کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6268813 1614648 2014 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Computational NeuroscienceMultivariate synchronization index for frequency recognition of SSVEP-based brain-computer interface
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Computational NeuroscienceMultivariate synchronization index for frequency recognition of SSVEP-based brain-computer interface
چکیده انگلیسی


- A novel frequency recognition method (MSI) was proposed.
- MSI showed better performance than traditional method when using short length data.
- MSI showed better performance when using small number of channels.
- MSI was successfully used in online BCI experiment.

Multichannel frequency recognition methods are prevalent in SSVEP-BCI systems. These methods increase the convenience of the BCI system for users and require no calibration data. A novel multivariate synchronization index (MSI) for frequency recognition was proposed in this paper. This measure characterized the synchronization between multichannel EEGs and the reference signals, the latter of which were defined according to the stimulus frequency. For the simulation and real data, the proposed method showed better performance than the widely used canonical correlation analysis (CCA) and minimum energy combination (MEC), especially for short data length and a small number of channels. The MSI was also implemented successfully in an online SSVEP-based BCI system, thus further confirming its feasibility for application systems. Because fast and accurate recognition is crucial for practical systems, we recommend MSI as a potential method for frequency recognition in future SSVEP-BCI.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 221, 15 January 2014, Pages 32-40
نویسندگان
, , , ,