An amplitude-modulated visual stimulation for reducing eye fatigue in SSVEP-based brain-computer interfaces

Clinical Neurophysiology

Volumn 125, Issue 7, 2014, Pages 1380-1391

  Chang, Min Hye ^a   Baek, Hyun Jae ^b   Lee, Seung Min ^c   Park, Kwang Suk ^d  

^a Seoul National University   (South Korea)

^b SAMSUNG Electronics   (South Korea)

^c Korea University   (South Korea)

^d Seoul National University College of Medicine   (South Korea)

Author keywords

Amplitude modulated stimulus; Brain computer interface (BCI); Electroencephalogram (EEG); Steady state visual evoked potential (SSVEP)

Indexed keywords

ADULT; ARTICLE; BRAIN COMPUTER INTERFACE; ELECTROENCEPHALOGRAM; EVOKED VISUAL RESPONSE; EYE DISEASE; EYE FATIGUE; FATIGUE; FEMALE; FREQUENCY MODULATION; HEAD MOVEMENT; HUMAN; HUMAN EXPERIMENT; MALE; MEASUREMENT ACCURACY; NEUROMODULATION; NORMAL HUMAN; ONLINE ANALYSIS; PRIORITY JOURNAL; SIGNAL NOISE RATIO; STEADY STATE VISUAL EVOKED POTENTIAL; VISUAL STIMULATION; ASTHENOPIA; CONTROLLED STUDY; ELECTROENCEPHALOGRAPHY; FEASIBILITY STUDY; PATHOPHYSIOLOGY; PHOTOSTIMULATION; PHYSIOLOGY; PROCEDURES; RANDOMIZED CONTROLLED TRIAL; YOUNG ADULT;

ADULT; ASTHENOPIA; BRAIN-COMPUTER INTERFACES; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, VISUAL; FEASIBILITY STUDIES; FEMALE; HUMANS; MALE; PHOTIC STIMULATION; YOUNG ADULT;

EID: 84901289993     PISSN: 13882457     EISSN: 18728952     Source Type: Journal    
DOI: 10.1016/j.clinph.2013.11.016     Document Type: Article

References (38)

