A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives
Tóm tắt
Từ khóa
Tài liệu tham khảo
JR Wolpaw, 2000, Brain-computer interface technology: a review of the first international meeting, IEEE Trans Rehabil Eng, 8, 164, 10.1109/TRE.2000.847807
BZ Allison, 2007, Brain-computer interface systems: progress and prospects, Expert Rev Med Devices, 4, 463, 10.1586/17434440.4.4.463
A Nijholt, 2008, Brain-computer interfacing for intelligent systems, IEEE Intell Syst, 23, 72, 10.1109/MIS.2008.41
BZ Allison, 2012, Toward smarter BCIs: extending BCIs through hybridization and intelligent control, J Neural Eng, 9, 13001, 10.1088/1741-2560/9/1/013001
CS Nam, 2012, Severe motor disability affects functional cortical integration in the context of brain-computer interface (BCI) use, Ergonomics, 55, 581, 10.1080/00140139.2011.647095
Y Li, 2013, Effects of Luminosity Contrast and Stimulus Duration on User Performance and Preference in a P300-Based Brain–Computer Interface, Int J Hum Comput Interact, 30, 151, 10.1080/10447318.2013.839903
D Zhu, 2010, A survey of stimulation methods used in SSVEP-based BCIs, Comput Intell Neurosci, 2010, 1, 10.1155/2010/702357
MM Brouwer A-, 2010, A tactile P300 brain-computer interface, Front Neurosci, 4, 19
F Nijboer, 2008, A P300-based brain-computer interface for people with amyotrophic lateral sclerosis, Clin Neurophysiol, 119, 1909, 10.1016/j.clinph.2008.03.034
JJ Daly, 2008, Brain-computer interfaces in neurological rehabilitation, The Lancet Neurology, 1032, 10.1016/S1474-4422(08)70223-0
JN Mak, 2009, Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects, IEEE Rev Biomed Eng, 2, 187, 10.1109/RBME.2009.2035356
F Babiloni, 2007, The estimation of cortical activity for brain-computer interface: Applications in a domotic context, Comput Intell Neurosci, 2007, 10.1155/2007/91651
O Friman, 2007, Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces, IEEE Trans Biomed Eng, 54, 742, 10.1109/TBME.2006.889160
DJ Krusienski, 2012, Value of amplitude, phase, and coherence features for a sensorimotor rhythm-based brain—computer interface, Brain Res Bull, 87, 130, 10.1016/j.brainresbull.2011.09.019
BZ Allison, 2010, Brain-computer interfaces, 35
C Guger, 2012, How many people could use an SSVEP BCI?, Front Neurosci, 6, 169, 10.3389/fnins.2012.00169
DJ Krusienski, 2011, Critical issues in state-of-the-art brain—computer interface signal processing, J Neural Eng, 8, 25002, 10.1088/1741-2560/8/2/025002
R Scherer, 2012, Brain–computer interfacing: more than the sum of its parts, Soft Comput, 17, 317, 10.1007/s00500-012-0895-4
F Lotte, 2007, A review of classification algorithms for EEG-based brain-computer interfaces, J Neural Eng, 4, R1, 10.1088/1741-2560/4/2/R01
BZ Allison, 2010, Toward a hybrid brain-computer interface based on imagined movement and visual attention, J Neural Eng, 7, 26007, 10.1088/1741-2560/7/2/026007
C Vidaurre, 2010, Towards a cure for BCI illiteracy, Brain Topogr, 23, 194, 10.1007/s10548-009-0121-6
C Sannelli, 2008, Estimating noise and dimensionality in BCI data sets: towards illiteracy comprehension
B Blankertz, 2008, The Berlin Brain—Computer Interface: accurate performance from first-session in BCI-naive subjects, IEEE Trans Biomed Eng, 55, 2452, 10.1109/TBME.2008.923152
C Guger, 2009, How many people are able to control a P300-based brain-computer interface (BCI)?, Neurosci Lett, 462, 94, 10.1016/j.neulet.2009.06.045
