Title :
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
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;
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
DOI :
10.1109/MMAR.2012.6347901
