Brain-computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users
Open accessAbstract
Objective Connect-Four, a new sensorimotor rhythm (SMR) based brain-computer interface (BCI) gaming application, was evaluated by four severely motor restricted end-users; two were in the locked-in state and had unreliable eye-movement.Methods Following the user-centred approach, usability of the BCI prototype was evaluated in terms of effectiveness (accuracy), efficiency (information transfer rate (ITR) and subjective workload) and users' satisfaction.Results Online performance varied strongly across users and sessions (median accuracy (%) of end-users: A=.65; B=.60; C=.47; D=.77). Our results thus yielded low to medium effectiveness in three end-users and high effectiveness in one end-user. Consequently, ITR was low (0.05-1.44bits/min). Only two end-users were able to play the game in free-mode. Total workload was moderate but varied strongly across sessions. Main sources of workload were mental and temporal demand. Furthermore, frustration contributed to the subjective workload of two end-users. Nevertheless, most end-users accepted the BCI application well and rated satisfaction medium to high. Sources for dissatisfaction were (1) electrode gel and cap, (2) low effectiveness, (3) time-consuming adjustment and (4) not easy-to-use BCI equipment. All four end-users indicated ease of use as being one of the most important aspect of BCI.Conclusion Effectiveness and efficiency are lower as compared to applications using the event-related potential as input channel. Nevertheless, the SMR-BCI application was satisfactorily accepted by the end-users and two of four could imagine using the BCI application in their daily life. Thus, despite moderate effectiveness and efficiency BCIs might be an option when controlling an application for entertainment.
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Mutual learning has been claimed mostly on the grounds of adequate and improved BCI classification accuracy or application performances.
“Indeed, mutual learning has been claimed mostly on the grounds of adequate and improved BCI classification accuracy [25,27,30–35] or application performances [36,37].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [33]
Evidence that co-adaptive MI BCIs might also be able to promote and increase the ability of users to voluntarily modulate their brain signals (subject learning) is scarce, most often indirect and rather inconclusive.
“Evidence that co-adaptive MI BCIs might also be able to promote and increase the ability of the users to voluntary modulate their brain signals (subject learning) is, in fact, scarce, most often indirect and rather inconclusive.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [33]
Other training studies claim learnability in BCIs only on the grounds of improved online classification accuracy or application performances.
“Secondly, other training studies claim learnability in BCIs only on the grounds of improved online classification accuracy [9,27,30,31,33,35,51] or application performances [36,37].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [33]
Cites
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267 · see citing works
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927 · see citing works
Event-related EEG/MEG synchronization and desynchronization: basic principles
Pfurtscheller, G., & Lopes da Silva, F. H. (1999) · Clinical Neurophysiology · doi:10.1016/s1388-2457(99)00141-8 · Cited by 7,328 · see citing works
Optimizing Spatial filters for Robust EEG Single-Trial Analysis
Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., & Muller, K.-R. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2008.4408441 · Cited by 2,080 · see citing works
Neuromorphic Silicon Neuron Circuits
Indiveri, G., Linares-Barranco, B., Hamilton, T. J., André, V. S., Etienne‐Cummings, R., Delbrück, T., Liu, S., Dudek, P., Hafliger, P. D., Renaud, S., et al. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00073 · Cited by 1,836 · see citing works
Single-trial analysis and classification of ERP components — A tutorial
Blankertz, B., Lemm, S., Treder, M., Haufe, S., & Müller, K.-R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.048 · Cited by 1,138 · see citing works
Brain–Computer InterfacesPrinciples and Practice
Wolpaw, J. R., & Wolpaw, E. W. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388855.001.0001 · Cited by 1,114 · see citing works
A comparison of classification techniques for the P300 Speller
Krusienski, D. J., Sellers, E. W., Cabestaing, F., Bayoudh, S., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2006) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/4/007 · Cited by 762 · see citing works
A P300-based brain–computer interface for people with amyotrophic lateral sclerosis
Nijboer, F., Sellers, E. W., Mellinger, J., Jordan, M. A., Matuz, T., Furdea, A., Halder, S., Mochty, U., Krusienski, D. J., Vaughan, T. M., et al. (2008) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.03.034 · Cited by 633 · see citing works
Self-citationBrain-computer communication: Unlocking the locked in.