T Kaufmann, 2012, Spelling is just a click away—a user-centered brain-computer interface including auto-calibration and predictive text entry, Front Neurosci, 6, 72, 10.3389/fnins.2012.00072
EVC Friedrich, 2009, A scanning protocol for a sensorimotor rhythm-based brain-computer interface, Biol Psychol, 80, 169, 10.1016/j.biopsycho.2008.08.004
DJ McFarland, 2008, Emulation of computer mouse control with a noninvasive brain-computer interface, J Neural Eng, 5, 101, 10.1088/1741-2560/5/2/001
C Neuper, 2005, Imagery of motor actions: Differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG, Cogn Brain Res, 25, 668, 10.1016/j.cogbrainres.2005.08.014
DJ Krusienski, 2008, Toward enhanced P300 speller performance, J Neurosci Methods, 167, 15, 10.1016/j.jneumeth.2007.07.017
M Grosse-Wentrup, 2013, Brain-Computer Interface Research, 39
R Scherer, 2007, Self-initiation of EEG-based brain-computer communication using the heart rate response, J Neural Eng, 4, L23, 10.1088/1741-2560/4/4/L01
R Scherer, 2007, The self-paced graz brain-computer interface: methods and applications, Comput Intell Neurosci, 2007, 79826, 10.1155/2007/79826
S Amiri, 2013, A Review of P300, SSVEP, and Hybrid P300/SSVEP Brain- Computer Interface Systems, Brain-Computer Interface Syst—Recent Prog Futur Prospect, 2013, 1
G Pfurtscheller, 2010, The hybrid BCI, Front Neurosci., 4, 30
J-H Lim, 2015, Development of a hybrid mental spelling system combining SSVEP-based brain–computer interface and webcam-based eye tracking, Biomed Signal Process Control, 21, 99, 10.1016/j.bspc.2015.05.012
Choi I, Bond K, Nam CS. A hybrid BCI-controlled FES system for hand-wrist motor function. Systems, Man, and Cybernetics (SMC), 2016 IEEE International Conference on. 2016. pp. 2324–2328.
C Brunner, 2010, Improved signal processing approaches in an offline simulation of a hybrid brain-computer interface, J Neurosci Methods, 188, 165, 10.1016/j.jneumeth.2010.02.002
A Combaz, 2015, Simultaneous detection of P300 and steady-state visually evoked potentials for hybrid brain-computer interface, PLoS One, 10, e0121481, 10.1371/journal.pone.0121481
T Ma, 2017, The hybrid BCI system for movement control by combining motor imagery and moving onset visual evoked potential, J Neural Eng, 14, 26015, 10.1088/1741-2552/aa5d5f
L Jinyi, 2012, Target selection with hybrid feature for BCI-based 2-D cursor control, IEEE Trans Biomed Eng, 59, 132, 10.1109/TBME.2011.2167718
X Yin, 2015, A hybrid BCI based on EEG and fNIRS signals improves the performance of decoding motor imagery of both force and speed of hand clenching, J Neural Eng, 12, 36004, 10.1088/1741-2560/12/3/036004
M Severens, 2013, A multi-signature brain–computer interface: use of transient and steady-state responses, J Neural Eng, 10, 26005, 10.1088/1741-2560/10/2/026005
S Basaruddin, 2013, Taxonomy Approach for Organizing Knowledge in Academic Institutions, J Organ Knowl Manag, 2013, 13
TT Niranjan, 2007, Process-oriented taxonomy of BPOs: an exploratory study, Bus Process Manag J, 13, 588, 10.1108/14637150710763595
C Qin, 2003, Taxonomy of visualization techniques and systems–Concerns between users and developers are different, Asia GIS Conf, 2003, 1
VL Schwent, 1976, Selective attention and the auditory vertex potential. II. Effects of signal intensity and masking noise, Electroencephalogr Clin Neurophysiol, 40, 615, 10.1016/0013-4694(76)90136-X
Schipani SP. An evaluation of operator workload, during partially-autonomous vehicle operations. 2003.
