Control of a 2 DoF robot using a brain-machine interface

Comput Methods Programs Biomed. 2014 Sep;116(2):169-76. doi: 10.1016/j.cmpb.2014.02.018. Epub 2014 Mar 12.

Abstract

In this paper, a non-invasive spontaneous Brain-Machine Interface (BMI) is used to control the movement of a planar robot. To that end, two mental tasks are used to manage the visual interface that controls the robot. The robot used is a PupArm, a force-controlled planar robot designed by the nBio research group at the Miguel Hernández University of Elche (Spain). Two control strategies are compared: hierarchical and directional control. The experimental test (performed by four users) consists of reaching four targets. The errors and time used during the performance of the tests are compared in both control strategies (hierarchical and directional control). The advantages and disadvantages of each method are shown after the analysis of the results. The hierarchical control allows an accurate approaching to the goals but it is slower than using the directional control which, on the contrary, is less precise. The results show both strategies are useful to control this planar robot. In the future, by adding an extra device like a gripper, this BMI could be used in assistive applications such as grasping daily objects in a realistic environment. In order to compare the behavior of the system taking into account the opinion of the users, a NASA Tasks Load Index (TLX) questionnaire is filled out after two sessions are completed.

Keywords: Brain–Machine Interface; Directional control; Hierarchical control; Planar robot; Support Vector Machine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain-Computer Interfaces* / statistics & numerical data
  • Electroencephalography / statistics & numerical data
  • Feedback, Sensory / physiology
  • Humans
  • Imagination / physiology
  • Robotics / instrumentation*
  • Robotics / statistics & numerical data
  • Support Vector Machine