A bio-inspired filtering framework for the EMG-based control of robots

Artemiadis, P; Kyriakopoulos, K

dc.contributor.author	Artemiadis, P	en
dc.contributor.author	Kyriakopoulos, K	en
dc.date.accessioned	2014-03-01T02:51:51Z
dc.date.available	2014-03-01T02:51:51Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35686
dc.subject	Human Body	en
dc.subject	Human Motion	en
dc.subject	Motion Estimation	en
dc.subject	Probabilistic Model	en
dc.subject	Robot Arm	en
dc.subject	Skeletal Muscle	en
dc.subject	Space Use	en
dc.subject	3 dimensional	en
dc.subject	bayesian network	en
dc.subject	Real Time	en
dc.subject	Upper Limb	en
dc.title	A bio-inspired filtering framework for the EMG-based control of robots	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/MED.2009.5164702	en
heal.identifier.secondary	http://dx.doi.org/10.1109/MED.2009.5164702	en
heal.publicationDate	2009	en
heal.abstract	There is a great effort during the last decade towards building control interfaces for robots that are based on signals measured directly from the human body. In particular electromyographic (EMG) signals from skeletal muscles have proved to be very informative regarding human motion. However, this kind of interface demands an accurate decoding technique for the translation of EMG signals to	en
heal.journalName	Mediterranean Conference on Control and Automation	en
dc.identifier.doi	10.1109/MED.2009.5164702	en