P Liu, 2012, Task complexity: A review and conceptualization framework, Int J Ind Ergon, 42, 553, 10.1016/j.ergon.2012.09.001
Plass-Oude Bos D, Poel M, Nijholt A. A study in user-centered design and evaluation of mental tasks for BCI. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics). 2011;6524 LNCS: 122–134.
EM Holz, 2013, Brain-computer interface controlled gaming: evaluation of usability by severely motor restricted end-users, Artif Intell Med, 59, 111, 10.1016/j.artmed.2013.08.001
A Kübler, 2014, The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications, PLoS One, 9, e112392, 10.1371/journal.pone.0112392
Mora N, De Munari I, Ciampolini P. Improving BCI usability as HCI in ambient assisted living system control. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015. pp. 293–303.
E Pasqualotto, 2015, Usability and Workload of Access Technology for People With Severe Motor Impairment: A Comparison of Brain-Computer Interfacing and Eye Tracking, Neurorehabil Neural Repair, 29, 950, 10.1177/1545968315575611
L Garcia, 2015, Brain-Computer Interface: Usability Evaluation of Different P300 Speller Configurations: A Preliminary Study, Adv Comput Intell Pt I, 9094, 98, 10.1007/978-3-319-19258-1_9
E Pasqualotto, 2012, Toward functioning and usable brain-computer interfaces (BCIs): A literature review, Disabil Rehabil Assist Technol, 7, 89, 10.3109/17483107.2011.589486
A Riccio, 2011, Workload measurement in a communication application operated through a P300-based brain-computer interface, J Neural Eng, 8, 25028, 10.1088/1741-2560/8/2/025028
TO Zander, 2010, Combining Eye Gaze Input With a Brain–Computer Interface for Touchless Human–Computer Interaction, Int J Hum Comput Interact, 27, 38, 10.1080/10447318.2011.535752
E Pasqualotto, 2011, Toward a Usability Evaluation of BCIs, Int J Bioelectromagn, 13, 121
E Pasqualotto, 2011, Usability of brain computer interfaces, Assistive Technology Research Series, 481
R Joshi, 2012, A Novel Mu Rhythm-based Brain Computer Interface Design that uses a Programmable System on Chip, J Med Signals Sens, 2, 11, 10.4103/2228-7477.103146
F Aloise, 2013, Asynchronous gaze-independent event-related potential-based brain-computer interface, Artif Intell Med, 59, 61, 10.1016/j.artmed.2013.07.006
N Kos’Myna, 2013, Evaluation and comparison of a multimodal combination of BCI paradigms and eye tracking with affordable consumer-grade hardware in a gaming context, IEEE Trans Comput Intell AI Games, 5, 150, 10.1109/TCIAIG.2012.2230003
S Perdikis, 2014, Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller, J Neural Eng, 11, 10.1088/1741-2560/11/3/036003
E Hortal, 2015, Using a brain-machine interface to control a hybrid upper limb exoskeleton during rehabilitation of patients with neurological conditions, J Neuroeng Rehabil, 12, 92, 10.1186/s12984-015-0082-9
SG Charlton, 2002, The role of human factors testing and evaluation in systems development, Handb Hum Factors Test Eval, 21
1998, Ergonomic requirements for office work with visual display terminals (VDTs), Int Organ Stand, 45
A Liberati, 2009, The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions, Ann Intern Med, 151, W65, 10.7326/0003-4819-151-4-200908180-00136
JC Powers, 2015, he Human Factors and Ergonomics of P300-Based Brain-Computer Interfaces, T, 5, 318
K Minho, 2015, Quantitative evaluation of a low-cost noninvasive hybrid interface based on EEG and eye movement, IEEE Trans Neural Syst Rehabil Eng, 23, 159, 10.1109/TNSRE.2014.2365834
