Improving Ensemble Averaging by Epoch Detrending in Evoked Potentials
The objective of this work is to evaluate different detrending methods in the quality of auditory evoked responses. We compared the average responses obtained by simply removing the DC level and the linear trend, and also the estimated trends using polynomials and Fourier models up to the 8th order. Two quality measures were used to compare the results: the standard deviation ratio, as a measure of the signal-to-noise ratio, and the correlation coefficient between consecutive responses obtained under the same experimental conditions. The best results were obtained using a polynomial model of order 7.
KeywordsDetrending Ensemble averages Evoked potential CCR SDR
This work was partially supported by the Cuban National Program of Creation of an R+D Platform in Neuro-technology and by an Alexander von Humboldt Foundation Fellowship granted to C. A. Ferrer-Riesgo (Ref 3.2-1164728-CUB-GF-E).
- 1.Sörnmo, L., Laguna, P.: Bioelectrical Signal Processing in Cardiac and Neural Applications. Academic Press, London (2005)Google Scholar
- 4.Kugiumtzis, D., Tsimpiris, A.: Measures of Analysis of Time Series (MATS): a MATLAB toolkit for computation of multiple measures on time series data bases. J. Stat. Softw. 33(i.5) (2010)Google Scholar
- 7.Taboada-Crispi, A.: Improving ventricular late potentials detection effectiveness. Doctoral dissertation, Ph.D. thesis, University of New Brunswick, Canada (2002)Google Scholar
- 10.ACNS: Guideline 9C: guidelines on short-latency auditory evoked potentials. Am. Clin. Neurophysiology Soc. Guidel. 46(3), 275–286 (2006)Google Scholar
- 11.Ireland, K.H.: Can the auditory late response indicate audibility of speech sounds from hearing aids with different digital processing strategies. Doctoral dissertation, Ph.D. thesis, University of Southampton, United Kingdom (2014)Google Scholar
- 12.Rasheed, H.: A maximum likelihood method to estimate EEG evoked potentials. Doctoral dissertation, Ph.D. thesis, McGill University, Canada (1985)Google Scholar
- 16.Pander, T., Przybyla, T., Czabanski, R.: An application of the L P-norm in robust weighted averaging of biomedical signals. J. Med. Informatics Technol. 22(2), 1–8 (2013)Google Scholar
- 17.de Weerd, J.P.C.M.: Estimation of evoked potentials: a study of a posteriori ‘Wiener’ filtering and its time varying generalization. Doctoral dissertation, Ph.D. thesis, Catholic University of Nijmegen, The Netherlands (1981)Google Scholar
- 22.Gopinath, K.S.: Reduction of noise due to task correlated motion in event related overt word generation functional magnetic resonance imaging paradigms, University of Florida (2003)Google Scholar
- 27.Cabana-Pérez, I.M., Velarde-Reyes, E., Torres-Fortuny, A., Eimil-Suarez, E., García-Giró, A.: Automatic ABR detection at near-threshold intensities combining template-based approach and energy analysis. In: Torres, I., Bustamante, J., Sierra, D. (eds.) VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016. IP, vol. 60, pp. 122–125. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-4086-3_31CrossRefGoogle Scholar
- 30.Picton, T.W., Hillyard, S.A., Krausz, H.I., Galambos, R.: Human auditory evoked potentials. I: evaluation of components. Electroencephalogr. Clin. Neurophysiol. 36, 79–190 (1974)Google Scholar
- 31.British Columbia Early Hearing Programme: Audiology Assessment Protocol. V. 4.1 (2012). http://www.phsa.ca/Documents/bcehpaudiologyassessmentprotocol.pdf. Accessed 10 May 2018