%0 Journal Article %J Arch Phys Med Rehabil %D 2015 %T Toward independent home use of brain-computer interfaces: a decision algorithm for selection of potential end-users. %A Kübler, Andrea %A Holz, Elisa Mira %A Sellers, Eric W %A Theresa M Vaughan %K Algorithms %K brain-computer interfaces %K Cognition %K Disabled Persons %K Electroencephalography %K Environment %K Humans %K Patient Selection %K Physical Therapy Modalities %X

Noninvasive brain-computer interfaces (BCIs) use scalp-recorded electrical activity from the brain to control an application. Over the past 20 years, research demonstrating that BCIs can provide communication and control to individuals with severe motor impairment has increased almost exponentially. Although considerable effort has been dedicated to offline analysis for improving signal detection and translation, far less effort has been made to conduct online studies with target populations. Thus, there remains a great need for both long-term and translational BCI studies that include individuals with disabilities in their own homes. Completing these studies is the only sure means to answer questions about BCI utility and reliability. Here we suggest an algorithm for candidate selection for electroencephalographic (EEG)-based BCI home studies. This algorithm takes into account BCI end-users and their environment and should assist in study design and substantially improve subject retention rates, thereby improving the overall efficacy of BCI home studies. It is the result of a workshop at the Fifth International BCI Meeting that allowed us to leverage the expertise of multiple research laboratories and people from multiple backgrounds in BCI research.

%B Arch Phys Med Rehabil %V 96 %P S27-32 %8 03/2015 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/25721544 %N 3 Suppl %R 10.1016/j.apmr.2014.03.036 %0 Journal Article %J Amyotroph Lateral Scler Frontotemporal Degener %D 2014 %T Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis. %A McCane, Lynn M %A Sellers, Eric W %A Dennis J. McFarland %A Mak, Joseph N %A Carmack, C Steve %A Zeitlin, Debra %A Jonathan Wolpaw %A Theresa M Vaughan %K Adult %K Aged %K Amyotrophic Lateral Sclerosis %K Biofeedback, Psychology %K brain-computer interfaces %K Communication Disorders %K Electroencephalography %K Event-Related Potentials, P300 %K Female %K Humans %K Male %K Middle Aged %K Online Systems %K Photic Stimulation %K Psychomotor Performance %K Reaction Time %X Brain-computer interfaces (BCIs) might restore communication to people severely disabled by amyotrophic lateral sclerosis (ALS) or other disorders. We sought to: 1) define a protocol for determining whether a person with ALS can use a visual P300-based BCI; 2) determine what proportion of this population can use the BCI; and 3) identify factors affecting BCI performance. Twenty-five individuals with ALS completed an evaluation protocol using a standard 6 × 6 matrix and parameters selected by stepwise linear discrimination. With an 8-channel EEG montage, the subjects fell into two groups in BCI accuracy (chance accuracy 3%). Seventeen averaged 92 (± 3)% (range 71-100%), which is adequate for communication (G70 group). Eight averaged 12 (± 6)% (range 0-36%), inadequate for communication (L40 subject group). Performance did not correlate with disability: 11/17 (65%) of G70 subjects were severely disabled (i.e. ALSFRS-R < 5). All L40 subjects had visual impairments (e.g. nystagmus, diplopia, ptosis). P300 was larger and more anterior in G70 subjects. A 16-channel montage did not significantly improve accuracy. In conclusion, most people severely disabled by ALS could use a visual P300-based BCI for communication. In those who could not, visual impairment was the principal obstacle. For these individuals, auditory P300-based BCIs might be effective. %B Amyotroph Lateral Scler Frontotemporal Degener %V 15 %P 207-15 %8 06/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24555843 %N 3-4 %R 10.3109/21678421.2013.865750