The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Control of an Electrical Prosthesis With an SSVEP-Based BCI
Abstract
Brain-computer interfaces (BCIs) are systems that establish a direct connection between the human brain and a computer, thus providing an additional communication channel. They are used in a broad field of applications nowadays. One important issue is the control of neuroprosthetic devices for the restoration of the grasp function in spinal-cord-injured people. In this communication, an asynchronous (self-paced) four-class BCI based on steady-state visual evoked potentials (SSVEPs) was used to control a two-axes electrical hand prosthesis. During training, four healthy participants reached an online classification accuracy between 44% and 88%. Controlling the prosthetic hand asynchronously, the participants reached a performance of 75.5 to 217.5 s to copy a series of movements, whereas the fastest possible duration determined by the setup was 64 s. The number of false negative (FN) decisions varied from 0 to 10 (the maximal possible decisions were 34). It can be stated that the SSVEP-based BCI, operating in an asynchronous mode, is feasible for the control of neuroprosthetic devices with the flickering lights mounted on its surface.
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Citations
Cites
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927
Self-citationEEG-based neuroprosthesis control: A step towards clinical practice
Müller-Putz, G. R., Scherer, R., Pfurtscheller, G., & Rupp, R. (2005) · Neuroscience Letters · doi:10.1016/j.neulet.2005.03.021 · Cited by 477
Self-citation
Cited by
Brain Computer Interfaces, a Review
Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012) · Sensors · doi:10.3390/s120201211 · Cited by 2,143
Steady-state visually evoked potentials: Focus on essential paradigms and future perspectives
Vialatte, F.-B., Maurice, M., Dauwels, J., & Cichocki, A. (2010) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2009.11.005 · Cited by 1,066
Bin, G., Gao, X., Yan, Z., Hong, B., & Gao, S. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/4/046002 · Cited by 773
A Survey of Stimulation Methods Used in SSVEP-Based BCIs
Zhu, D., Bieger, J., Garcia Molina, G., & Aarts, R. M. (2010) · Computational Intelligence and Neuroscience · doi:10.1155/2010/702357 · Cited by 654
Quo vadis artificial intelligence?
Jiang, Y., Li, X., Luo, H., Yin, S., & Kaynak, O. (2022) · Discover Artificial Intelligence · doi:10.1007/s44163-022-00022-8 · Cited by 544
Metadata
- Authors
- Muller-Putz, G. R., & Pfurtscheller, G.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2008-01
- Volume
- 55
- Issue
- 1
- Pages
- 361-364
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2150825261
- Cited by
- 589
- References
- 2
- FWCI
- 8.97
- Type
- journal article
- Language
- en
- Open access
- closed
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