Kübler, A., Kotchoubey, B., Kaiser, J., Wolpaw, J. R., & Birbaumer, N. (2001) · Psychological Bulletin · doi:10.1037/0033-2909.127.3.358 · Cited by 554 · see citing works
Self-citationPatients with ALS can use sensorimotor rhythms to operate a brain-computer interface
Kübler, A., Nijboer, F., Mellinger, J., Vaughan, T. M., Pawelzik, H., Schalk, G., McFarland, D. J., Birbaumer, N., & Wolpaw, J. R. (2005) · Neurology · doi:10.1212/01.wnl.0000158616.43002.6d · Cited by 539 · see citing works
Self-citationKübler, A., & Birbaumer, N. (2008) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.06.019 · Cited by 441 · see citing works
Self-citation(1993) · Beltz eBooks · Cited by 409 · see citing works
A brain-computer interface for long-term independent home use
Sellers, E. W., Vaughan, T. M., & Wolpaw, J. R. (2010) · Amyotrophic Lateral Sclerosis · doi:10.3109/17482961003777470 · Cited by 400 · see citing works
Brain-computer communication: Self-regulation of slow cortical potentials for verbal communication
Kübler, A., Neumann, N., Kaiser, J., Kotchoubey, B., Hinterberger, T., & Birbaumer, N. (2001) · Archives of Physical Medicine and Rehabilitation · doi:10.1053/apmr.2001.26621 · Cited by 351 · see citing works
Self-citationPiccione, F., Giorgi, F., Tonin, P., Priftis, K., Giove, S., Silvoni, S., Palmas, G., & Beverina, F. (2006) · Clinical Neurophysiology · doi:10.1016/j.clinph.2005.07.024 · Cited by 327 · see citing works
Nijboer (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00055 · Cited by 323 · see citing works
Flashing characters with famous faces improves ERP-based brain–computer interface performance
Kaufmann, T., Schulz, S. M., Grünzinger, C., & Kübler, A. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/5/056016 · Cited by 302 · see citing works
Self-citationAdaptation to changing health: Response shift in quality-of-life research.
(2000) · American Psychological Association eBooks · doi:10.1037/10382-000 · Cited by 301 · see citing works
Bruno, M., Bernheim, J., Ledoux, D., Pellas, F., Athena Demertzi, A., & Laureys, S. (2011) · BMJ Open · doi:10.1136/bmjopen-2010-000039 · Cited by 225 · see citing works
Machine-learning-based coadaptive calibration for brain-computer interfaces
Vidaurre, C., Sannelli, C., Müller, K.-R., & Blankertz, B. (2011) · Neural Computation · doi:10.1162/neco_a_00089 · Cited by 207 · see citing works
Brain–Computer Interfaces: Something New under the Sun
Wolpaw, J. R., & Wolpaw, E. W. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388855.003.0001 · Cited by 198 · see citing works
Mak, J. N., Arbel, Y., Minett, J. W., McCane, L. M., Yuksel, B. F., Ryan, D. B., Thompson, D. E., Bianchi, L., & Deniz Erdogmus, B. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025003 · Cited by 195 · see citing works
Mugler, E. M., Ruf, C. A., Halder, S., Bensch, M., & Kübler, A. (2010) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2010.2068059 · Cited by 181 · see citing works
Self-citationMuenssinger, J., Halder, S., Kleih, S. C., Furdea, A., Raco, V., Hösle, A., & Kübler, A. (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00182 · Cited by 175 · see citing works
Self-citationBrain-Computer Interfacing and Games
Bos, D., Reuderink, B., van de Laar, B. V. D., Gürkök, H., Mühl, C., Poel, M., Nijholt, A., & Heylen, D. (2010) · Brain-Computer Interfaces · doi:10.1007/978-1-84996-272-8_10 · Cited by 175 · see citing works
Towards Practical Brain-Computer Interfaces
Allison, B. Z., Dunne, S., Leeb, R., Millán, J. D. R., Allison, B. Z., Dunne, S., Leeb, R., Millán, J. D. R., & Nijholt, A. (2012) · Biological and medical physics series · doi:10.1007/978-3-642-29746-5 · Cited by 163 · see citing works
A novel 9-class auditory ERP paradigm driving a predictive text entry system
Höhne, J. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00099 · Cited by 158 · see citing works
