Authors:
Samuel Bustamante
;
Juan C. Yepes
;
Vera Z. Pérez
and
Julio C. Correa
Affiliation:
Universidad Pontificia Bolivariana, Colombia
Keyword(s):
Methodology, Neural Interface Systems, Surface Electromyography, Upper Limb Prostheses, Rehabilitation, Signal Processing, Myoelectric Control.
Related
Ontology
Subjects/Areas/Topics:
Animation and Simulation
;
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Motion Control
;
Real-Time Systems
Abstract:
Neural interface systems (NISs) are widely used in rehabilitation and upper limb prosthetics. These systems
usually involve robots, such as robotic exoskeletons or electric arms, as terminal devices. We propose a
methodology to assess the feasibility of implementing these kind of neural interfaces by means of an online
kinematic simulation of the robot. It allows the researcher or developer to make tests and improve the design
of the mechatronic devices when they have not been built yet or are not available. Moreover, it may be used
in biofeedback applications for rehabilitation. The simulation makes use of the CAD model of the robot, its
Denavit–Hartenberg parameters, and biosignals recorded from a human being. The proposed methodology
was tested using surface electromyography signals acquired from the upper limb of a 25-year-old healthy
male. Both real-time and prerecorded signals were used. The robot simulated was the commercial robotic arm
KUKA KR6. The tests proved that the onli
ne simulation can be effectively implemented and controlled by
means of a biosignal.
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