In this work authors would like to propose a novel time-frequency approach to the study of cortico-muscular coherence in the detection of movement intent and evaluation of tremor during task performed by tremorous patients. This method is based on coherence calculation from a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for the coherence will be assessed by means of a surrogate data analysis approach. Preliminary observations obtained using this method on data acquired from two tremorous patients on rest and dynamic tasks will be exposed.
Severini, G., Conforto, S., Schmid, M., D'Alessio, T. (2009). Movement Intent as Predicted by Time-Varying Cortico-Muscular Coherence Estimated through MAR Models. In Proceedings of ICRA Workshop on Wearable Robots.
Movement Intent as Predicted by Time-Varying Cortico-Muscular Coherence Estimated through MAR Models
CONFORTO, SILVIA;SCHMID, Maurizio;
2009-01-01
Abstract
In this work authors would like to propose a novel time-frequency approach to the study of cortico-muscular coherence in the detection of movement intent and evaluation of tremor during task performed by tremorous patients. This method is based on coherence calculation from a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for the coherence will be assessed by means of a surrogate data analysis approach. Preliminary observations obtained using this method on data acquired from two tremorous patients on rest and dynamic tasks will be exposed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
