DocumentCode
1530359
Title
Adaptive estimation of latency change in evoked potentials by direct least mean p-norm time-delay estimation
Author
Kong, Xuan ; Qiu, Tianshuang
Author_Institution
Dept. of Electr. Eng., Northern Illinois Univ., DeKalb, IL, USA
Volume
46
Issue
8
fYear
1999
Firstpage
994
Lastpage
1003
Abstract
Evoked potentials (EP) have been widely used to quantify neurological system properties. Changes in EP latency may indicate impending neurological injury. Traditional EP analyses are developed under the condition that the background noise in EP analysis are Gaussian distributed. This paper proposes a latency change detection and estimation algorithm under α-stable noise condition, a generalization of Gaussian noise assumption. An analysis shows that the α-stable model fits the noises found in the impact acceleration experiment under study better than the Gaussian model. The robustness of the proposed algorithm is demonstrated through computer simulations and experimental data analysis under both Gaussian and α-stable noise environments.
Keywords
adaptive estimation; adaptive signal processing; bioelectric potentials; medical signal processing; /spl alpha/-stable noise environments; Gaussian model; Gaussian noise assumption; adaptive estimation; computer simulations; direct least mean p-norm time-delay estimation; evoked potentials; experimental data analysis; impending neurological injury; latency change; neurological system properties quantification; Acceleration; Adaptive estimation; Background noise; Change detection algorithms; Computer simulation; Delay; Gaussian noise; Injuries; Noise robustness; Working environment noise; Algorithms; Animals; Artifacts; Computer Simulation; Data Interpretation, Statistical; Electroencephalography; Evoked Potentials; Haplorhini; Humans; Least-Squares Analysis; Models, Neurological; Models, Theoretical; Normal Distribution; Reaction Time; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.775410
Filename
775410
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