H Lee M-, 2015, Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI, . Pattern Recognit, 48, 2725, 10.1016/j.patcog.2015.03.010
B Koo, 2015, A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery, J Neurosci Methods, 244, 26, 10.1016/j.jneumeth.2014.04.016
S Fazli, 2012, Enhanced performance by a hybrid NIRS-EEG brain computer interface, Neuroimage, 59, 519, 10.1016/j.neuroimage.2011.07.084
F Putze, 2014, Hybrid fNIRS-EEG based classification of auditory and visual perception processes, Front Neurosci, 8, 373, 10.3389/fnins.2014.00373
A Riccio, 2015, Hybrid P300-based brain-computer interface to improve usability for people with severe motor disability: electromyographic signals for error correction during a spelling task, Arch Phys Med Rehabil, 96, S54, 10.1016/j.apmr.2014.05.029
J Ma, 2015, A Novel EOG/EEG Hybrid Human-Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control, Ieee Trans Biomed Eng, 62, 876, 10.1109/TBME.2014.2369483
H Wang, 2014, An asynchronous wheelchair control by hybrid EEG-EOG brain-computer interface, Cogn Neurodyn, 8, 399, 10.1007/s11571-014-9296-y
TH Falk, 2011, Taking NIRS-BCIs outside the lab: towards achieving robustness against environment noise, IEEE Trans Neural Syst Rehabil Eng, 19, 136, 10.1109/TNSRE.2010.2078516
S Choi J-, 2013, Enhanced perception of user intention by combining EEG and gaze-tracking for brain-computer interfaces (BCIs), Sensors (Basel), 13, 3454, 10.3390/s130303454
G Li, 2015, A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness, Sensors (Basel), 15, 20873, 10.3390/s150820873
M Rohm, 2013, Hybrid brain-computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury, Artif Intell Med, 59, 133, 10.1016/j.artmed.2013.07.004
R Leeb, 2013, Thinking Penguin: Multimodal Brain–Computer Interface Control of a VR Game, IEEE Trans Comput Intell AI Games, 5, 117, 10.1109/TCIAIG.2013.2242072
A Kreilinger, 2011, Switching between manual control and brain-computer interface using long term and short term quality measures, Front Neurosci, 5, 147
Y Su, 2011, A hybrid brain-computer interface control strategy in a virtual environment, J Zhejiang Univ Sci C, 12, 351, 10.1631/jzus.C1000208
L Bai, 2015, A brain computer interface-based explorer, J Neurosci Methods, 244, 2, 10.1016/j.jneumeth.2014.06.015
M Xu, 2013, A hybrid BCI speller paradigm combining P300 potential and the SSVEP blocking feature, J Neural Eng, 10, 26001, 10.1088/1741-2560/10/2/026001
J Pan, 2014, Detecting awareness in patients with disorders of consciousness using a hybrid brain-computer interface, J Neural Eng, 11, 56007, 10.1088/1741-2560/11/5/056007
S Ahn, 2014, Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery, J Neural Eng, 11, 66004, 10.1088/1741-2560/11/6/066004
T Yu, 2015, Enhanced motor imagery training using a hybrid BCI with feedback, IEEE Trans Biomed Eng, 62, 1706, 10.1109/TBME.2015.2402283
A Frisoli, 2012, A New Gaze-BCI-Driven Control of an Upper Limb Exoskeleton for Rehabilitation in Real-World Tasks, IEEE Trans Syst Man, Cybern Part C (Applications Rev, 42, 1169, 10.1109/TSMCC.2012.2226444
U Park, 2014, Human implicit intent discrimination using EEG and eye movement, Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics), 8834, 11
X Yong, 2011, The Design of a Point-and-Click System by Integrating a Self-Paced Brain–Computer Interface With an Eye-Tracker, IEEE J Emerg Sel Top Circuits Syst, 1, 590, 10.1109/JETCAS.2011.2175589
T Malechka, 2015, sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface, Micromachines, 6, 291, 10.3390/mi6030291
