Title :
Separating and tracking ERP subcomponents by constrained particle filtering
Author :
Jarchi, Delaram ; Abadi, Bahador Makki ; Sanei, Saeid
Author_Institution :
Centre of Digital Signal Process., Cardiff Univ., Cardiff, UK
Abstract :
In this paper a new method based on particle filtering for separating and tracking event related-potential (ERP) subcomponents in different trials is presented. The latency and amplitude of each ERP subcomponent is formulated in the state space model. Based on some knowledge about ERP subcomponents, a constraint on the state space variables is provided to prevent the generation of invalid particles and also make use of a small number of particles which are most effective especially in high dimensions. The method is applied on the simulated and real P300 data. The algorithm has the ability of tracking P300 subcomponents i.e. P3a and P3b, in single trials even in the low signal-to-noise ratio situations.
Keywords :
bioelectric potentials; electroencephalography; medical signal processing; state-space methods; ERP separation; ERP subcomponent tracking; constrained particle filtering; electroencephalogram; event related-potential; real P300 subcomponents; state space model; Brain modeling; Delay; Digital filters; Electroencephalography; Enterprise resource planning; Filtering; Particle filters; Particle tracking; Scalp; State-space methods; Event related potential (ERP); P300; Particle filter; constraint; subcomponent;
Conference_Titel :
Digital Signal Processing, 2009 16th International Conference on
Conference_Location :
Santorini-Hellas
Print_ISBN :
978-1-4244-3297-4
Electronic_ISBN :
978-1-4244-3298-1
DOI :
10.1109/ICDSP.2009.5201049