Brainâ€“Computer Interfaces - Index of

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266 J. Mellinger and G. Schalk Filters do not have their own user interface. Rather, they typically request configuration parameters from the programming framework, which will then be displayed and organized in the Operator module, with no specific programming effort required. Parameters may be of numeric or string type, and may be single values, lists, or matrices. These parameters are typically constant during one particular experimental recording session. In addition to parameters, BCI2000 supports event markers called states. These state variables encode various aspects of the state of the system during operation. They can, and typically do, change their values during a recording session. A typical application of states is to use them as event markers, encoding information about stimulation or user task for later data analysis. Similarly to parameters, states are requested by filters, and then propagated and recorded transparently by the framework. During operation, a filter may access parameters and states using a simple programming interface that allows setting and obtaining parameter and state values in a manner similar to assigning values to or from variables. The advantage of using this software infrastructure is that requested parameters automatically appear in particular tabs in the configuration dialog, that they are automatically stored in the header of the data file (so that all aspects of system configuration can be retrieved offline), and that state variables are automatically associated with data samples and stored in the data file. In other words, BCI2000 system operation, data storage, and real-time data interchange, can be adapted substantially to the needs of particular situations by only making local changes to individual BCI2000 filters within modules. 2.3 Interfacing Components For greater flexibility, BCI2000 supports interoperability with other software in various ways, both at the time of online operation and offline data analysis. These interfaces fall into the following categories (Fig. 6): 2.3.1 Data Formats BCI2000 currently implements three data formats available for storage. The first format is the BCI2000 native data format, which consists of a human-readable header, and the actual data in compact binary form. In addition to specifying details of the binary file format, the header contains all configuration parameters, providing information about all circumstances of the recording. Due to its human readable header, the BCI2000 data format is especially suited for integration into recording databases, and allows for the use of full-text searching techniques to organize and identify a large number of recordings. In addition to the native file format, two further data formats are currently supported: the European Data Format (EDF, [10]), a format especially popular in sleep research; and, building on EDF, the General Data Format for Biosignals (GDF, [29]), which is designed mainly with BCI applications in mind. Implementation of file formats is realized in particular components of the
Using BCI2000 in BCI Research 267 Source Storage Data Formats Export/Import brain signals event markers event markers Scripting Operator system configuration visualization Signal Processing Matlab processing control signals event markers event markers User Application Online data exchange Fig. 6 BCI2000 interfaces to external programs are indicated with large arrows Source module. Thus, further file formats may be added by creating new components; the effort of writing such a component is limited to implementing the output format itself, by providing code that writes incoming data into an output stream. 2.3.2 Data Exchange BCI2000 provides a MatlabTM extension (i.e., a “mex file”) that supports reading recorded BCI2000 data files directly into Matlab. Using this component, data from multiple files may be concatenated, and restricted to a range of samples within files. Parameters and states are mapped to Matlab variables, allowing to access parameter and state values by name, which results in well-understandable Matlab code. Building on that mex file, BCI2000 provides an EEGlab extension [8] that enables EEGlab to directly operate on BCI2000 data files. Other data exchange components include an export tool that translates BCI2000 data files into ASCII data, or into binary format suited for import into BrainProductsTM BrainVision Analyzer. In addition to the components provided by BCI2000 itself, the BIOSIG toolbox [30] also includes support for BCI2000 data files. 2.3.3 Matlab Filter Scripts As an alternative to writing filter code in C++, online processing of brain signals may be done using Matlab code. BCI2000 comes with a “MatlabFilter” that exposes BCI2000’s full signal processing filter interface to Matlab TM . Thus, a new signal
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THE FRONTIERS COLLECTION
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Bernhard Graimann · Brendan Alliso
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Preface It’s an exciting time to
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Contents Brain-Computer Interfaces:
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Contributors Brendan Allison Instit
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Contributors xi Femke Nijboer Insti
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List of Abbreviations ADHD Attentio
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Brain-Computer Interfaces: A Gentle
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30 J.R. Wolpaw and C.B. Boulay by b
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32 J.R. Wolpaw and C.B. Boulay 2 Br
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34 J.R. Wolpaw and C.B. Boulay Fig.
