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Preprocessing by a Bayesian single-trial event-related potential estimation technique allows feasibility of an assistive single-channel P300-based brain-computer interface.

Goljahani A, D'Avanzo C, Silvoni S, Tonin P, Piccione F, Sparacino G - Comput Math Methods Med (2014)

Bottom Line: A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives.Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities.Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6/B, 35131 Padova, Italy.

ABSTRACT
A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives. Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities. Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels. By using offline data collected in 30 subjects (21 amyotrophic lateral sclerosis patients and 9 controls) through a clinical BCI with N = 5 channels, in the present paper we show that a preprocessing approach based on a Bayesian single-trial ERP estimation technique allows reducing N to 1 without affecting the system's accuracy. The potentially great benefit for the practical usability of BCI devices (including patient acceptance) that would be given by the reduction of the number N of channels encourages further development of the present study, for example, in an online setting.

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Related in: MedlinePlus

Distributions of accuracy achieved by MC and SC systems in T1,…, T4 for ALS patients (a) and controls (b). Labels Tj-MC and Tj-SC for, j = 1,…, 4, denote accuracy achieved in testing day Tj by MC and SC systems, respectively.
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fig5: Distributions of accuracy achieved by MC and SC systems in T1,…, T4 for ALS patients (a) and controls (b). Labels Tj-MC and Tj-SC for, j = 1,…, 4, denote accuracy achieved in testing day Tj by MC and SC systems, respectively.

Mentions: Numerical results in Tables 1 and 2 are graphically represented in Figure 5, where a series of box-plots are reported in two panels related to ALS patients (panel (a)) and healthy controls (panel (b)), respectively. Each box-plot is based on values from one column of the tables, that is, on the accuracy achieved in a specific testing day, Ti, i = 1,…, 4, and by a specific system, MC or SC. The lower and upper edges of the rectangles are drawn in correspondence with the 25th and 75th percentile of accuracy, respectively, and the red lines represent the median accuracy.


Preprocessing by a Bayesian single-trial event-related potential estimation technique allows feasibility of an assistive single-channel P300-based brain-computer interface.

Goljahani A, D'Avanzo C, Silvoni S, Tonin P, Piccione F, Sparacino G - Comput Math Methods Med (2014)

Distributions of accuracy achieved by MC and SC systems in T1,…, T4 for ALS patients (a) and controls (b). Labels Tj-MC and Tj-SC for, j = 1,…, 4, denote accuracy achieved in testing day Tj by MC and SC systems, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4109663&req=5

fig5: Distributions of accuracy achieved by MC and SC systems in T1,…, T4 for ALS patients (a) and controls (b). Labels Tj-MC and Tj-SC for, j = 1,…, 4, denote accuracy achieved in testing day Tj by MC and SC systems, respectively.
Mentions: Numerical results in Tables 1 and 2 are graphically represented in Figure 5, where a series of box-plots are reported in two panels related to ALS patients (panel (a)) and healthy controls (panel (b)), respectively. Each box-plot is based on values from one column of the tables, that is, on the accuracy achieved in a specific testing day, Ti, i = 1,…, 4, and by a specific system, MC or SC. The lower and upper edges of the rectangles are drawn in correspondence with the 25th and 75th percentile of accuracy, respectively, and the red lines represent the median accuracy.

Bottom Line: A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives.Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities.Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6/B, 35131 Padova, Italy.

ABSTRACT
A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives. Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities. Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels. By using offline data collected in 30 subjects (21 amyotrophic lateral sclerosis patients and 9 controls) through a clinical BCI with N = 5 channels, in the present paper we show that a preprocessing approach based on a Bayesian single-trial ERP estimation technique allows reducing N to 1 without affecting the system's accuracy. The potentially great benefit for the practical usability of BCI devices (including patient acceptance) that would be given by the reduction of the number N of channels encourages further development of the present study, for example, in an online setting.

Show MeSH
Related in: MedlinePlus