C Postelnicu C-, 2013, P300-based brain-neuronal computer interaction for spelling applications, IEEE Trans Biomed Eng, 60, 534, 10.1109/TBME.2012.2228645
J Jin, 2012, A combined brain—computer interface based on P300 potentials and motion-onset visual evoked potentials, J Neurosci Methods, 205, 265, 10.1016/j.jneumeth.2012.01.004
F Guo, 2008, A brain-computer interface using motion-onset visual evoked potential, J Neural Eng Eng, 5, 477, 10.1088/1741-2560/5/4/011
D Zhang, 2012, An N200 speller integrating the spatial profile for the detection of the non-control state, J Neural Eng, 9, 26016, 10.1088/1741-2560/9/2/026016
PF Diez, 2015, Attention-level transitory response: a novel hybrid BCI approach, J Neural Eng, 12, 56007, 10.1088/1741-2560/12/5/056007
BH Kim, 2014, Quadcopter flight control using a low-cost hybrid interface with EEG-based classification and eye tracking, Comput Biol Med, 51, 82, 10.1016/j.compbiomed.2014.04.020
Carlson T, Tonin L, Perdikis S, Leeb R, del R Millán J. A hybrid BCI for enhanced control of a telepresence robot. Conf Proc. Annu Int Conf IEEE Eng Med Biol Soc IEEE Eng Med Biol Soc Annu Conf. 2013;2013: 3097–100.
R Leeb, 2011, A hybrid brain-computer interface based on the fusion of electroencephalographic and electromyographic activities, J Neural Eng, 8, 25011, 10.1088/1741-2560/8/2/025011
J Llobera, 2013, Virtual reality for assessment of patients suffering chronic pain: a case study, Exp Brain Res, 225, 105, 10.1007/s00221-012-3352-9
L Wang, 2014, Selecting Filter Range of Hybrid Brain-Computer Interfaces by Mutual Information, Adv Mater Res, 981, 171, 10.4028/www.scientific.net/AMR.981.171
MH Chang, 2016, Eliciting dual-frequency SSVEP using a hybrid SSVEP-P300 BCI, J Neurosci Methods, 258, 104, 10.1016/j.jneumeth.2015.11.001
B Graimann, 2009, Brain-Computer Interfaces, 1
D Rozado, 2015, Improving the performance of an EEG-based motor imagery brain computer interface using task evoked changes in pupil diameter, PLoS One, 10, e0121262, 10.1371/journal.pone.0121262
AM Savic, 2014, Feasibility of a hybrid brain-computer interface for advanced functional electrical therapy, ScientificWorldJournal, 2014, 797128, 10.1155/2014/797128
S Amiri, 2013, A review of hybrid brain-computer interface systems, Adv Human-Computer Interact, 2013, 1, 10.1155/2013/187024
BZ Allison, 2012, A hybrid ERD/SSVEP BCI for continuous simultaneous two dimensional cursor control, J Neurosci Methods, 209, 299, 10.1016/j.jneumeth.2012.06.022
M Wang, 2015, A new hybrid BCI paradigm based on P300 and SSVEP, J Neurosci Methods, 244, 16, 10.1016/j.jneumeth.2014.06.003
E Yin, 2015, A Hybrid Brain-Computer Interface Based on the Fusion of P300 and SSVEP Scores, IEEE Trans Neural Syst Rehabil Eng, 23, 693, 10.1109/TNSRE.2015.2403270
E Yin, 2014, A speedy hybrid BCI spelling approach combining P300 and SSVEP, IEEE Trans Biomed Eng, 61, 473, 10.1109/TBME.2013.2281976
Y Li, 2013, A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control, IEEE Trans Biomed Eng, 60, 3156, 10.1109/TBME.2013.2270283
SR Soekadar, 2015, An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand, Biomed Tech (Berl), 60, 199, 10.1515/bmt-2014-0126
J Li, 2014, Evaluation and application of a hybrid brain computer interface for real wheelchair parallel control with multi-degree of freedom, Int J Neural Syst, 24, 1450014, 10.1142/S0129065714500142
S Bhattacharyya, 2014, Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose, Med Biol Eng Comput, 52, 1007, 10.1007/s11517-014-1204-4
