In this paper, we report on a biomedical engineering research project we are carrying out in coopertion with Duke University, Durham, NC, USA. The neural schemes implementing Indipendent Component Analysis (ICA) are used in order to process a vector of experimental electro-myographic data coming from surface sensors. Previous works on the subject used directly sEMG data from muscles thus generating cross-talk. Also, sEMG data are combined with fMRI data with the aim of correlating muscular to cortical activity.
Neural Independent Component Analysis of Experimental Electro-Myographic Data from non-Invasive Surface Sensors
MORABITO, Francesco Carlo;VERSACI, Mario
2002-01-01
Abstract
In this paper, we report on a biomedical engineering research project we are carrying out in coopertion with Duke University, Durham, NC, USA. The neural schemes implementing Indipendent Component Analysis (ICA) are used in order to process a vector of experimental electro-myographic data coming from surface sensors. Previous works on the subject used directly sEMG data from muscles thus generating cross-talk. Also, sEMG data are combined with fMRI data with the aim of correlating muscular to cortical activity.File in questo prodotto:
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