In this work, an optical myography system is demonstrated as an innovative and promising alternative to recover gesture information. During the experiments, a total of eight different postures were defined to evaluate the sensor performance. A classifier based on artificial neural network was...

In this work, an optical myography system is demonstrated as an innovative and promising alternative to recover gesture information. During the experiments, a total of eight different postures were defined to evaluate the sensor performance. A classifier based on artificial neural network was trained and validated, showing an average precision of ~92% and accuracy of ~98%.

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

2014/25080-0

Fechado