L Yao, 2014, Combining motor imagery with selective sensation toward a hybrid-modality BCI, IEEE Trans Biomed Eng, 61, 2304, 10.1109/TBME.2013.2287245
Y Li, 2010, An EEG-based BCI system for 2-D cursor control by combining Mu/Beta rhythm and P300 potential, IEEE Trans Biomed Eng, 57, 2495, 10.1109/TBME.2010.2055564
EC Lee, 2010, A brain-computer interface method combined with eye tracking for 3D interaction, J Neurosci Methods, 190, 289, 10.1016/j.jneumeth.2010.05.008
L Cao, 2014, A hybrid brain computer interface system based on the neurophysiological protocol and brain-actuated switch for wheelchair control, J Neurosci Methods, 229, 33, 10.1016/j.jneumeth.2014.03.011
T Yu, 2013, A hybrid brain-computer interface-based mail client, Comput Math Methods Med, 2013, 750934
B Choi, 2013, A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition, PLoS One, 8, e74583, 10.1371/journal.pone.0074583
A Vučković, 2015, Hybrid Brain-Computer Interface and Functional Electrical Stimulation for Sensorimotor Training in Participants With Tetraplegia, J Neurol Phys Ther, 39, 3, 10.1097/NPT.0000000000000063
G Pfurtscheller, 2010, Self-paced operation of an SSVEP-Based orthosis with and without an imagery-based “brain switch:” a feasibility study towards a hybrid BCI, IEEE Trans Neural Syst Rehabil Eng, 18, 409, 10.1109/TNSRE.2010.2040837
T Zeyl, 2016, Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label, J Neural Eng, 13, 26008, 10.1088/1741-2560/13/2/026008
T Zeyl, 2016, Adding Real-Time Bayesian Ranks to Error-Related Potential Scores Improves Error Detection and Auto-Correction in a P300 Speller, Ieee Trans Neural Syst Rehabil Eng, 24, 46, 10.1109/TNSRE.2015.2461495
E Yin, 2013, A novel hybrid BCI speller based on the incorporation of SSVEP into the P300 paradigm, J Neural Eng, 10, 26012, 10.1088/1741-2560/10/2/026012
DC Jangraw, 2014, Neurally and ocularly informed graph-based models for searching 3D environments, J Neural Eng, 11, 46003, 10.1088/1741-2560/11/4/046003
J Jiang, 2014, Hybrid Brain-Computer Interface (BCI) based on the EEG and EOG signals, Biomed Mater Eng., 24, 2919
C Brunner, 2011, A comparison of three brain-computer interfaces based on event-related desynchronization, steady state visual evoked potentials, or a hybrid approach using both signals, J Neural Eng, 8, 25010, 10.1088/1741-2560/8/2/025010
J Long, 2012, A hybrid brain computer interface to control the direction and speed of a simulated or real wheelchair, IEEE Trans Neural Syst Rehabil Eng, 20, 720, 10.1109/TNSRE.2012.2197221
M Rohm, 2010, A hybrid-Brain Computer Interface for control of a reaching and grasping neuroprosthesis, Biomedizinische Technik
H-Y Wu, 2011, Accounting for phase drifts in SSVEP-based BCIs by means of biphasic stimulation, IEEE Trans Biomed Eng, 58, 1394, 10.1109/TBME.2010.2102757
R Lorenz, 2014, Towards a holistic assessment of the user experience with hybrid BCIs, J Neural Eng, 11, 35007, 10.1088/1741-2560/11/3/035007
E Yin, 2016, An auditory-tactile visual saccade-independent P300 brain—computer interface, Int J Neural Syst, 26, 1650001, 10.1142/S0129065716500015
T Zeyl, 2016, Improving bit rate in an auditory BCI: Exploiting error-related potentials, Brain-Computer Interfaces, 3, 75, 10.1080/2326263X.2016.1169723
C Breitwieser, 2016, A hybrid three-class brain–computer interface system utilizing SSSEPs and transient ERPs, J Neural Eng, 13, 66015, 10.1088/1741-2560/13/6/066015
