Latency change detection in evoked potentials by direct least mean p-norm adaptive time delay estimation

Evoked potentials (EP) have been widely used to quantify neurological system properties. Changes in EP latency may be linked to neurological injuries. Many traditional EP analysis methods are developed under the condition that the additive background EEG noises are Gaussian. This paper proposes a latency change detection and estimation algorithm under the α-stable noise condition, a generalization of Gaussian noise assumption. An analysis shows that the α-stable model fits the noises from an impact acceleration experiment better than the Gaussian model. The robustness of the proposed algorithm is demonstrated through computer simulations and experimental data analysis, while traditional time delay estimation algorithm fails to yield an accurate estimate of the latency changes under lower-order α-stable noise conditions