A Mobile Brain-Computer Interface for Clinical Applications: From the Lab to the Ubiquity
Technological advances during the last years have contributed to the development of wireless and low-cost electroencephalography (EEG) acquisition systems and mobile brain-computer interface (mBCI) applications. The most popular applications are general-purpose (e.g., games, sports, daily-life, etc.). However, clinical usefulness of mBCIs is still an open question. In this paper we present a low-cost mobile BCI application and demonstrate its potential utility in clinical practice. In particular, we conducted a study in which visual evoked potentials (VEP) of two subjects were analyzed using our mBCI application, under different conditions: inside a laboratory, walking and traveling in a car. The results show that the features of our system (level of synchronization, robustness and signal quality) are acceptable for the demanding standard required for the electrophysiological evaluation of vision. In addition, the mobile recording and cloud computing of VEPs offers a number of advantages over traditional in-lab systems. The presented mobile application could be used for visual impairment screening, for ubiquitous, massive and low-cost evaluation of vision, and as ambulatory diagnostic tool in rural or undeveloped areas.
KeywordsEEG VEP mHealth mBCI Mobile brain-computer interface Cloud-computing Clinical Ubiquity
This work was supported by Nicolo Association for the R+D in Neurotechnologies for disability, the Ministry of Economy and Competitiveness DPI2015-69098-REDT, the research project P11-TIC-7983 of Junta of Andalucia (Spain), and the Spanish National Grant TIN2015-67020-P, co-financed by the European Regional Development Fund (ERDF).
- 10.Liao, L., Chen, C., Wang, I.: Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors. J. NeuroEng. Rehabil. 9(5) (2012)Google Scholar
- 12.Wang, Y., Wang, Y., Jung, T.: A cell-phone-based braincomputer interface for communication in daily life. J. Neural Eng. (2011)Google Scholar
- 13.Brennan, C., McCullagh, P., Lightbody, G., Galway, L., Feuser, D., González, J.L., Martin, S.: Accessing tele-services using a hybrid BCI approach. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2015. LNCS, vol. 9094, pp. 110–123. Springer, Cham (2015). doi: 10.1007/978-3-319-19258-1_10 CrossRefGoogle Scholar
- 26.Julkunen, L., Tenovuo, O., Vorobyev, V., Hiltunen, J., Teräs, M., Jääskeläinen, S.K., Hämäläinen, H.: Functional brain imaging, clinical and neurophysiological outcome of visual rehabilitation in a chronic stroke patient. Restorative Neurol. Neurosci. 24(2), 123–132 (2006)Google Scholar
- 27.Van den Bruel, A., Gailly, J., Hulstaert, F., Devriese, S., Eyssen, M.: The value of EEG, evoked potentials in clinical practice, Good Clinical Practice (GCP). Brussel: Belgian Health Care Knowledge Centre (KCE), KCE report 109C, pp. 1–138 (2009)Google Scholar
- 28.Evans, A.B.: Clinical utility of evoked potentials. Medscape, 1–28 (2014)Google Scholar
- 29.Brigell, M., Kaufman, D.I., Bobak, P., Beydoun, A.: The pattern visual evoked potential. A multicenter study using standardized techniques. Ophthalmic Lit. 48(4), 308 (1995)Google Scholar