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. - In: ATTI DELLA FONDAZIONE GIORGIO RONCHI. - ISSN 0391-2051. - 4:(2002), pp. 667-670.
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
