A fuzzy logic model for hand posture control using human cortical activity recorded by micro-ECog electrodes.
Annu Int Conf IEEE Eng Med Biol Soc
; 2009: 4339-42, 2009.
Article
em En
| MEDLINE
| ID: mdl-19963823
This paper presents a fuzzy logic model to decode the hand posture from electro-cortico graphic (ECoG) activity of the motor cortical areas. One subject was implanted with a micro-ECoG electrode array on the surface of the motor cortex. Neural signals were recorded from 14 electrodes on this array while Subject participated in three reach and grasp sessions. In each session, Subject reached and grasped a wooden toy hammer for five times. Optimal channels/electrodes which were active during the task were selected. Power spectral densities of optimal channels averaged over a time period of 1/2 second before the onset of the movement and 1 second after the onset of the movement were fed into a fuzzy logic model. This model decoded whether the posture of the hand is open or closed with 80% accuracy. Hand postures along the task time were decoded by using the output from the fuzzy logic model by two methods (i) velocity based decoding (ii) acceleration based decoding. The latter performed better when hand postures predicted by the model were compared to postures recorded by a data glove during the experiment. This fuzzy logic model was imported to MATLABSIMULINK to control a virtual hand.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Postura
/
Córtex Cerebral
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Eletroencefalografia
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Mãos
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Microeletrodos
Tipo de estudo:
Prognostic_studies
Limite:
Adolescent
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Female
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Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Ano de publicação:
2009
Tipo de documento:
Article
País de afiliação:
Estados Unidos
País de publicação:
Estados Unidos