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
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;
Journal_Title :
Biomedical Engineering, IEEE Transactions on