02171nas a2200289   4500008004100000022001400041245012100055210006900176260001200245300001100257490000700268520128300275653001501558653003001573653001401603653002101617653002701638653001601665653001101681653002201692653003201714100002001746700002201766700002101788700002401809856004801833       2015                        eng d  a1532-821X00aToward independent home use of brain-computer interfaces: a decision algorithm for selection of potential end-users.0 aToward independent home use of braincomputer interfaces a decisi  c03/2015  aS27-320 v963 a<p>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.</p>10aAlgorithms10abrain-computer interfaces10aCognition10aDisabled Persons10aElectroencephalography10aEnvironment10aHumans10aPatient Selection10aPhysical Therapy Modalities1 aKübler, Andrea1 aHolz, Elisa, Mira1 aSellers, Eric, W1 aVaughan, Theresa, M  uhttp://www.ncbi.nlm.nih.gov/pubmed/2572154402112nas a2200289   4500008004100000022001400041245004800055210004100103260001200144300001200156490000800168520133600176653002201512653002901534653000801563653002001571653001501591653002401606100001901630700001901649700001601668700002301684700002601707700002101733700002001754856004801774       2008                        eng d  a0165-027000aAn auditory brain-computer interface (BCI).0 aauditory braincomputer interface BCI  c01/2008  a43–500 v1673 aBrain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2-3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session. Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.10aauditory feedback10abrain-computer interface10aEEG10alocked-in state10amotivation10asensorimotor rhythm1 aNijboer, Femke1 aFurdea, Adrian1 aGunst, Ingo1 aMellinger, Jürgen1 aMcFarland, Dennis, J.1 aBirbaumer, Niels1 aKübler, Andrea  uhttp://www.ncbi.nlm.nih.gov/pubmed/1739979702907nas a2200325   4500008004100000022001400041245008700055210006900142260001200211300001300223490000700236520189600243653003102139653003502170653003302205653001902238100002402257700002702281700002302308700002302331700002202354700002202376700002002398700002202418700002102440700002102461700003002482700002102512856004802533       2003                        eng d  a1534-432000aBrain-computer interface technology: a review of the Second International Meeting.0 aBraincomputer interface technology a review of the Second Intern  c06/2003  a94–1090 v113 aThis paper summarizes the Brain-Computer Interfaces for Communication and Control, The Second International Meeting, held in Rensselaerville, NY, in June 2002. Sponsored by the National Institutes of Health and organized by the Wadsworth Center of the New York State Department of Health, the meeting addressed current work and future plans in brain-computer interface (BCI) research. Ninety-two researchers representing 38 different research groups from the United States, Canada, Europe, and China participated. The BCIs discussed at the meeting use electroencephalographic activity recorded from the scalp or single-neuron activity recorded within cortex to control cursor movement, select letters or icons, or operate neuroprostheses. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI that recognizes the commands contained in the input and expresses them in device control. Current BCIs have maximum information transfer rates of up to 25 b/min. Achievement of greater speed and accuracy requires improvements in signal acquisition and processing, in translation algorithms, and in user training. These improvements depend on interdisciplinary cooperation among neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective criteria for evaluating alternative methods. The practical use of BCI technology will be determined by the development of appropriate applications and identification of appropriate user groups, and will require careful attention to the needs and desires of individual users.10aaugmentative communication10aBrain-computer interface (BCI)10aelectroencephalography (EEG)10aRehabilitation1 aVaughan, Theresa, M1 aHeetderks, William, J.1 aTrejo, Leonard, J.1 aRymer, William, Z.1 aWeinrich, Michael1 aMoore, Melody, M.1 aKübler, Andrea1 aDobkin, Bruce, H.1 aBirbaumer, Niels1 aDonchin, Emanuel1 aWolpaw, Elizabeth, Winter1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/12899247