Self-citationA Brain-Computer Interface as Input Channel for a Standard Assistive Technology Software
Zickler, C., Riccio, A., Leotta, F., Hillian-Tress, S., Halder, S., Holz, E. M., Staiger-Sälzer, P., Hoogerwerf, E.-J., Desideri, L., Donatella Mattia, A., et al. (2011) · Clinical EEG and Neuroscience · doi:10.1177/155005941104200409 · Cited by 157 · see citing works
Self-citationKaufmann, T., Schulz, S. M., Köblitz, A., Renner, G., Wessig, C., & Kübler, A. (2012) · Clinical Neurophysiology · doi:10.1016/j.clinph.2012.11.006 · Cited by 154 · see citing works
Self-citationZickler, C., Halder, S., Kleih, S. C., Herbert, C., & Kübler, A. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.08.003 · Cited by 126 · see citing works
Self-citationPersonal Values and Individual Quality of Life in Palliative Care Patients
Fegg, M. J., Wasner, M., Neudert, C., & Borasio, G. D. (2005) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2005.02.012 · Cited by 106 · see citing works
Barriers to and mediators of brain–computer interface user acceptance: focus group findings
Blain‐Moraes, S., Schaff, R., Gruis, K. L., Huggins, J. E., & Wren, P. A. (2012) · Ergonomics · doi:10.1080/00140139.2012.661082 · Cited by 102 · see citing works
Jin, J., Allison, B. Z., Wang, X., & Neuper, C. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.01.004 · Cited by 94 · see citing works
Riccio, A., Leotta, F., Bianchi, L., Aloise, F., Zickler, C., Hoogerwerf, E.-J., Kübler, A., Donatella Mattia, A., & Febo Cincotti, A. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025028 · Cited by 89 · see citing works
Self-citationComparison of instruments addressing quality of life in patients with ALS and their caregivers
Bromberg, M. B., & Forshew, D. A. (2002) · Neurology · doi:10.1212/wnl.58.2.320 · Cited by 86 · see citing works
Silvoni, S. (2009) · Frontiers in Neuroscience · doi:10.3389/neuro.20.001.2009 · Cited by 83 · see citing works
Training locked-in patients: a challenge for the use of brain-computer interfaces
Neumann, N., & Kübler, A. (2003) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2003.814431 · Cited by 82 · see citing works
Self-citationBernheim, J., & Buyse, M. E. (1983) · Journal of Psychosocial Oncology · doi:10.1300/j077v01n04_03 · Cited by 77 · see citing works
Walking toward a convergence in aging research
Smith, M. A. (2009) · Frontiers in Neuroscience · doi:10.3389/neuro.01.012.2009 · Cited by 67 · see citing works
Natural stimuli improve auditory BCIs with respect to ergonomics and performance
Höhne, J., Krenzlin, K., Dähne, S., & Tangermann, M. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/4/045003 · Cited by 61 · see citing works
Self-citationBCI Applications for People with Disabilities: Defining User Needs and User Requirements
Zickler, C., Donna, V. D., Kaiser, V., Al-Khodairy, A., Kleih, S. C., Andrea, K., Malavasi, M., Donatella Mattia, A., Mongardi, S., Neuper, C., et al. (2009) · IOS Press eBooks · doi:10.3233/978-1-60750-042-1-185 · Cited by 55 · see citing works
Weiss‐Lambrou, R. (2000) · Cited by 43 · see citing works
Optimized stimulation events for a visual ERP BCI
Tangermann, M., Schreuder, M., Dähne, J., Regler, S., Ramsay, A., Quek, M., Williamson, J. H., & Murray‐Smith, R. (2011) · Cited by 34 · see citing works
Self-citationEthical Issues in BCI Research
Schneider, M.-J., Fins, J. J., & Wolpaw, J. R. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388855.003.0024 · Cited by 31 · see citing works
Measuring response shift using the Schedule for Evaluation of Individual Quality of Life.
O’Boyle, C. A., McGee, H. M., & Browne, J. P. (2000) · American Psychological Association eBooks · doi:10.1037/10382-008 · Cited by 24 · see citing works
The SEIQoL and functional status: how do they relate?