K Lin, 2016, An online hybrid BCI system based on SSVEP and EMG, J Neural Eng, 13, 26020, 10.1088/1741-2560/13/2/026020
AP Buccino, 2016, Hybrid EEG-fNIRS asynchronous brain-computer interface for multiple motor tasks, PLoS One, 11, 1, 10.1371/journal.pone.0146610
W Yi, 2016, Enhancing performance of a motor imagery based brain-computer interface by incorporating electrical stimulation-induced SSSEP, J Neural Eng
EM Holz, 2015, Long-term independent brain-computer interface home use improves quality of life of a patient in the locked-in state: A case study, Arch Phys Med Rehabil, 96, S16, 10.1016/j.apmr.2014.03.035
C Zickler, 2013, Brain painting: Usability testing according to the user-centered design in end users with severe motor paralysis, Artif Intell Med, 59, 99, 10.1016/j.artmed.2013.08.003
C Zickler, 2011, A brain-computer interface as input channel for a standard assistive technology software, Clin EEG Neurosci, 42, 236, 10.1177/155005941104200409
J H??hne, 2014, Towards user-friendly spelling with an auditory brain-computer interface: The CharStreamer paradigm, PLoS One, 9, e98322, 10.1371/journal.pone.0098322
S Weyand, 2015, Usability and performance-informed selection of personalized mental tasks for an online near-infrared spectroscopy brain-computer interface, Neurophotonics, 2, 25001, 10.1117/1.NPh.2.2.025001
J Daly, 2014, Moving brain computer interfaces towards home based systems for people with acquired brain injury, Ambient Assist Living Dly Act, 8868, 115
F Deravi, 2015, Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients, Int J Eng Technol Innov, 5, 165
SC Kleih, 2015, The WIN-speller: A new intuitive auditory brain-computer interface spelling application, Front Neurosci, 9, 346, 10.3389/fnins.2015.00346
R Carabalona, 2012, Light on! Real world evaluation of a P300-based brain-computer interface (BCI) for environment control in a smart home, Ergonomics, 55, 552, 10.1080/00140139.2012.661083
A Combaz, 2013, A Comparison of Two Spelling Brain-Computer Interfaces Based on Visual P3 and SSVEP in Locked-In Syndrome, PLoS One, 8, 10.1371/journal.pone.0073691
G Morone, 2015, Proof of principle of a brain-computer interface approach to support poststroke arm rehabilitation in hospitalized patients: design, acceptability, and usability, Arch Phys Med Rehabil, 96, S71, 10.1016/j.apmr.2014.05.026
F Schettini, 2015, Assistive device with conventional, alternative, and brain-computer interface inputs to enhance interaction with the environment for people with amyotrophic lateral sclerosis: a feasibility and usability study, Arch Phys Med Rehabil, 96, S46, 10.1016/j.apmr.2014.05.027
H-J Hwang, 2017, Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: Case studies, Psychophysiology, 54, 444, 10.1111/psyp.12793
N Kosmyna, 2016, Feasibility of BCI Control in a Realistic Smart Home Environment, Front Hum Neurosci, 10, 10.3389/fnhum.2016.00416
E Baykara, 2016, Effects of training and motivation on auditory P300 brain-computer interface performance, Clin Neurophysiol, 127, 379, 10.1016/j.clinph.2015.04.054
T-S Lee, 2013, A brain-computer interface based cognitive training system for healthy elderly: A randomized control pilot study for usability and preliminary efficacy, PLoS One, 8, e79419, 10.1371/journal.pone.0079419
T-S Lee, 2015, A pilot randomized controlled trial using EEG-based brain–computer interface training for a Chinese-speaking group of healthy elderly, Clin Interv Aging, 10, 217
