@inproceedings{b78f216d00d84056bc01e59a4aa6d804,
title = "Design of assistive torque for a lower limb exoskeleton based on motion prediction",
abstract = "This paper presents a method to generate assistive torque to a lower limb exoskeleton using a predictive approach. A control scheme is proposed to predict the suitable force of next movement of legs using gait information. By using human walking gait cycle and Center of Pressure (CoP), it is expected that the exoskeleton can provide an assistive force to people and help them to walk normally. In order to predict the next movement for assistive torque given by exoskeleton to the human, a predictive Artificial Neural Network (pANN) is developed. A prototype lower limb exoskeleton has been designed and constructed for experimental study. The controller is implemented by using LabVIEW programming. The experimental results verified that the proposed controller can provide proper assistive torques to hip and knee joints for both legs while wearing the exoskeleton.",
keywords = "Artificial Neural Network, Exoskeleton, Gait motion prediction, Walking gait",
author = "Susanto and Riska Analia and Kai-Tai Song",
year = "2016",
month = nov,
day = "18",
doi = "10.1109/SICE.2016.7749261",
language = "English",
series = "2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "172--177",
booktitle = "2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016",
address = "United States",
note = "null ; Conference date: 20-09-2016 Through 23-09-2016",
}