Lhussier, M., Watson, B., Reed, J., & Clarke, C. L. (2005) · Scandinavian Journal of Caring Sciences · doi:10.1111/j.1471-6712.2005.00362.x · Cited by 23 · see citing works
Vision-Based Shared Control for a BCI Wheelchair
Carlson, T., Monnard, G., & Millán, J. D. R. (2011) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 20 · see citing works
User Centred Design in BCI Development
Holz, E. M., Kaufmann, T., Desideri, L., Malavasi, M., Hoogerwerf, E.-J., & Kübler, A. (2012) · Biological and medical physics series · doi:10.1007/978-3-642-29746-5_8 · Cited by 19 · see citing works
Self-citationBrain-computer interfacing: science fiction has come true
Kübler, A. (2013) · Brain · doi:10.1093/brain/awt077 · Cited by 15 · see citing works
Self-citation
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Rashid, M., Sulaiman, N., Majeed, A. P. P. A., Musa, R. M., Nasir, A. F. A., Bari, B. S., & Khatun, S. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.00025 · Cited by 513 · see citing works
Simon, N., Käthner, I., Ruf, C. A., Pasqualotto, E., Kübler, A., & Halder, S. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01039 · Cited by 478 · see citing works
Self-citationLazarou, I., Nikolopoulos, S., Petrantonakis, P. C., Kompatsiaris, I. Y., & Tsolaki, M. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00014 · Cited by 340 · see citing works
Käthner, I., Wriessnegger, S. C., Muller-Putz, G. R., Kübler, A., & Halder, S. (2014) · Biological Psychology · doi:10.1016/j.biopsycho.2014.07.014 · Cited by 332 · see citing works
Self-citationNoninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms
He, B., Baxter, B., Edelman, B. J., Cline, C. C., & Ye, W. W. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2407272 · Cited by 233 · see citing works
Kübler, A., Holz, E. M., Riccio, A., Zickler, C., Kaufmann, T., Kleih, S. C., Staiger-Sälzer, P., Desideri, L., Hoogerwerf, E.-J., & Donatella Mattia, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112392 · Cited by 222 · see citing works
Self-citationHolz, E. M., Botrel, L., Kaufmann, T., & Kübler, A. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2014.03.035 · Cited by 171 · see citing works
Self-citationThe Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
Perdikis, S., Tonin, L., Saeedi, S., Schneider, C., & Millán, J. D. R. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2003787 · Cited by 166 · see citing works
Abibullaev, B., Keutayeva, A., & Zollanvari, A. (2023) · IEEE Access · doi:10.1109/access.2023.3329678 · Cited by 147 · see citing works
Kaufmann, T., Holz, E. M., & Kübler, A. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00129 · Cited by 137 · see citing works
Self-citationA systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives
Choi, I., Rhiu, I., Lee, Y., Yun, M. H., & Nam, C. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0176674 · Cited by 133 · see citing works
Review of real brain-controlled wheelchairs
Fernández-Rodríguez, Á., Velasco-Álvarez, F., & Ron-Angevín, R. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/6/061001 · Cited by 102 · see citing works
Huggins, J. E., Moinuddin, A. A., Chiodo, A. E., & Wren, P. A. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2014.05.028 · Cited by 97 · see citing works
Effects of training and motivation on auditory P300 brain-computer interface performance
Baykara, E., Ruf, C. A., Fioravanti, C., Käthner, I., Simon, N., Kleih, S. C., Kübler, A., & Halder, S. (2016) · Clinical Neurophysiology · doi:10.1016/j.clinph.2015.04.054 · Cited by 91 · see citing works
Self-citationBrain-Machine Interfaces: A Tale of Two Learners
Perdikis, S., & Millán, J. D. R. (2020) · IEEE Systems Man and Cybernetics Magazine · doi:10.1109/msmc.2019.2958200 · Cited by 87 · see citing works
Höhne, J., Holz, E., Staiger-Sälzer, P., Müller, K.-R., Kübler, A., & Tangermann, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104854 · Cited by 85 · see citing works
Self-citationTrue Zero-Training Brain-Computer Interfacing – An Online Study
Kindermans, P.-J., Schreuder, M., Schrauwen, B., Müller, K., & Tangermann, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102504 · Cited by 83 · see citing works
