Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface
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 electroencep...
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| Published in | Journal of neural engineering Vol. 10; no. 4; pp. 46003 - 1-15 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
IOP Publishing
01.08.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1741-2560 1741-2552 1741-2552 |
| DOI | 10.1088/1741-2560/10/4/046003 |
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| 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. |
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| AbstractList | 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.
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.
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).
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. 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 super(-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 accomplishing 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. 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. 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.OBJECTIVEAt 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.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.APPROACHFive 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.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).MAIN RESULTSIndividual 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).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.SIGNIFICANCEFreely 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. |
| Author | Rogin, Eitan Shades, Kaleb Doud, Alexander He, Bin Cassady, Kaitlin LaFleur, Karl |
| AuthorAffiliation | 2 Institute for Engineering in Medicine, University of Minnesota 1 Department of Biomedical Engineering, University of Minnesota |
| AuthorAffiliation_xml | – name: 1 Department of Biomedical Engineering, University of Minnesota – name: 2 Institute for Engineering in Medicine, University of Minnesota |
| Author_xml | – sequence: 1 givenname: Karl surname: LaFleur fullname: LaFleur, Karl organization: University of Minnesota Department of Biomedical Engineering, 7-105 NHH, 312 Church Street, SE, Minneapolis, MN 55455, USA – sequence: 2 givenname: Kaitlin surname: Cassady fullname: Cassady, Kaitlin organization: University of Minnesota Department of Biomedical Engineering, 7-105 NHH, 312 Church Street, SE, Minneapolis, MN 55455, USA – sequence: 3 givenname: Alexander surname: Doud fullname: Doud, Alexander organization: University of Minnesota Department of Biomedical Engineering, 7-105 NHH, 312 Church Street, SE, Minneapolis, MN 55455, USA – sequence: 4 givenname: Kaleb surname: Shades fullname: Shades, Kaleb organization: University of Minnesota Department of Biomedical Engineering, 7-105 NHH, 312 Church Street, SE, Minneapolis, MN 55455, USA – sequence: 5 givenname: Eitan surname: Rogin fullname: Rogin, Eitan organization: University of Minnesota Department of Biomedical Engineering, 7-105 NHH, 312 Church Street, SE, Minneapolis, MN 55455, USA – sequence: 6 givenname: Bin surname: He fullname: He, Bin email: binhe@umn.edu organization: University of Minnesota Institute for Engineering in Medicine, 725 Mayo, 420 Delaware Ave SE, Minneapolis, MN 55455, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23735712$$D View this record in MEDLINE/PubMed |
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| CODEN | JNEIEZ |
