Title :
Automated oscillatory potential detection and parameter extraction in the electroretinogram
Author :
Meklenburg, J. ; Clancy, E.A. ; Tzekov, R.
Author_Institution :
Dept. Electr. & Comp. Eng., Worcester Polytech. Inst., Worcester, MA, USA
Abstract :
The oscillatory potentials (OPs) of the electroretinogram (ERG) have long been used to study the progression of a number of retinal disorders. The OP parameters used in these studies are difficult to evaluate directly from the unconditioned ERG signal. Automated OP detection software was developed in MATLAB to extract the OP wavelets, identify peaks, and extract parameters of interest including the implicit time and amplitude of each OP along with the noise-adjusted RMS value of the entire OP signal. The cutoff frequency for OP filtering was determined adaptively for each record based on the characteristics of the Discrete Fourier Transform of the ERG. Preliminary testing of the software was conducted using mouse data.
Keywords :
bioelectric potentials; discrete Fourier transforms; electroretinography; filtering theory; mathematics computing; medical disorders; medical signal detection; medical signal processing; ERG; MATLAB; automated oscillatory potential detection; cutoff frequency; discrete Fourier transform; electroretinogram; filtering; noise-adjusted RMS value; parameter extraction; peak identification; retinal disorders; wavelet extraction; Band pass filters; Cutoff frequency; Discrete Fourier transforms; Electric potential; Filtering algorithms; Mice; Software;
Conference_Titel :
Bioengineering Conference (NEBEC), 2011 IEEE 37th Annual Northeast
Conference_Location :
Troy, NY
Print_ISBN :
978-1-61284-827-3
DOI :
10.1109/NEBC.2011.5778637
