Study on Detection of P300 ERP Component in EEG Signals and Algorithms

Abstract

Abstract.P300 Event Related Potential (ERP) has drawn much interest in different application of psychological background. An endogenous ERP component, P300, has been widely inspected in detecting deception. Detecting P300 from EEG signals is hard to find because P300 is overloaded with noise and other EEG signals. We typically use the features of the amplitude and latency of P300 to recognize P300.In this paper we are presenting several methods for the efficient detection of P300 detection algorithms such as; reconstruction algorithm for small P300 wave using Independent Component Analysis (ICA), Extreme Learning Machine (ELM) method using BackPropagation network, Multi-domain EEG signal processing. Each detection method has good effectiveness but the complexation level is dissimilar for each algorithm based on the constraints and optimal features used at the classification stage. This survey will brings you algorithms for the P300 detection and give you detail idea about the use of them.

Efficient Algorithms for E-Healthcare to Solve Multiobject Fuse Detection Problem

“…) is a neural network used as a neural forwarding network [49][50][51]. e BP algorithm has a multilayer architecture mapping, which can transmit information between the forwarding and output layers.…”