A Noninvasive Brain-Actuated Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation

Abstract

Abstract-This paper describes a new noninvasive brainactuated wheelchair that relies on a P300 neurophysiological protocol and automated navigation. When in operation, the user faces a screen displaying a real-time virtual reconstruction of the scenario and concentrates on the location of the space to reach. A visual stimulation process elicits the neurological phenomenon, and the electroencephalogram (EEG) signal processing detects the target location. This location is transferred to the autonomous navigation system that drives the wheelchair to the desired location while avoiding collisions with obstacles in the environment detected by the laser scanner. This concept gives the user the flexibility to use the device in unknown and evolving scenarios. The prototype was validated with five healthy participants in three consecutive steps: screening (an analysis of three different groups of visual interface designs), virtual-environment driving, and driving sessions with the wheelchair. On the basis of the results, this paper reports the following evaluation studies: 1) a technical evaluation of the device and all functionalities; 2) a users' behavior study; and 3) a variability study. The overall result was that all the participants were able to successfully operate the device with relative ease, thus showing a great adaptation as well as a high robustness and low variability of the system.

A hybrid BCI for enhanced control of a telepresence robot

“…One of the most significant challenges currently faced is that in addition to high accuracy in the decoding of mental commands, fast decision-making and split attention are critical [1], [2], [3]. There have been several demonstrations of such braincontrolled devices, ranging from robotic arms [4], [5], to hand orthoses [6], [7]; and from telepresence robots [1], [8], to wheelchairs [9], [10], [11]. These works predominantly take spontaneous approaches, where the subjects learn to voluntarily modulate their sensorimotor brain activity.…”

A Framework for Processing Brain Waves Used in a Brain-computer Interface

“…The interface has been used to control wheelchairs for the physically challenged [2] and to control robot arms [3]. The recent launch of BCI devices [4,5] at moderate prices has stimulated studies on approaches to developing games that use the brain waves measured by the BCI [6,7].…”

Regularized logistic regression and multiobjective variable selection for classifying MEG data

“…Brain computer interfaces (BCIs) (Lebedev and Nicolelis 2006;Wolpaw et al 2002) can translate electrical signals into commands without the need for motor intervention. They have been used intensively to provide communication and control to people with severe muscular or neural handicaps (Hoffmann et al 2008;Iturrate et al 2009;Nicolelis 2003), but they can also be used, for example, to conduct cognitive experiments (Carmena et al 2003;Tan et al 2009), improve human behavior, and facilitate interaction in special environments (Rossini et al 2009), etc. For analysis, a BCI can be divided into a signal acquisition module and a signal processing module (Wolpaw et al 2002). Signal acquisition is executed using electroencephalography (EEG), MEG, or other techniques for recording brain activity.…”