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Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).

Brunner P, Ritaccio AL, Emrich JF, Bischof H, Schalk G - Front Neurosci (2011)

Bottom Line: The results showed that the subject sustained a rate of 17 characters/min (i.e., 69 bits/min), and achieved a peak rate of 22 characters/min (i.e., 113 bits/min).Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller BCI system.Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

View Article: PubMed Central - PubMed

Affiliation: New York State Department of Health, Brain-Computer Interface Research and Development Program, Wadsworth Center Albany, NY, USA.

ABSTRACT
A brain-computer interface (BCI) can provide a non-muscular communication channel to severely disabled people. One particular realization of a BCI is the P300 matrix speller that was originally described by Farwell and Donchin (1988). This speller uses event-related potentials (ERPs) that include the P300 ERP. All previous online studies of the P300 matrix speller used scalp-recorded electroencephalography (EEG) and were limited in their communication performance to only a few characters per minute. In our study, we investigated the feasibility of using electrocorticographic (ECoG) signals for online operation of the matrix speller, and determined associated spelling rates. We used the matrix speller that is implemented in the BCI2000 system. This speller used ECoG signals that were recorded from frontal, parietal, and occipital areas in one subject. This subject spelled a total of 444 characters in online experiments. The results showed that the subject sustained a rate of 17 characters/min (i.e., 69 bits/min), and achieved a peak rate of 22 characters/min (i.e., 113 bits/min). Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller BCI system. Our results also point to potential reasons for the apparent advantages in spelling performance of ECoG compared to EEG. Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

No MeSH data available.


Optimizing number of electrodes. The two figures show the relationship between the number of electrodes over visual cortex and accuracy (left) or bit rate (right) that this subject may achieve with these electrodes at one (blue circle), two (green triangle), and three (orange square) flash sequences. The subject may achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes.
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Figure 6: Optimizing number of electrodes. The two figures show the relationship between the number of electrodes over visual cortex and accuracy (left) or bit rate (right) that this subject may achieve with these electrodes at one (blue circle), two (green triangle), and three (orange square) flash sequences. The subject may achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes.

Mentions: To do this, in offline post hoc analyses, we evaluated spelling performance using 1–6 electrodes over visual cortex (i.e., locations A–F in Figure 5) and 1–3 flash sequences. In these analyses, we used the same calibration data as in the online experiment (i.e., “THE QUICK BROWN,” 15 flash sequences, 3/64 s flash duration). We then established one classifier for each possible combination of the 1–6 electrodes over visual cortex. For each combination, we then applied the corresponding classifier to the data from the online experiments. The results in Figure 6 and Table 2 show the relationship between the best combinations of 1–6 electrodes and spelling performance, i.e., accuracy and bit rate, for 1–3 flash sequences. The results suggest that this particular subject could achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes. Furthermore, one bipolar derivation ( between locations C and A) may already allow for 57 bits/min or 90% of the peak spelling performance supported by five electrodes (see Table 2).


Rapid Communication with a "P300" Matrix Speller Using Electrocorticographic Signals (ECoG).

Brunner P, Ritaccio AL, Emrich JF, Bischof H, Schalk G - Front Neurosci (2011)

Optimizing number of electrodes. The two figures show the relationship between the number of electrodes over visual cortex and accuracy (left) or bit rate (right) that this subject may achieve with these electrodes at one (blue circle), two (green triangle), and three (orange square) flash sequences. The subject may achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3037528&req=5

Figure 6: Optimizing number of electrodes. The two figures show the relationship between the number of electrodes over visual cortex and accuracy (left) or bit rate (right) that this subject may achieve with these electrodes at one (blue circle), two (green triangle), and three (orange square) flash sequences. The subject may achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes.
Mentions: To do this, in offline post hoc analyses, we evaluated spelling performance using 1–6 electrodes over visual cortex (i.e., locations A–F in Figure 5) and 1–3 flash sequences. In these analyses, we used the same calibration data as in the online experiment (i.e., “THE QUICK BROWN,” 15 flash sequences, 3/64 s flash duration). We then established one classifier for each possible combination of the 1–6 electrodes over visual cortex. For each combination, we then applied the corresponding classifier to the data from the online experiments. The results in Figure 6 and Table 2 show the relationship between the best combinations of 1–6 electrodes and spelling performance, i.e., accuracy and bit rate, for 1–3 flash sequences. The results suggest that this particular subject could achieve a maximum of 100% classification accuracy at three flash sequences and four electrodes, and a maximum of 64 bits/min at two flash sequences and five electrodes. Furthermore, one bipolar derivation ( between locations C and A) may already allow for 57 bits/min or 90% of the peak spelling performance supported by five electrodes (see Table 2).

Bottom Line: The results showed that the subject sustained a rate of 17 characters/min (i.e., 69 bits/min), and achieved a peak rate of 22 characters/min (i.e., 113 bits/min).Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller BCI system.Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

View Article: PubMed Central - PubMed

Affiliation: New York State Department of Health, Brain-Computer Interface Research and Development Program, Wadsworth Center Albany, NY, USA.

ABSTRACT
A brain-computer interface (BCI) can provide a non-muscular communication channel to severely disabled people. One particular realization of a BCI is the P300 matrix speller that was originally described by Farwell and Donchin (1988). This speller uses event-related potentials (ERPs) that include the P300 ERP. All previous online studies of the P300 matrix speller used scalp-recorded electroencephalography (EEG) and were limited in their communication performance to only a few characters per minute. In our study, we investigated the feasibility of using electrocorticographic (ECoG) signals for online operation of the matrix speller, and determined associated spelling rates. We used the matrix speller that is implemented in the BCI2000 system. This speller used ECoG signals that were recorded from frontal, parietal, and occipital areas in one subject. This subject spelled a total of 444 characters in online experiments. The results showed that the subject sustained a rate of 17 characters/min (i.e., 69 bits/min), and achieved a peak rate of 22 characters/min (i.e., 113 bits/min). Detailed analysis of the results suggests that ERPs over visual areas (i.e., visual evoked potentials) contribute significantly to the performance of the matrix speller BCI system. Our results also point to potential reasons for the apparent advantages in spelling performance of ECoG compared to EEG. Thus, with additional verification in more subjects, these results may further extend the communication options for people with serious neuromuscular disabilities.

No MeSH data available.