[1] Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M., Brain computer interfaces for communication and control; Clin. Neurophysiol., 2002; 113: 767–791.
[2] Muller-Putz J.R., Scherer R., Pfurtscheller G., Game-like training to learn single switch operated neuroprosthetic control; Int. Conf. Adv. Comput. Entertainment Technol. Workshop. BrainPlay’07: playing with your brain (brain–computer interfaces and games), 2007: 49–51.
[3] Thorpe J., Oorchot P., Somayaji A., Pass-thoughts: authenticating with our minds; Proc new Secur paradigms workshop, 2005.
[4] Scherer R., Schlogl A., Lee F., Bischof H., Jansa J., Pfurtscheller G., The self-paced Graz brain–computer interface: methods and applications; J. Comput. Intell. Neurosci., 2007; 79825.
[5] Townsend G., Graimann B., Pfurtscheller G., Continuous EEG Classification During Motor Imagery—Simulation of an Asynchronous BCI; IEEE Trans. Neural, Rehab., 2006; 12: 258-265.
[6] Mason S.G., Birch G.E., A brain-controlled switch for asynchronous control applications; IEEE Trans. Biomed. Eng., 2000; 47: 1297–1307.
[7] Fatourechi M., Ward R.K., Birch G.E., A self-paced brain–computer interface system with a low false positive rate; J. Neural Eng., 2008; 5: 9-23.
[8] Bashashati A., Mason S., Ward R.K., Birch G.E., An improved asynchronous brain interface: making use of the temporal history of the LF-ASD feature vectors; J. Neural. Eng., 2006; 3: 87-94.
[9] Pfurtscheller G., Lopes da Silva F.H., Event-related EEG/MEG synchronization and desynchronization: basic principles; Clin Neurophysiol, 1999; 110: 1842-57.
[10] Leeb R., Friedman D., Müller-Putz G.R., Scherer R., Slater M., Pfurtscheller G., Self-paced (asynchronous) BCI control of a wheelchair in virtual environments: A case study with a Tetraplegic Computational Intelligence and Neuroscience special issue: Brain-Computer Interfaces; Towards Practical Implementations and Potential Applications, 2007: 1-8.
[11] Hasan B.A.S, Gan J.Q., Unsupervised movement onset detection from EEG recorded during self-paced real hand movement; Med. Biol. Eng. Comput., 2010; 48: 245-53.
[12] Wright J., Yang A.Y., Ganesh A., Sastry S.S., Ma Y., Robust face recognition via sparse representation; IEEE Trans. Pattern Anal. Mach. Intell., 2009; 31: 210–27.
[13] Chen S., Donoho D., Saunders M., Atomic decomposition by basis pursuit; SIAM Rev., 2001; 43: 129–59.
[14] Gemmeke J.F., Virtanen T., Hurmalainen A., Exemplar-based sparse representations for noise robustautomatic speech recognition; IEEE Trans. Audio Speech Lang. Process., 2011; 19: 2067–80.
[15] Li Y., Guan C., Qin J., Enhancing feature extraction with sparse component analysis for brain–computer interface; Proc. 27th Annual Int. Conf. of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), 2005: 5335–5338.
[16] Arvaneh M., Guan C., Ang K.K., Quek H.C., Spatially sparsed common spatial pattern to improve BCI performance; Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP 2011), 2011: 2412–2415.
[17] Yu H., Lu H., Ouyang T., Liu H., Lu B.L., Vigilance detection based on sparse representation of EEG; Proc. 32nd Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBC 2010), 2010: 2439–2442.
[18] Solis-Escalante T., Muller-Putz G.R., Pfurtscheller G., Overt foot movement detection in one single Laplacian EEG derivation; J. Neurosci. Methods, 2008; 175: 148-153.
[19] Mohammadi R., Mahlooji A., Coyle D., A Combination of Pre- and Postprocessing Techniques to Enhance Self-Paced BCIs; Advances in humn-computer interaction, 2012; Article ID 185320.
[20] Schlogl A., Brunner C., Scherer R., Glatz A., BioSig: an open-source software library for BCI research; In Towards brain–computer interfacing, 2007; 20: MIT Press. p. 347–58.
[21] Graimann B., Huggins J.E., Levine S.P., Pfurtscheller G., Visualization of significant ERD/ERS patterns in multichannel EEG and ECoG data; Clin. Neurophysiol., 2002; 113(1): 43–47.
[22] Sadeghian E.B., Moradi M.H., fractal dimension for detection of ERD/ERS patterns in asynchronous brain computer interface; The 2th Int. Conf. Bioinfo. Biomed. Eng., May 16-18, 2008.
[23]
Shin Y.,
Lee S.,
Lee J.,
Lee H.N., Sparse representation-based classification scheme for motor imagery-based brain-computer interface systems;
J Neural Eng., 2012; no.9;056002.
[24] Donoho D., Stodden V., Tsaig Y., SparseLab: http://sparselab.stanford.edu/.
[25] Townsend G., Graimann B., Pfurtscheller G., Continuous EEG Classification During Motor Imagery—Simulation of an Asynchronous BCI; IEEE Trans. Neural, Rehab., 2006; 12: 258-265.