Simulation study of FES-assisted standing up with neural network control

Author

Zhang, D.G. ; Zhu, K.Y.

Author_Institution

Dept. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore

Volume

2

fYear

2004

fDate

1-5 Sept. 2004

Firstpage

4877

Lastpage

4880

Abstract

A neural network (NN) control system is designed for the functional electrical stimulation (FES) assisted standing up. A musculoskeletal model of nine muscles and three segments is constructed for the simulation study. Each muscle is controlled by the sub-network of the functional neural network. The sub-network is the radial basis function (RBF) NN. Minimal resource allocation (M-RAN) learning algorithm is used in the RBF NN design. This system aims to reduce the upper body effort and keep the body balance when the patient stands up. Promising simulation results provide the potential for feasible clinical application in the future.

Keywords

biocontrol; bioelectric phenomena; biomechanics; learning (artificial intelligence); neuromuscular stimulation; physiological models; radial basis function networks; body balance; functional electrical stimulation-assisted standing up; minimal resource allocation learning algorithm; muscles; musculoskeletal model; neural network control; radial basis function neural nets; reduced upper body effort; Biological neural networks; Centralized control; Control systems; Hip; Joints; Knee; Muscles; Musculoskeletal system; Neural networks; Torque; FES; RBF; musculoskeletal model; neural network control; standing up;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-8439-3

Type

conf

DOI

10.1109/IEMBS.2004.1404349

Filename

1404349