Self-citationKoumpouros, Y. (2016) · Journal of Healthcare Engineering · doi:10.1155/2016/1048964 · Cited by 83 · see citing works
Using brain-computer interfaces: a scoping review of studies employing social research methods
Kögel, J., Schmid, J. R., Jox, R. J., & Friedrich, O. (2019) · BMC Medical Ethics · doi:10.1186/s12910-019-0354-1 · Cited by 76 · see citing works
Orlandi, S., House, S. C., Karlsson, P., Saab, R., & Chau, T. T. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.643294 · Cited by 73 · see citing works
An in-depth survey on Deep Learning-based Motor Imagery Electroencephalogram (EEG) classification
Wang, X., Liesaputra, V., Liu, Z., Wáng, Y., & Huang, Z. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2023.102738 · Cited by 74 · see citing works
Facing the challenge: Bringing brain–computer interfaces to end-users
Kübler, A., Donatella Mattia, A., Rupp, R., & Tangermann, M. (2013) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2013.08.002 · Cited by 71 · see citing works
Self-citationElectroencephalogram based brain-computer interface: Applications, challenges, and opportunities
Yadav, H., & Maini, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15653-x · Cited by 71 · see citing works
Nijboer, F., van de Laar, B., Gerritsen, S., Nijholt, A., & Poel, M. (2015) · Interacting with Computers · doi:10.1093/iwc/iwv023 · Cited by 65 · see citing works
Kübler, A., Holz, E. M., Sellers, E. W., & Vaughan, T. M. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2014.03.036 · Cited by 63 · see citing works
Self-citationBrain-controlled applications using dynamic P300 speller matrices
Halder, S., Pinegger, A., Käthner, I., Wriessnegger, S. C., Faller, J., Antunes, J. B. P., Muller-Putz, G. R., & Kübler, A. (2014) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2014.12.001 · Cited by 58 · see citing works
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Self-citationInterfacing to the brain’s motor decisions
Mirabella, G., & Lebedev, M. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00051.2016 · Cited by 55 · see citing works
Al-Taleb, M., Purcell, M. A., Fraser, M., Petric-Gray, N., & Vučković, A. (2019) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-019-0588-7 · Cited by 56 · see citing works
Liberati, G., Pizzimenti, A., Simione, L., Riccio, A., Schettini, F., Inghilleri, M., Donatella Mattia, A., & Febo Cincotti, A. (2015) · Applied Ergonomics · doi:10.1016/j.apergo.2015.03.012 · Cited by 51 · see citing works
Towards a holistic assessment of the user experience with hybrid BCIs
Lorenz, R., Pascual, J., Blankertz, B., & Vidaurre, C. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/3/035007 · Cited by 50 · see citing works
Performance Assessment of a Custom, Portable, and Low-Cost Brain–Computer Interface Platform
McCrimmon, C. M., Fu, J. L., Wang, M., Lopes, L. S., Wang, P. T., Karimi-Bidhendi, A., Liu, C. Y., Heydari, P., Nenadić, Z., & Do, A. H. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2667579 · Cited by 49 · see citing works
Monardo, G., Pavese, C., Giorgi, I., Godi, M., & Colombo, R. (2020) · Games for Health Journal · doi:10.1089/g4h.2020.0024 · Cited by 47 · see citing works
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Cassady, K. E., You, A. K., Doud, A., & He, B. (2014) · TECHNOLOGY · doi:10.1142/s233954781450023x · Cited by 46 · see citing works
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The brain-computer interface researcher’s questionnaire: from research to application
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The Human Factors and Ergonomics of P300-Based Brain-Computer Interfaces
Powers, J. C., Bieliaieva, K., Wu, S., & Nam, C. S. (2015) · Brain Sciences · doi:10.3390/brainsci5030318 · Cited by 40 · see citing works
Pan, H., Ding, P., Wang, F., Li, T., Zhao, L., Nan, W., Fu, Y., & Gong, A. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1429130 · Cited by 37 · see citing works
Weyand, S., Schudlo, L. C., Takehara‐Nishiuchi, K., & Chau, T. T. (2015) · Neurophotonics · doi:10.1117/1.nph.2.2.025001 · Cited by 30 · see citing works