J Legény, 2011, Navigating in virtual worlds using a self-paced ssvep-based brain-computer interface with integrated stimulation and real-time feedback, Presence Teleoperators Virtual Environ, 20, 529, 10.1162/PRES_a_00075
CS Nam, 2010, Evaluation of P300-based brain-computer interface in real-world contexts, Int J Hum Comput Interact, 26, 621, 10.1080/10447311003781326
F Nijboer, 2015, Usability of three electroencephalogram headsets for brain-computer interfaces: A within subject comparison, Interact Comput, 27, 500, 10.1093/iwc/iwv023
N Simon, 2015, An auditory multiclass brain-computer interface with natural stimuli: Usability evaluation with healthy participants and a motor impaired end user, Front Hum Neurosci, 8, 1, 10.3389/fnhum.2014.01039
D-O Won, 2015, Effect of higher frequency on the classification of steady-state visual evoked potentials, J Neural Eng, 13, 16014, 10.1088/1741-2560/13/1/016014
CK Coursaris, 2011, A meta-analytical review of empirical mobile usability studies, J usability Stud, 6, 117
A Cao, 2009, NASA TLX: software for assessing subjective mental workload, Behav Res Methods, 41, 113, 10.3758/BRM.41.1.113
EE Ohnhaus, 1975, Methodological problems in the measurement of pain: A comparison between the verbal rating scale and the visual analogue scale, Pain, 1, 379, 10.1016/0304-3959(75)90075-5
MJ Scherer, 2002, Matching person & technology (MPT) assessment process, Technol Disabil, 14, 125, 10.3233/TAD-2002-14308
L Demers, 2002, The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2. 0): An overview and recent progress, Technol Disabil, 14, 101, 10.3233/TAD-2002-14304
A Bangor, 2009, Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale, J Usability Stud, 4, 114
AM Lund, 2001, Measuring usability with the USE questionnaire, Usability interface, 8, 3
JR Lewis, 1995, IBM Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use, Int J Hum Comput Interact, 7, 57, 10.1080/10447319509526110
F Rheinberg, 2001, QCM: A questionnaire to assess current motivation in learning situations, Diagnostica, 47, 57
SH Han, 2001, Usability of consumer electronic products, International Journal of Industrial Ergonomics, 143, 10.1016/S0169-8141(01)00025-7
Nielsen J. Usability Engineering. 1995; 362.
S Blain-Moraes, 2012, Barriers to and mediators of brain–computer interface user acceptance: focus group findings, Ergonomics, 55, 516, 10.1080/00140139.2012.661082
A Kübler, 2013, A User Centred Approach for Bringing BCI Controlled Applications to End-Users, Brain-Computer Interface Syst—Recent Prog Futur Prospect, 1
Botte-lecocq C, Vannobel J, Botte-lecocq C. Considering human factors in BCI experiments: a global approach St ´ To cite this version: HAL Id: hal-01114440. 2015;
Barros R, Santos G, Ribeiro C, Torres R. A Usability Study of a Brain-Computer Interface Apparatus: An Ergonomic Approach. Conf Des …. 2015;
JI Ekandem, 2012, Evaluating the ergonomics of BCI devices for research and experimentation, Ergonomics, 55, 592, 10.1080/00140139.2012.662527
D Lacko, 2017, Ergonomic design of an EEG headset using 3D anthropometry, Appl Ergon, 58, 128, 10.1016/j.apergo.2016.06.002
R Merletti, 2010, The electrode—skin interface and optimal detection of bioelectric signals, Physiol Meas, 31, 10.1088/0967-3334/31/10/E01
L-D Liao, 2012, Biosensor technologies for augmented brain—computer interfaces in the next decades, Proc IEEE, 100, 1553, 10.1109/JPROC.2012.2184829
DPO Bos, 2011, ser Experience Evaluation in BCI: Mind the Gap!, U, 13, 48
A Kübler, 2013, Applying the user-centred design to evaluation of Brain-Computer Interface controlled applications, Biomedical