講演抄録/キーワード |
講演名 |
2012-10-11 11:35
Continuous Estimation of Finger Joint Angles Using Inputs from an EMG-to-Muscle Activation Model ○Jimson Ngeo・Tomoya Tamei・Tomohiro Shibata(NAIST) MBE2012-39 |
抄録 |
(和) |
Surface electromyography (sEMG) signals are often used in many robot and rehabilitation applications because these reflect the motor intention of users. However, inherent problems such as electromechanical delay are present in such applications. Here, we present a method to estimate finger joint angles using a neural network with inputs obtained from an EMG-to-Activation model which parameterizes this delay. Our results show overall root-mean-square errors of 5-12% between the predicted and actual joint angles. We also show results when the proposed muscle activation input is used compared to using features used by other related studies. Finally, we compare the use of a neural network to a Gaussian Process, which is a popular nonparametric Bayesian regressor that could efficiently give better prediction in this setting. |
(英) |
Surface electromyography (sEMG) signals are often used in many robot and rehabilitation applications because these reflect the motor intention of users. However, inherent problems such as electromechanical delay are present in such applications. Here, we present a method to estimate finger joint angles using a neural network with inputs obtained from an EMG-to-Activation model which parameterizes this delay. Our results show overall root-mean-square errors of 5-12% between the predicted and actual joint angles. We also show results when the proposed muscle activation input is used compared to using features used by other related studies. Finally, we compare the use of a neural network to a Gaussian Process, which is a popular nonparametric Bayesian regressor that could efficiently give better prediction in this setting. |
キーワード |
(和) |
Surface Electromyography (sEMG) / Muscle Activation Model / Finger Joint Angles / Neural Networks / / / / |
(英) |
Surface Electromyography (sEMG) / Muscle Activation Model / Finger Joint Angles / Neural Networks / / / / |
文献情報 |
信学技報, vol. 112, no. 232, MBE2012-39, pp. 17-22, 2012年10月. |
資料番号 |
MBE2012-39 |
発行日 |
2012-10-04 (MBE) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
PDFダウンロード |
MBE2012-39 |