University, Hyderabad, Telangana, India

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0976-8580.158562

This paper presents the design of different filtering techniques for the Neuro-Biomedical signals in single electrode electroencephalogram collected brainstem speech evoked potentials data of audiology for the signal-to-noise ratio (SNR) performance evaluations. We have designed Yule-Walk multiband filter, cascaded Yule-Walk-Comb-Peak filter; conventional wavelet transform filters of Daubechies, Symlet, Coiflet wavelets for these auditory brainstem responses. In addition, we have designed a translation-invariant (TI) wavelet estimation filtering technique that is highly useful. In our research, the idea of cascaded Yule-Walk-Comb-Peak filter is giving us a considerable improvement in SNR over Yule-Walk filter; and the conventional wavelets are performing far better that too specifically Daubechies wavelets are performing better than all. The TI wavelets technique is performing exceptionally well and better than conventional wavelets.

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