1. Allison B., Luth T., Valbuena D., Teymourian A., Volosyak I., Graser A. BCI demographics: how many (and what kinds of) people can use an SSVEP BCI?. IEEE Trans Neural Syst Rehabil Eng 2010, 18:107-116.
2. Baek H.J., Lee H.J., Lim Y.G., Park K.S. Conductive polymer foam surface improves the performance of a capacitive EEG electrode. IEEE Trans Biomed Eng 2012, 59:3422-3431.
3. Bashashati A., Fatourechi M., Ward R.K., Birch G.E. A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals. J Neural Eng 2007, 4:R32-R57.
4. Bieger J., Molina G.G. Light stimulation properties to influence brain activity. Technical note TN-2010-00315 2010, Koninklijke Philips Electron N.V., [1-120].
5. Bin G., Gao X., Yan Z., Hong B., Gao S. An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J Neural Eng 2009, 6:1-6.
6. Cecotti H. A self-paced and calibration-less SSVEP-based brain-computer interface speller. IEEE Trans Neural Syst Rehabil Eng 2010, 18:127-133.
7. Cecotti H. Spelling with non-invasive brain-computer interfaces - current and future trends. J Physiol Paris 2011, 105:106-114.
8. Diez P.F., Mut V.A., Avila Perona E.M., Laciar Leber E. Asynchronous BCI control using high-frequency SSVEP. J Neuroeng Rehabil 2011, 8:39.
9. Fang-Cheng L., Zao J.K., Kuan-Chung T., Yijun W., Yi-Pai H., Che-Wei C., et al. SNR analysis of high-frequency steady-state visual evoked potentials from the foveal and extrafoveal regions of human retina. Conf Proc IEEE Eng Med Biol Soc 2012, 1810-1814.
10. Fatourechi M., Bashashati A., Ward R.K., Birch G.E. EMG and EOG artifacts in brain computer interface systems: a survey. Clin Neurophysiol 2007, 118:480-494.
11. Frenzel L. Principles of electronic communication systems 2007, McGraw-Hill, Inc., New York.
12. Graimann B., Allison B., Pfurtscheller G. Brain-computer interfaces: revolutionizing human-computer interaction 2010, Springer, Heidelberg.
13. Grozea C., Voinescu C.D., Fazli S. Bristle-sensor - slow-cost flexible passive dry EEG electrodes for neurofeedback and BCI applications. J Neural Eng 2011, 8:1-8.
14. Hakvoort, G, Reuderink, B, Obbink, M. Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. Technical Report TR-CTIT-11-03. Centre for Telematics and Information Technology, University of Twente; 2011: 1-12.
15. Herrmann C.S., Human E.E.G. Responses to 1-100Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena. Exp Brain Res 2001, 137:346-353.
16. Kim C.-K., Lee S., Koh D., Kim B.-M. Development of wireless NIRS system with dynamic removal of motion artifacts. Biomed Eng Lett 2011, 1:254-259.
17. Lebedev M.A., Nicolelis M.A.L. Brain-machine interfaces: past, present and future. Trends Neurosci 2006, 29:536-546.
18. Lee P.L., Sie J.J., Liu Y.J., Wu C.H., Lee M.H., Shu C.H., et al. An SSVEP-actuated brain computer interface using phase-tagged flickering sequences: a cursor system. Ann Biomed Eng 2010, 38:2383-2397.
19. Lee P.L., Yeh C.L., Cheng J.Y.S., Yang C.Y., Lan G.Y. An SSVEP-based BCI using high duty-cycle visual flicker. IEEE Trans Biomed Eng 2011, 58:3350-3359.
20. Lopez-Gordo M., Prieto A., Pelayo F., Morillas C. Use of phase in brain-computer interfaces based on steady-state visual evoked potentials. Neural Process Lett 2010, 32:1-9.
21. Luo A., Sullivan T.J. A user-friendly SSVEP-based brain-computer interface using a time-domain classifier. J Neural Eng 2010, 7:1-10.
22. Molina G.G., Mihajlovic V. Spatial filters to detect steady-state visual evoked potentials elicited by high frequency stimulation: BCI application. Biomed Tech (Berl) 2010, 55:173-182.
23. Muller S., Diez P.F., Bastos-Filho T.F., Sarcinelli-Filho M., Mut V., Laciar E. SSVEP-BCI implementation for 37-40Hz frequency range. Conf Proc IEEE Eng Med Biol Soc 2011, 6352-6355.
24. Ortner R., Allison B.Z., Korisek G., Gaggl H., Pfurtscheller G. An SSVEP BCI to control a hand orthosis for persons with tetraplegia. IEEE Trans Neural Syst Rehabil Eng 2011, 19:1-5.
25. Pasqualotto E., Federici S., Belardinelli M.O. Toward functioning and usable brain-computer interfaces (BCIs): a literature review. Disabil Rehabil Assist Technol 2012, 7:89-103.
26. Pfurtscheller G., Allison B.Z., Brunner C., Bauernfeind G., Solis-Escalante T., Scherer R., et al. The hybrid BCI. Front Neurosci 2010, 4:30.
27. Schwartz S.H., Meese T. Visual perception: a clinical orientation 2004, McGraw-Hill, New York, NY.
28. Shyu K.K., Lee P.L., Liu Y.J., Sie J.J. Dual-frequency steady-state visual evoked potential for brain computer interface. Neurosci Lett 2010, 483:28-31.
29. Shyu K., Chiu Y.J., Lee P.L., Lee M.H., Sie J.J., Wu C.H., et al. Total design of an FPGA-based brain computer interface control hospital bed nursing system. IEEE Trans Ind Electron 2013, 60:2731-2739.
30. Teng F., Choong A.M., Gustafson S., Waddell D., Lawhead P., Chen Y. Steady state visual evoked potentials by dual sine waves. Proc Ann ACM SE Reg Conf 2010, 50-53.
31. Vialatte F.-B., Maurice M., Dauwels J., Cichocki A. Steady-state visually evoked potentials: focus on essential paradigms and future perspectives. Prog Neurobiol 2010, 90:418-438.
32. Volosyak I., Valbuena D., Luth T., Malechka T., Graser A. BCI demographics II: how many (and what kinds of) people can use a high-frequency SSVEP BCI?. IEEE Trans Neural Syst Rehabil Eng 2011, 19:232-239.
33. Wang Y., Wang R.P., Gao X.R., Hong B., Gao S.K. A practical VEP-based brain-computer interface. IEEE Trans Neural Syst Rehabil Eng 2006, 14:234-239.
34. Wang Y.T., Wang Y., Jung T.P. A cell-phone-based brain-computer interface for communication in daily life. J Neural Eng 2011, 8:1-5.
35. Wilkins A., Veitch J., Lehman B. LED lighting flicker and potential health concerns: IEEE standard PAR1789 update. Proc IEEE Energy Convers Congr Expo 2010, 171-178.
36. Wilson J.J., Palaniappan R. Analogue mouse pointer control via an online steady state visual evoked potential (SSVEP) brain-computer interface. J Neural Eng 2011, 8:1-6.
37. Wolpaw J.R., Birbaumer N., Heetderks W.J., McFarland D.J., Peckham P.H., Schalk G., et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Biomed Eng 2000, 8:164-173.
38. Zheng Y., Xiaorong G., Guangyu B., Bo H., Shangkai G. A half-field stimulation pattern for SSVEP-based brain-computer interface. Conf Proc IEEE Eng Med Biol Soc 2009, 6461-6464.