@inproceedings{abc3972b8fff45b09a05f59161791499,
title = "Rediction of joint angle from muscle activities decoded from electrocorticograms",
abstract = "Electrocorticogram (ECoG) has drawn attention as an effective recording approach for less invasive brain-machine interfaces (BMI). Previous studies succeeded in classifying the movement direction or velocity from ECoGs. Despite such successful studies, there still remain considerable works for the purpose of realizing an ECoG-based BMI robot. Our previous study suggested and verified the method to predict multiple muscle activities from ECoG measurements. In this article, we predicted 4 DOF angle of arm from muscle activities decoded from ECoG signals. We also controlled 4 DOF robot arm using the predicted angle. Consequently, this study shows that it could derive online prediction of angle of arm from ECoG signals.",
keywords = "Brain machine interface, EMG, Electrocorticogram",
author = "Duk Shin and Chao Chen and Yasuhiko Nakanishi and Hiroyuki Kambara and Natsue Yoshimura and Hidenori Watanabe and Atsushi Nambu and Tadashi Isa and Yukio Nishimura and Yasuharu Koike",
year = "2013",
language = "English",
isbn = "9781632660251",
series = "5th International Symposium on Measurement, Analysis and Modelling of Human Functions, ISHF 2013",
publisher = "IMEKO-International Measurement Federation Secretariat",
pages = "65--66",
booktitle = "5th International Symposium on Measurement, Analysis and Modelling of Human Functions, ISHF 2013",
note = "5th International Symposium on Measurement, Analysis and Modelling of Human Functions, ISHF 2013 ; Conference date: 27-06-2013 Through 29-06-2013",
}