TY - GEN
T1 - Task based motion intention prediction with EEG signals
AU - Bandara, D. S.V.
AU - Arata, Jumpei
AU - Kigichi, Kazuo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/10/11
Y1 - 2017/10/11
N2 - EEG signal is one of the biological signals that can be useful to control wearable robotic devices, according to the human motion intention. However, the real-time estimation of the user's motion intention from EEG signals is cumbersome. The user's motion intention might not be estimated when the user does not concentrate on the control of the robot, distracted by other things or disturbed by the outside interferences. In this paper, a neural network based real-time estimation method is proposed to detect human motion intention in terms of intended task, using EEG signals. The inputs of bandpower time series signals let the neural network identify the dynamic nature of the tasks performed. Experimental details, methodology and the prediction results are presented.
AB - EEG signal is one of the biological signals that can be useful to control wearable robotic devices, according to the human motion intention. However, the real-time estimation of the user's motion intention from EEG signals is cumbersome. The user's motion intention might not be estimated when the user does not concentrate on the control of the robot, distracted by other things or disturbed by the outside interferences. In this paper, a neural network based real-time estimation method is proposed to detect human motion intention in terms of intended task, using EEG signals. The inputs of bandpower time series signals let the neural network identify the dynamic nature of the tasks performed. Experimental details, methodology and the prediction results are presented.
UR - http://www.scopus.com/inward/record.url?scp=85050246248&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050246248&partnerID=8YFLogxK
U2 - 10.1109/IRIS.2016.8066066
DO - 10.1109/IRIS.2016.8066066
M3 - Conference contribution
AN - SCOPUS:85050246248
T3 - IRIS 2016 - 2016 IEEE 4th International Symposium on Robotics and Intelligent Sensors: Empowering Robots with Smart Sensors
SP - 57
EP - 60
BT - IRIS 2016 - 2016 IEEE 4th International Symposium on Robotics and Intelligent Sensors
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016
Y2 - 17 December 2016 through 20 December 2016
ER -