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36 J.R. Wolpaw and C.B. Boulay Sens
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38 J.R. Wolpaw and C.B. Boulay pote
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40 J.R. Wolpaw and C.B. Boulay EEG-
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42 J.R. Wolpaw and C.B. Boulay 29.
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48 G. Pfurtscheller and C. Neuper F
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80 G. Pfurtscheller et al. mode, th
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82 G. Pfurtscheller et al. Therefor
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84 G. Pfurtscheller et al. A B C 1
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86 G. Pfurtscheller et al. filters
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88 G. Pfurtscheller et al. differen
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90 G. Pfurtscheller et al. In this
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92 G. Pfurtscheller et al. Fig. 8 P
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94 G. Pfurtscheller et al. 10. D. F
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96 G. Pfurtscheller et al. 51. G. P
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98 E.W. Sellers et al. Fig. 1 Three
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100 E.W. Sellers et al. Fig. 3 Two-
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102 E.W. Sellers et al. Fig. 5 Comp
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104 E.W. Sellers et al. Fig. 7 Mont
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106 E.W. Sellers et al. fixation wa
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108 E.W. Sellers et al. 5 SMR-Based
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110 E.W. Sellers et al. 22. D.J Kru
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Detecting Mental States by Machine
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138 Y. Wang et al. which has been e
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140 Y. Wang et al. After many studi
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142 Y. Wang et al. Left Hand Right
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144 Y. Wang et al. 0-degree 60-degr
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146 Y. Wang et al. 3.1.2 Stimulatio
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148 Y. Wang et al. Foot 1 0.5 Left
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150 Y. Wang et al. be summarized as
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152 Y. Wang et al. Fig. 10 A player
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154 Y. Wang et al. 22. Y. Wang, R.
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156 N. Birbaumer and P. Sauseng C A
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158 N. Birbaumer and P. Sauseng 3 B
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160 N. Birbaumer and P. Sauseng pat
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162 N. Birbaumer and P. Sauseng Fig
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164 N. Birbaumer and P. Sauseng of
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166 N. Birbaumer and P. Sauseng Neu
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168 N. Birbaumer and P. Sauseng 8.
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Non Invasive BCIs for Neuroprosthes
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204 D.M. Taylor and M.E. Stetner mo
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322 Y. Li et al. is small and the n
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324 Y. Li et al. (ROC) analysis app
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328 Y. Li et al. 6. M. Cheng, X. Ga
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332 A. Schlögl et al. Fig. 1 Schem
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340 A. Schlögl et al. yk = a1 · y
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342 A. Schlögl et al. d{i}(x) = ((
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Toward Ubiquitous BCIs Brendan Z. A
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Toward Ubiquitous BCIs 359 BCI Chal
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Toward Ubiquitous BCIs 361 communic
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Toward Ubiquitous BCIs 363 facial m
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Toward Ubiquitous BCIs 365 The best
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Toward Ubiquitous BCIs 367 Across a
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Toward Ubiquitous BCIs 369 the ques
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Toward Ubiquitous BCIs 371 controll
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Toward Ubiquitous BCIs 373 controls
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Toward Ubiquitous BCIs 375 hair in
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Toward Ubiquitous BCIs 377 Table 1
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Toward Ubiquitous BCIs 379 conversa
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Toward Ubiquitous BCIs 381 may down
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Toward Ubiquitous BCIs 383 physicis
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Toward Ubiquitous BCIs 385 31. F.H.
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Toward Ubiquitous BCIs 387 67. G. S
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390 Index 65, 157, 163, 217, 221-23
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392 Index 208, 236, 243, 245, 260-2
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