This paper aims at introducing a novel approach for assisting and restoring upper arm movements in stroke patients. The presented system integrates advanced markerless motion analysis together with an artificial neural network controller for a biomechanical arm model. The keypoint of the project is to acquire kinematics information from the healthy arm of a stroke patient during planar arm movements and elaborate them in order to obtain a selfrehabilitative stimulation of the plegic arm of the same patient. The first experimental tests show good results and allow to define working direction for the extension of the work and for its application in clinical contexts.
Goffredo, M., Bernabucci, I., Schmid, M., Conforto, S., D'Alessio, T. (2006). Combining neural tracking and control to improve rehabilitation of upper limb movements in hemiplegia. In Proceedings of the 2nd International Workshop on Biosignal Processing and Classification, BPC 2006, in Conjunction with ICINCO 2006 (pp.96-105).
Combining neural tracking and control to improve rehabilitation of upper limb movements in hemiplegia
GOFFREDO M;BERNABUCCI, IVAN;SCHMID, Maurizio;CONFORTO, SILVIA;
2006-01-01
Abstract
This paper aims at introducing a novel approach for assisting and restoring upper arm movements in stroke patients. The presented system integrates advanced markerless motion analysis together with an artificial neural network controller for a biomechanical arm model. The keypoint of the project is to acquire kinematics information from the healthy arm of a stroke patient during planar arm movements and elaborate them in order to obtain a selfrehabilitative stimulation of the plegic arm of the same patient. The first experimental tests show good results and allow to define working direction for the extension of the work and for its application in clinical contexts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