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| Cites_doi | 10.1109/TBME.2007.903709 10.1016/j.ijhcs.2004.09.001 10.1016/j.clinph.2008.06.001 10.1088/1741-2560/1/3/002 10.1109/TNSRE.2012.2214789 10.1088/1741-2560/7/2/026001 10.1038/nature06996 10.1371/journal.pone.0026322 10.1109/TNSRE.2005.847386 10.1038/nature04970 10.1126/science.1070291 10.1088/1741-2560/7/3/036007 10.1016/j.brainresbull.2008.01.007 10.1109/IEMBS.2011.6091046. 10.1016/j.clinph.2004.06.022 10.1126/science.1097938 10.1016/S1388-2457(02)00057-3 10.1016/j.clinph.2010.02.157 10.1073/pnas.0403504101 10.1088/1741-2560/10/2/026014 10.1523/JNEUROSCI.02-11-01527.1982 10.1109/TNSRE.2008.2003384 10.3109/17482968.2011.572978 10.1038/nature11076 10.1088/1741-2560/6/1/016005 10.1109/86.712231 10.1016/0304-3940(93)90886-P 10.1088/1741-2560/1/1/001 10.1109/TNSRE.2010.2077654 10.1038/nature04968 10.1016/j.neuroimage.2009.10.028 10.1016/S0301-0511(03)00073-5 10.1088/1741-2560/2/4/001 10.1109/TBME.2004.827072 |
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| References | 23 24 25 Wang T (32) 2004; 1 27 28 Kronegg J Voloshynovskiy S Pun T (12) 2005 Vallabhaneni A (29) 2005 Shannon C E (26) 1964 Yuan P (39) 2013; 10 Qin L (18) 2004; 1 30 Doud A J LaFleur K Shades K Rogin E Cassady K He B (3) 2012 31 10 11 33 34 13 Qin L (19) 2005; 2 35 Georgopoulos A P (6) 1982; 2 14 Royer A (22) 2009; 6 36 16 38 17 1 2 4 5 8 9 McFarland D J (15) 2010; 7 He B (7) 2013 20 Yuan H (37) 2010; 7 21 15876616 - J Neural Eng. 2004 Mar;1(1):1-7 20876032 - IEEE Trans Neural Syst Rehabil Eng. 2010 Dec;18(6):581-9 15876632 - J Neural Eng. 2004 Sep;1(3):135-41 18394526 - Brain Res Bull. 2008 Apr 15;75(6):796-803 23033330 - IEEE Trans Neural Syst Rehabil Eng. 2012 Nov;20(6):823-35 20168002 - J Neural Eng. 2010 Apr;7(2):26001 12853169 - Biol Psychol. 2003 Jul;63(3):237-51 22596161 - Nature. 2012 May 17;485(7398):372-5 19850134 - Neuroimage. 2010 Feb 1;49(3):2596-606 12052948 - Science. 2002 Jun 7;296(5574):1829-32 15247483 - Science. 2004 Jul 9;305(5681):258-62 16838014 - Nature. 2006 Jul 13;442(7099):164-71 22046274 - PLoS One. 2011;6(10):e26322 15585584 - Proc Natl Acad Sci U S A. 2004 Dec 21;101(51):17849-54 18990646 - IEEE Trans Neural Syst Rehabil Eng. 2008 Oct;16(5):425-31 10896178 - IEEE Trans Rehabil Eng. 2000 Jun;8(2):164-73 16317229 - J Neural Eng. 2005 Dec;2(4):65-72 9749910 - IEEE Trans Rehabil Eng. 1998 Sep;6(3):326-33 18270004 - IEEE Trans Biomed Eng. 2008 Feb;55(2 Pt 1):675-82 15188875 - IEEE Trans Biomed Eng. 2004 Jun;51(6):1034-43 23953939 - Trends Cogn Sci. 2013 Oct;17(10):490-2 7143039 - J Neurosci. 1982 Nov;2(11):1527-37 19121977 - Clin Neurophysiol. 2009 Feb;120(2):239-47 20460690 - J Neural Eng. 2010 Jun;7(3):036007 12048038 - Clin Neurophysiol. 2002 Jun;113(6):767-91 21534845 - Amyotroph Lateral Scler. 2011 Sep;12(5):318-24 16003895 - IEEE Trans Neural Syst Rehabil Eng. 2005 Jun;13(2):166-71 16838020 - Nature. 2006 Jul 13;442(7099):195-8 10576479 - Clin Neurophysiol. 1999 Nov;110(11):1842-57 18621580 - Clin Neurophysiol. 2008 Sep;119(9):2159-69 18509337 - Nature. 2008 Jun 19;453(7198):1098-101 20347612 - Clin Neurophysiol. 2010 Aug;121(8):1293-303 23448963 - J Neural Eng. 2013 Apr;10(2):026014 15546783 - Clin Neurophysiol. 2004 Dec;115(12):2744-53 |
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| Snippet | Objective. At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we... At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a... |
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| SubjectTerms | 3D control Adult Aircraft - instrumentation Algorithms BCI Biofeedback, Psychology - instrumentation Biofeedback, Psychology - physiology Brain-computer interface Brain-Computer Interfaces Control systems Devices EEG Evoked Potentials - physiology Female Human Human-computer interface Humans Imagination - physiology Male Man-Machine Systems Motor Cortex - physiology motor imagery Movement - physiology Robot control Robotics Robots Task Performance and Analysis telepresence robotics Three dimensional Young Adult |
| Title | Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface |
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