Estimation of daily forearm and wrist motion from shoulder and elbow kinematics by using artificial neural networks

Subrata Kumar Kundu, Kazuo Kiguchi, Etsuo Horikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multifunctional arm prostheses have been developed since last several decades. One of the major problems that cause the loss of interest in current prostheses is the inadequate control interface between the patient and the prosthesis. The purpose of this research is to investigate the effectiveness of applying the kinematic data of the shoulder and elbow joint to control the arm prosthesis. In this paper, we propose an artificial neural network (ANN) technique to estimate the forearm and wrist motion pattern from shoulder and elbow kinematics for the control of arm prostheses. A number of activities which are essential and frequently performed in daily living are considered here and the proposed multilayer ANN is applied to classify them using the shoulder and elbow kinematics.

Original languageEnglish
Title of host publication2008 World Automation Congress, WAC 2008
Publication statusPublished - 2008
Externally publishedYes
Event2008 World Automation Congress, WAC 2008 - Waikoloa, HI, United States
Duration: Sep 28 2008Oct 2 2008

Other

Other2008 World Automation Congress, WAC 2008
CountryUnited States
CityWaikoloa, HI
Period9/28/0810/2/08

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Kundu, S. K., Kiguchi, K., & Horikawa, E. (2008). Estimation of daily forearm and wrist motion from shoulder and elbow kinematics by using artificial neural networks. In 2008 World Automation Congress, WAC 2008 [4698979]