Abstract
Objective. At the balanced intersection of human and machine adaptation is found the optimally functioning brain–computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional (3D) physical space using noninvasive scalp electroencephalogram (EEG) in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that the operation of a real world device has on subjects' control in comparison to a 2D virtual cursor task. Approach. Five human subjects were trained to modulate their sensorimotor rhythms to control an AR Drone navigating a 3D physical space. Visual feedback was provided via a forward facing camera on the hull of the drone. Main results. Individual subjects were able to accurately acquire up to 90.5% of all valid targets presented while travelling at an average straight-line speed of 0.69 m s−1. Significance. Freely exploring and interacting with the world around us is a crucial element of autonomy that is lost in the context of neurodegenerative disease. Brain–computer interfaces are systems that aim to restore or enhance a user's ability to interact with the environment via a computer and through the use of only thought. We demonstrate for the first time the ability to control a flying robot in 3D physical space using noninvasive scalp recorded EEG in humans. Our work indicates the potential of noninvasive EEG-based BCI systems for accomplish complex control in 3D physical space. The present study may serve as a framework for the investigation of multidimensional noninvasive BCI control in a physical environment using telepresence robotics.
Highlights
Brain-computer interfaces (BCIs) are aimed at restoring crucial functions to people that are severely disabled by a wide variety of neuromuscular disorders, and at enhancing functions in healthy individuals (Wolpaw et al, 2002; Vallabhaneni et al, 2005; He et al, 2013)
Our brain-computer interface system demonstrated the ability to acquire 25.8% of the rings that were acquired via keyboard control, which is a method considered to be the gold standard in terms of reliability and prevalence for our current interactions with computer technology
In the present study we performed an experimental investigation to demonstrate the ability for human subjects to control a robotic quadcopter in a three-dimensional physical space by means of a motor imagery EEG brain-computer interface
Summary
Brain-computer interfaces (BCIs) are aimed at restoring crucial functions to people that are severely disabled by a wide variety of neuromuscular disorders, and at enhancing functions in healthy individuals (Wolpaw et al, 2002; Vallabhaneni et al, 2005; He et al, 2013). Noninvasive BCIs have long been pursued from scalp recorded noninvasive electroencephalograms (EEGs). Among such noninvasive BCIs, sensorimotor rhythm (SMR) based BCIs have been developed using a motor imagery paradigm (Pfurtscheller et al, 1993; Wolpaw et al, 1998, 2004; Wang & He, 2004; Wang et al, 2004; Qin et al, 2004; Yuan et al, 2008, 2010a,b). The development of BCIs is aimed at providing users with the ability to communicate with the external world through the modulation of thought. Such a task is achieved through a closed loop of sensing, processing and actuation. The user can receive feedback in order to adjust his or her thoughts, and generates new and adapted signals for the BCI system to interpret
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