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Kübler, A., & Donatella Mattia, A. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-800948-2.00014-5 · Cited by 25 · see citing works
Self-citationMACRO: Multi-Attention Convolutional Recurrent Model for Subject-Independent ERP Detection
Lan, Z., Yan, C., Li, Z., Tang, D., & Xiang, X. (2021) · IEEE Signal Processing Letters · doi:10.1109/lsp.2021.3095761 · Cited by 26 · see citing works
Hearing the needs of clinical users
Kübler, A., Nijboer, F., & Kleih, S. C. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63934-9.00026-3 · Cited by 25 · see citing works
Self-citationWhat It Takes to Be a Pioneer: Ability Expectations From Brain-Computer Interface Users
Kögel, J., & Wolbring, G. (2020) · NanoEthics · doi:10.1007/s11569-020-00378-0 · Cited by 25 · see citing works
Koumpouros, Y., Karavasili, A., Papageorgiou, E. G., & Siavelis, P. (2016) · Assistive Technology · doi:10.1080/10400435.2015.1131758 · Cited by 24 · see citing works
Miralles, F., Vargiu, E., Rafael-Palou, X., Solà, M., Dauwalder, S., Guger, C., Hintermüller, C., Espinosa, A., Lowish, H., Martin, S., et al. (2015) · Frontiers in ICT · doi:10.3389/fict.2015.00025 · Cited by 23 · see citing works
A neural algorithm for the non-uniform and adaptive sampling of biomedical data
Mesin, L. (2016) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2016.02.004 · Cited by 22 · see citing works
Human factors engineering of BCI: an evaluation for satisfaction of BCI based on motor imagery
Lyu, X., Ding, P., Li, S., Dong, Y., Su, L., Zhao, L., Gong, A., & Fu, Y. (2022) · Cognitive Neurodynamics · doi:10.1007/s11571-022-09808-z · Cited by 22 · see citing works
Combining brain-computer interfaces and multiplayer video games: an application based on c-VEPs
Moreno-Calderón, S., Martínez-Cagigal, V., Santamaría-Vázquez, E., Pérez-Velasco, S., Marcos-Martínez, D., & Hornero, R. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1227727 · Cited by 24 · see citing works
Fatigue in children using motor imagery and P300 brain-computer interfaces
Keough, J. R. G., Irvine, B., Kelly, D., Wrightson, J. G., Márquez, D. C., Kinney‐Lang, E., & Kirton, A. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01349-2 · Cited by 21 · see citing works
Floreani, E. D., Rowley, D., Kelly, D., Kinney‐Lang, E., & Kirton, A. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1007199 · Cited by 21 · see citing works
BNCI Horizon 2020 – Towards a Roadmap for Brain/Neural Computer Interaction
Brunner, C., Blankertz, B., Febo Cincotti, A., Kübler, A., Donatella Mattia, A., Miralles, F., Nijholt, A., Otal, B., Salomon, P. R., & Muller-Putz, G. R. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-07437-5_45 · Cited by 21 · see citing works
Self-citationDohle, E., Swanson, E., Jovanović, L., Yusuf, S., Thompson, L., Horsfall, H. L., Muirhead, W. R., Bashford, L., & Brannigan, J. (2025) · Advanced Science · doi:10.1002/advs.202501912 · Cited by 21 · see citing works
EEG-Induced Autonomous Game-Teaching to a Robot Arm by Human Trainers Using Reinforcement Learning
Kar, R., Ghosh, L., Konar, A., Chakraborty, A., & Nagar, A. K. (2021) · IEEE Transactions on Games · doi:10.1109/tg.2021.3124340 · Cited by 19 · see citing works
Han, Y., Ziebell, P., Riccio, A., & Halder, S. (2022) · Brain-Computer Interfaces · doi:10.1080/2326263x.2022.2041294 · Cited by 19 · see citing works
Bavishi, S., Rosenthal, J., & Bockbrader, M. A. (2018) · Elsevier eBooks · doi:10.1016/b978-0-323-54456-6.00017-7 · Cited by 19 · see citing works
Kleih, S. C., Botrel, L., & Kübler, A. (2021) · Psychophysiology · doi:10.1111/psyp.13832 · Cited by 18 · see citing works
Self-citationPost-Adaptation Effects in a Motor Imagery Brain-Computer Interface Online Coadaptive Paradigm
Cunha, J. D., Perdikis, S., Halder, S., & Scherer, R. (2021) · IEEE Access · doi:10.1109/access.2021.3064226 · Cited by 16 · see citing works
Muscle Artifact Removal Toward Mobile SSVEP-Based BCI: A Comparative Study
Liu, A., Liu, Q., Zhang, X., Chen, X. '., & Chen, X. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3085944 · Cited by 16 · see citing works
Development of Nanotoxicology: Implications for Drug Delivery and Medical Devices
