Intuitive control for robotic rehabilitation devices by human-machine interface with EMG and EEG signals

Author

Borgul, Alexandr ; Margun, Alexey ; Zimenko, Konstantin ; Kremlev, Artem ; Krasnov, Alexandr

Author_Institution

Dept. of Control Syst. & Inf., St. Petersburg Nat. Res. Univ. of Inf. Technol., Mech. & Opt., St. Petersburg, Russia

fYear

2012

fDate

27-30 Aug. 2012

Firstpage

308

Lastpage

311

Abstract

This article presents a system of intuitive control the upper extremity exoskeleton and other mechatronic devices with EMG and EEG for people with different degrees of musculoskeletal system damage. The technology let control an apparatus by thinking about it. Various identification methods for control signals like neural networks, wavelet analysis, fastICA, Fourier series are given below. Algorithms were tested on real objects and simulator.

Keywords

Fourier series; electroencephalography; electromyography; human-robot interaction; independent component analysis; medical disorders; medical robotics; medical signal processing; neurocontrollers; wavelet transforms; EEG signal; EMG signal; Fourier series; apparatus control; control signal; fastICA; human-machine interface; identification method; intuitive control; mechatronic device; musculoskeletal system damage; neural network; robotic rehabilitation device; upper extremity exoskeleton; wavelet analysis; Electroencephalography; Electromyography; Exoskeletons; Humans; Man machine systems; Noise; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Methods and Models in Automation and Robotics (MMAR), 2012 17th International Conference on

Conference_Location

Miedzyzdrojie

Print_ISBN

978-1-4673-2121-1

Type

conf

DOI

10.1109/MMAR.2012.6347901

Filename

6347901