Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design

被引:202
作者
Lotte, Fabien [1 ]
Larrue, Florian [1 ]
Muehl, Christian [1 ]
机构
[1] Inria Bordeaux Sud Ouest LaBRI, 200 Rue Vieille Tour, F-33405 Talence, France
关键词
Brain-Computer Interface; instructional design; electroencephalography; training protocols; feedback; MOTOR IMAGERY; VIRTUAL-REALITY; COMMUNICATION; EEG; FEEDBACK; BCI; PERFORMANCE; POTENTIALS; ATTENTION; DEVICE;
D O I
10.3389/fnhum.2013.00568
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
While recent research on Brain-Computer Interfaces (BCI) has highlighted their potential for many applications, they remain barely used outside laboratories. The main reason is their lack of robustness. Indeed, with current BCI, mental state recognition is usually slow and often incorrect. Spontaneous BCI (i.e., mental imagery-based BCI) often rely on mutual learning efforts by the user and the machine, with BCI users learning to produce stable ElectroEncephaloGraphy (EEG) patterns (spontaneous BCI control being widely acknowledged as a skill) while the computer learns to automatically recognize these EEG patterns, using signal processing. Most research so far was focused on signal processing, mostly neglecting the human in the loop. However, how well the user masters the BCI skill is also a key element explaining BCI robustness. Indeed, if the user is not able to produce stable and distinct EEG patterns, then no signal processing algorithm would be able to recognize them. Unfortunately, despite the importance of BCI training protocols, they have been scarcely studied so far, and used mostly unchanged for years. In this paper, we advocate that current human training approaches for spontaneous BCI are most likely inappropriate. We notably study instructional design literature in order to identify the key requirements and guidelines for a successful training procedure that promotes a good and efficient skill learning. This literature study highlights that current spontaneous BCI user training procedures satisfy very few of these requirements and hence are likely to be suboptimal. We therefore identify the flaws in BCI training protocols according to instructional design principles, at several levels: in the instructions provided to the user, in the tasks he/she has to perform, and in the feedback provided. For each level, we propose new research directions that are theoretically expected to address some of these flaws and to help users learn the BCI skill more efficiently.
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页数:11
相关论文
共 68 条
[1]   DeFT: A conceptual framework for considering learning with multiple representations [J].
Ainsworth, Shaaron .
LEARNING AND INSTRUCTION, 2006, 16 (03) :183-198
[2]   Towards an independent brain-computer interface using steady state visual evoked potentials [J].
Allison, Brendan. Z. ;
McFarland, Dennis J. ;
Schalk, Gerwin ;
Zheng, Shi Dong ;
Jackson, Melody Moore ;
Wolpaw, Jonathan R. .
CLINICAL NEUROPHYSIOLOGY, 2008, 119 (02) :399-408
[3]  
Allison BZ, 2010, HUM-COMPUT INT-SPRIN, P35, DOI 10.1007/978-1-84996-272-8_3
[4]  
Arrouet C., 2005, J NEUROTHERAPY, V9, P3, DOI [10.1300/J184v09n01\_02, DOI 10.1300/J184V09N01_]
[5]   Biased feedback in brain-computer interfaces [J].
Barbero, Alvaro ;
Grosse-Wentrup, Moritz .
JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2010, 7
[6]   A spelling device for the paralysed [J].
Birbaumer, N ;
Ghanayim, N ;
Hinterberger, T ;
Iversen, I ;
Kotchoubey, B ;
Kübler, A ;
Perelmouter, J ;
Taub, E ;
Flor, H .
NATURE, 1999, 398 (6725) :297-298
[7]   The Berlin brain-computer interface:: EEG-based communication without subject training [J].
Blankertz, Benjamin ;
Dornhege, Guido ;
Krauledat, Matthias ;
Mueller, Klaus-Robert ;
Kunzmann, Volker ;
Losch, Florian ;
Curio, Gabriel .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2006, 14 (02) :147-152
[8]   Neurophysiological predictor of SMR-based BCI performance [J].
Blankertz, Benjamin ;
Sannelli, Claudia ;
Haider, Sebastian ;
Hammer, Eva M. ;
Kuebler, Andrea ;
Mueller, Klaus-Robert ;
Curio, Gabriel ;
Dickhaus, Thorsten .
NEUROIMAGE, 2010, 51 (04) :1303-1309
[9]   Two Brains, One Game: Design and Evaluation of a Multiuser BCI Video Game Based on Motor Imagery [J].
Bonnet, Laurent ;
Lotte, Fabien ;
Lecuyer, Anatole .
IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, 2013, 5 (02) :185-198
[10]   The effects of video game playing on attention, memory, and executive control [J].
Boot, Walter R. ;
Kramer, Arthur F. ;
Simons, Daniel J. ;
Fabiani, Monica ;
Gratton, Gabriele .
ACTA PSYCHOLOGICA, 2008, 129 (03) :387-398