Bhattacharjee, S., & Brayden, D. J. (2015) · Nanomedicine · doi:10.2217/nnm.15.69 · Cited by 16 · see citing works
People with Motor Disabilities Using Gaze to Control Telerobots
Zhang, G., & Hansen, J. P. (2020) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3334480.3382939 · Cited by 16 · see citing works
Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance
Śliwowski, M., Martin, M., Souloumiac, A., Blanchart, P., & Aksenova, T. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1111645 · Cited by 17 · see citing works
GIMIS: Gaze Input with Motor Imagery Selection
Hou, B. J., Bækgaard, P., MacKenzie, I. S., Hansen, J. P., & Puthusserypady, S. K. (2020) · ACM Symposium on Eye Tracking Research and Applications (ETRA) · doi:10.1145/3379157.3388932 · Cited by 15 · see citing works
Yadav, H., & Maini, S. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110937 · Cited by 14 · see citing works
Weyand, S., Takehara‐Nishiuchi, K., & Chau, T. T. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.07.007 · Cited by 14 · see citing works
Botrel, L., Acqualagna, L., Blankertz, B., & Kübler, A. (2017) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2017.08.007 · Cited by 13 · see citing works
Self-citationDillen, A., Omidi, M., Ghaffari, F., Romain, O., Vanderborght, B., Roelands, B., Nowé, A., & Pauw, K. D. (2024) · Sensors · doi:10.3390/s24165253 · Cited by 11 · see citing works
López, S., Cervantes, J.-A., Cervantes, S., Molina, J., & Cervantes, F. (2019) · Cognitive Systems Research · doi:10.1016/j.cogsys.2019.09.013 · Cited by 11 · see citing works
Li, Z., Yan, C., Lan, Z., Tang, D., & Xiang, X. (2022) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2022.3208197 · Cited by 11 · see citing works
Shirzhiyan, Z., Keihani, A., Farahi, M., Shamsi, E., GolMohammadi, M., Mahnam, A., Haidari, M. R., & Jafari, A. H. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.534619 · Cited by 10 · see citing works
User-centred design in brain–computer interface research and development
Kübler, A., Muller-Putz, G. R., & Donatella Mattia, A. (2015) · Annals of Physical and Rehabilitation Medicine · doi:10.1016/j.rehab.2015.06.003 · Cited by 10 · see citing works
Self-citationComputational Intelligence for Pattern Recognition in EEG Signals
Mutasim, A. K., Tipu, R. S., Bashar, M. R., Islam, M. K., & Amin, M. A. (2018) · Studies in computational intelligence · doi:10.1007/978-3-319-89629-8_11 · Cited by 10 · see citing works
Weyand, S., & Chau, T. T. (2015) · Developmental Neurorehabilitation · doi:10.3109/17518423.2015.1087436 · Cited by 9 · see citing works
Gulyás, D., & Jochumsen, M. (2024) · Sensors · doi:10.3390/s24186004 · Cited by 8 · see citing works
Yang, X. (2019) · International Conference on Robots & Intelligent System · doi:10.1109/icris.2019.00100 · Cited by 8 · see citing works
Dwyer, N., Harrison, M., O’Mara, B., & Harley, K. (2024) · Frontiers in Computer Science · doi:10.3389/fcomp.2024.1379559 · Cited by 6 · see citing works
Design and development of contactless interaction with computers based on the Emotiv EPOC+ device
Šumak, B., Špindler, M., & Pušnik, M. (2017) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.23919/mipro.2017.7973491 · Cited by 6 · see citing works
User-Centered BCI Videogame Design
Loup‐Escande, É., Lotte, F., Loup, G., & Lécuyer, A. (2016) · Springer eBooks · doi:10.1007/978-981-4560-50-4_3 · Cited by 6 · see citing works
P300 Brain Computer Interface Control after an Acquired Brain Injury
Daly, J. (2015) · International Journal on Recent and Innovation Trends in Computing and Communication · doi:10.17762/ijritcc2321-8169.150165 · Cited by 6 · see citing works
Farzan, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95730-4.00003-2 · Cited by 5 · see citing works
Daly, J., Armstrong, E., Pinegger, A., Muller-Putz, G. R., & Martin, S. (2015) · International Journal on Recent and Innovation Trends in Computing and Communication · Cited by 5 · see citing works
Closed-loop EEG study on visual recognition during driving
Aydarkhanov, R., Ušćumlić, M., Chavarriaga, R., Gheorghe, L., & Millán, J. D. R. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abdfb2 · Cited by 5 · see citing works
