Performances evaluation and optimization of brain computer interface systems in a copy spelling task

被引:38
作者
Bianchi, Luigi [1 ]
Quitadamo, Lucia Rita
Garreffa, Girolamo
Cardarilli, Gian Carlo
Marciani, Maria Grazia
机构
[1] Univ Roma Tor Vergata, Dept Neurosci, I-00133 Rome, Italy
[2] IRCCS Neurofisiopatol, Fdn Santa Lucia, I-00179 Rome, Italy
[3] Univ Roma Tor Vergata, Dept Elect Engn, I-00133 Rome, Italy
关键词
assistive communication; brain-computer interface (BCI); efficiency; optimization; performance;
D O I
10.1109/TNSRE.2007.897024
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The evaluation of the performances of brain-computer interface (BCI) systems could be difficult as a standard procedure does not exist. In fact, every research team creates its own experimental protocol (different input signals, different trial structure, different output devices, etc.) and this makes systems comparison difficult. Moreover, the great question is whether these experiments can be extrapolated to real world applications or not. To overcome some intrinsic limitations of the most used criteria a new efficiency indicator will be described and used. Its main advantages are that it can predict with a high accuracy the performances of a whole system, a fact that can be used to successfully improve its behavior. Finally, simulations were performed to illustrate that the best system is built by tuning the transducer (TR) and the control interface (CI), which are the two main components of a BCI system, so that the best TR and the best CI do not exist but just the best combination of them.
引用
收藏
页码:207 / 216
页数:10
相关论文
共 17 条
[1]  
Bianchi L, 2003, METHOD INFORM MED, V42, P104
[2]   Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis [J].
Blankertz, B ;
Dornhege, G ;
Schäfer, C ;
Krepki, R ;
Kohlmorgen, J ;
Müller, KR ;
Kunzmann, V ;
Losch, F ;
Curio, G .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2003, 11 (02) :127-131
[3]   Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms [J].
Dornhege, G ;
Blankertz, B ;
Curio, G ;
Müller, KR .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2004, 51 (06) :993-1002
[4]   Conversion of EEG activity into cursor movement by a brain-computer interface (BCI) [J].
Fabiani, GE ;
McFarland, DJ ;
Wolpaw, JR ;
Pfurtscheller, G .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2004, 12 (03) :331-338
[5]  
Gamma Erich., 1994, DESIGN PATTERNS
[6]   Graz brain-computer interface II: Towards communication between humans and computers based on online classification of three different EEG patterns [J].
Kalcher, J ;
Flotzinger, D ;
Neuper, C ;
Golly, S ;
Pfurtscheller, G .
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 1996, 34 (05) :382-388
[7]   Brain-computer interfaces -: the key for the conscious brain locked into a paralyzed body [J].
Kübler, A ;
Neumann, N .
BOUNDARIES OF CONSCIOUSNESS: NEUROBIOLOGY AND NEUROPATHOLOGY, 2005, 150 :513-525
[8]   A general framework for characterizing studies of brain interface technology [J].
Mason, SG ;
Jackson, MMM ;
Birch, GE .
ANNALS OF BIOMEDICAL ENGINEERING, 2005, 33 (11) :1653-1670
[9]   BCI Meeting 2005 -: Workshop on BCI signal processing:: Feature extraction and translation [J].
McFarland, Dennis J. ;
Anderson, Charles W. ;
Mueller, Klaus-Robert ;
Schloegl, Alois ;
Krusienski, Dean J. .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2006, 14 (02) :135-138
[10]   Clinical application of an EEG-based brain-computer interface:: a case study in a patient with severe motor impairment [J].
Neuper, C ;
Müller, GR ;
Kübler, A ;
Birbaumer, N ;
Pfurtscheller, G .
CLINICAL NEUROPHYSIOLOGY, 2003, 114 (03) :399-409