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Lu C.-K.,Chyao Shiunn Electronic Industrial Ltd. | Lu C.-K.,Chang Gung Memorial Hospital | Huang Y.-C.,Chyao Shiunn Electronic Industrial Ltd. | Huang Y.-C.,Chang Gung Memorial Hospital | And 2 more authors.
Neurocomputing | Year: 2015

As seniors are the fastest growing populations in the world, walking assistive robots have recently received much attention. In this paper, we proposed an effective motion guidance system equipped upon a robotic walking assistant to emulate the biological rhythm for the practical daily use. This system consists of a pair of force-sensing handles for measuring user's applied force and an intelligent learning scheme to derive the proper driving force from the measured grip force. The handles are designed to be of low cost and with high reliability. The learning scheme is combined with an assistive strategy offering adaptive motion guidance for the various elderly in walking. The feasibility of the proposed system is demonstrated via a series of movement assistance experiments based on a developed walking robot. © 2015 Elsevier B.V.

Lu C.-K.,Chyao Shiunn Electronic Industrial Ltd. | Huang Y.-C.,Advanced Semiconductor Engineering Inc. | Lee C.-J.,Memorial Hospital | Yang Z.,Middlesex University
Electronics Letters | Year: 2014

A simple yet effective method to reduce the dimensions of the input variables and is adaptive to various users for intelligent controllers is proposed. The method has been developed specifically to address the challenge due to fuzziness in the system inputs, especially when studying the relationship of a large mapping between input variables and system response outputs. The proposed method exploits the principal components analysis to reduce the number of inputs and uses a fuzzy c-means technique to cluster them. The objective is to extract significant principal components for adaptive neural fuzzy inference systems (ANFIS) learning. The method has been applied to a robotic walker system for elderly movement assistance. Experimental results demonstrate the feasibility of the proposed method. © The Institution of Engineering and Technology 2014.

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