Ethical Considerations of Endovascular Brain–Computer Interfaces
Fry, A., Breyman, E., LaGrassa, E., Oxley, T. J., & Putrino, D. F. (2023) · Advances in neuroethics · doi:10.1007/978-3-031-26801-4_4 · Cited by 5 · see citing works
A Study of Deep Learning Based Classification of Mandarin Vowels Using Spoken Speech EEG Signals
Cui, W., Wang, X., Li, M., Pun, S. H., & Chen, F. (2023) · IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) · doi:10.1109/icspcc59353.2023.10400255 · Cited by 5 · see citing works
de Godoi, T. X., & Valentim, N. (2019) · Brazilian Symposium on Software Quality (SBQS) · doi:10.1145/3364641.3364669 · Cited by 5 · see citing works
User-Centred BCI Videogame Design
Loup‐Escande, É., Lotte, F., Loup, G., & Lécuyer, A. (2015) · Springer eBooks · doi:10.1007/978-981-4560-52-8_3-1 · Cited by 4 · see citing works
Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces
Kozin, A. V., Gerasimov, A., Bakaev, M., Pashkov, A. A., & Разумникова, О. М. (2023) · Algorithms · doi:10.3390/a16110502 · Cited by 3 · see citing works
Making Video Games More Inclusive for People Living With Motor Neuron Disease: Scoping Review
O’Mara, B., Harrison, M., Harley, K., & Dwyer, N. (2024) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/58828 · Cited by 3 · see citing works
Workshops of the Fifth International Brain-Computer
Huggins, J. E., Guger, C., Allison, B. Z., Anderson, C. W., Batista, A. P., Brouwer, A.-M., Brunner, C., Chavarriaga, R., Fried-Oken, M. B., & Gunduz, A. (2014) · Cited by 2 · see citing works
Recent Applications of BCIs in Healthcare
Angulo-Sherman, I. N., & Salazar-Varas, R. (2023) · Intelligent systems reference library · doi:10.1007/978-3-031-37306-0_9 · Cited by 2 · see citing works
Moreno-Calderón, S., Martínez-Cagigal, V., Santamaría-Vázquez, E., Pérez-Velasco, S., Marcos-Martínez, D., & Hornero, R. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340542 · Cited by 2 · see citing works
Kordjazi, N., Koravand, A., & Sveistrup, H. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/166603 · Cited by 2 · see citing works
Acceleration of Therapeutic Use of Brain Computer Interfaces by Development for Gaming
Scott, J. A., & Sims, M. H. (2021) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-76426-5_18 · Cited by 1 · see citing works
Performing a Disembodied Mind: Neurotechnology Between Empowerment and Normalization
Kögel, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78224-5_17 · Cited by 1 · see citing works
A Brain Computer Interface for eInclusion and eHealth
Daly, J., Armstrong, E., Thomson, E., & Martin, S. (2014) · Ulster University Research Portal (Ulster University)
A Neurofeedback-Based Near-Infrared Spectroscopy Brain-Computer Interface
Weyand, S. (2015) · TSpace (University of Toronto)
- Authors
- Holz, E. M., Höhne, J., Staiger-Sälzer, P., Tangermann, M., & Kübler, A.
- Affiliations
- University of Würzburg (DE)
- Technische Universität Berlin (DE)
- University of Freiburg (DE)
- Corresponding author
- Holz, Elisa Mira
- Venue
- Artificial Intelligence in Medicine
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 59
- Issue
- 2
- Pages
- 111-120
- ISSN
- 0933-3657 (ISSN-L)
- OpenAlex
- W2077189121
- Cited by
- 111
- References
- 51
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 9 · 2023: 12 · 2022: 5 · 2021: 10 · 2020: 9 · 2019: 5 · 2018: 5 · 2017: 6 · 2016: 8 · 2015: 23 · 2014: 12 · 2013: 2
- FWCI
- 8.23
- Type
- journal article
- Language
- en
- Open access
- green
- zenodo.org
- Licence
- Locations
- Artificial Intelligence in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Funders
- European ICT Programme (FP7-224631)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- brain-computer interface, sensorimotor rhythm, usability evaluation, locked-in syndrome, information transfer rate, perceived workload, user satisfaction, Connect Four, event-related potentials, assistive technology
- MeSH terms
- Humans, Middle Aged, Paralysis, Severity of Illness Index, Patient Satisfaction, Brain-Computer Interfaces
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