Electroencephalographic Signals Acquisition for the Movement of a Wheelchair Prototype in a BCI System

Abstract

In this article, we propose a first research about the electroencephalographic signals for supporting in some person whit physical disabilities, for example, the movement of a wheelchair. The brain, along with the heart, are the most important organs of the human being is the center of the nervous system, making complex but important functions such as self-control, planning, reasoning and abstract thinking as well as vision. Addition is the organ lies the mind and consciousness of the person. A BCI system is the technique that allows the control of equipment with a proper interface with the brain once it has received the appropriate signals. The aim of this work is to lay a foundation for the development of complete support systems for mobilization of people with disabilities in Ecuador. That's why a BCI system has been developed, it shows where the reception of a cognitive response of the brain produced by the moving of a limb intention produces the movement of the hardware. In this case an electrical wheelchair, which will have the user´s affective responses and visual feedback. This work ends with comments and suggestions for further research process in this line to Ecuador.Index Terms -robotics, BCI systems, wheelchair, digital signal processing, and brain signals.I.

Control Systems and Electronic Instrumentation Applied to Autonomy in Wheelchair Mobility: The State of the Art

“…It is a hybrid system as it involves a BCI and a navigation system. A BCI is designed by Pinos et al [19] that takes signals from cognitive responses. The system used "mu" rhythms, which are the result of motor responses.…”

“…EEG headset, IMU, computer, wheelchair.Controller elaborated with three operating modes, through EEG, IMU, and cognitive mode [18]. EEG headset, computer, HMI.Adaptive algorithm with temporal oscillatory response [19]. EEG headset, sensors photoelectric sensors, Bluetooth module, computer.Multi-modal control with extraction and pattern recognition [20].…”