20.9.8.1 Brain-Computer Interface, Brain-Machine Interface

Chapter Contents (Back)
HCI. BCI.

Brunner, C.[Clemens], Naeem, M.[Muhammad], Leeb, R.[Robert], Graimann, B.[Bernhard], Pfurtscheller, G.[Gert],
Spatial filtering and selection of optimized components in four class motor imagery EEG data using independent components analysis,
PRL(28), No. 8, 1 June 2007, pp. 957-964.
WWW Link. 0704
Spatial filtering; Independent components analysis (ICA); Common spatial patterns (CSP); Principal components analysis (PCA); Electroencephalogram (EEG); Brain-computer interface (BCI); Motor imagery BibRef

Sun, S.L.[Shi-Liang], Zhang, C.S.[Chang-Shui], Zhang, D.[Dan],
An experimental evaluation of ensemble methods for EEG signal classification,
PRL(28), No. 15, 1 November 2007, pp. 2157-2163.
WWW Link. 0711
Brain-computer interface (BCI); EEG signal classification; Bagging; Boosting; Random subspace BibRef

Zhong, M.J.[Ming-Jun], Lotte, F.[Fabien], Girolami, M.[Mark], Lecuyer, A.[Anatole],
Classifying EEG for brain computer interfaces using Gaussian processes,
PRL(29), No. 3, 1 February 2008, pp. 354-359.
WWW Link. 0801
Gaussian process; Brain computer interfaces; Support vector machine; EEG BibRef

Li, Y.Q.[Yuan-Qing], Guan, C.T.[Cun-Tai], Li, H.Q.[Hui-Qi], Chin, Z.Y.[Zheng-Yang],
A self-training semi-supervised SVM algorithm and its application in an EEG-based brain computer interface speller system,
PRL(29), No. 9, 1 July 2008, pp. 1285-1294.
WWW Link. 0711
Semi-supervised support vector machine (SVM); Model selection; Convergence; Brain computer interface (BCI); Electroencephalogram (EEG) BibRef

Li, J.[Jie], Zhang, L.Q.[Li-Qing],
Regularized tensor discriminant analysis for single trial EEG classification in BCI,
PRL(31), No. 7, 1 May 2010, pp. 619-628.
Elsevier DOI 1004
Brain computer interfacing (BCI); Channel selection; Electroencephalogram (EEG); Regularized tensor discriminant analysis (RTDA); Single trial classification; Tensor factorization BibRef

Kayikcioglu, T.[Temel], Aydemir, O.[Onder],
A polynomial fitting and k-NN based approach for improving classification of motor imagery BCI data,
PRL(31), No. 11, 1 August 2010, pp. 1207-1215.
Elsevier DOI 1008
Brain computer interface (BCI); Polynomial fitting; k-Nearest neighbor; Electroencephalogram (EEG); Feature extraction; Classification BibRef

Cecotti, H.[Hubert], Graeser, A.[Axel],
Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces,
PAMI(33), No. 3, March 2011, pp. 433-445.
IEEE DOI 1102
BibRef
Earlier:
Convolutional Neural Network with embedded Fourier Transform for EEG classification,
ICPR08(1-4).
IEEE DOI 0812
To enable spelling out words. BibRef

Cecotti, H.[Hubert],
A time-frequency convolutional neural network for the offline classification of steady-state visual evoked potential responses,
PRL(32), No. 8, 1 June 2011, pp. 1145-1153.
Elsevier DOI 1101
Neural network; Convolution; Fourier transform; Spatial filters; Steady-state visual evoked potential (SSVEP); Electroencephalogram (EEG) BibRef

Zhang, S.M.[Shao-Min], Jiang, B.[Bo], Zhu, J.M.[Jun-Ming], Zhang, Q.S.[Qiao-Sheng], Chen, W.D.[Wei-Dong], Zheng, X.X.[Xiao-Xiang], Zhao, T.[Ting],
A study on combining local field potential and single unit activity for better neural decoding,
IJIST(21), No. 2, June 2011, pp. 165-172.
DOI Link 1101
brain-machine interface; local field potential; single-unit activity; neural decoding; time-frequency domain BibRef

Gouy-Pailler, C.[Cédric], Sebag, M.[Michčle], Larue, A.[Anthony], Souloumiac, A.[Antoine],
Single trial variability in brain-computer interfaces based on motor imagery: Learning in the presence of labeling noise,
IJIST(21), No. 2, June 2011, pp. 148-157.
DOI Link 1101
BibRef

Zhang, S.M.[Shao-Min], Liao, Y.[Yuxi], Zheng, X.X.[Xiao-Xiang], Chen, W.D.[Wei-Dong], Wang, Y.[Yiwen],
Decoding the nonstationary neural activity in motor cortex for brain machine interfaces,
IJIST(21), No. 2, June 2011, pp. 158-164.
DOI Link 1101
BibRef

Suk, H.I.[Heung-Il], Lee, S.W.[Seong-Whan],
Subject and class specific frequency bands selection for multiclass motor imagery classification,
IJIST(21), No. 2, June 2011, pp. 123-130.
DOI Link 1101
brain-computer interface; frequency bands selection; motor imagery classification; ERD/ERS; electroencephalography BibRef

Kroeker, K.L.[Kirk L.],
Improving Brain-Computer Interfaces,
CACM(54), No. 10, October 2011, pp. 11-14.
DOI Link 1110
Researchers are demonstrating advances in restorative BCI systems that are giving paralyzed individuals more effective ways to communicate, move, and interact with their environment. BibRef

Sasayama, T.[Teruyoshi], Kobayashi, T.[Tetsuo],
Movement-Imagery Brain-Computer Interface: EEG Classification of Beta Rhythm Synchronization Based on Cumulative Distribution Function,
IEICE(E94-D), No. 12, December 2011, pp. 2479-2486.
WWW Link. 1112
BibRef

Daly, I.[Ian], Nasuto, S.J.[Slawomir J.], Warwick, K.[Kevin],
Brain computer interface control via functional connectivity dynamics,
PR(45), No. 6, June 2012, pp. 2123-2136.
Elsevier DOI 1202
BCI; Phase synchronization; Functional connectivity; Complex networks; Finger tapping; HMM BibRef

Becedas, J.,
Brain-Machine Interfaces: Basis and Advances,
SMC-C(42), No. 6, November 2012, pp. 825-836.
IEEE DOI 1210
BibRef

Ang, K.K.[Kai Keng], Chin, Z.Y.[Zheng Yang], Zhang, H.H.[Hai-Hong], Guan, C.T.[Cun-Tai],
Mutual information-based selection of optimal spatial-temporal patterns for single-trial EEG-based BCIs,
PR(45), No. 6, June 2012, pp. 2137-2144.
Elsevier DOI 1202
Brain-computer interface (BCI); Electroencephalogram (EEG); Mutual information; Feature selection; Bayesian classification BibRef

van Erp, J.[Jan], Lotte, F.[Fabien], Tangermann, M.[Michael],
Brain-Computer Interfaces: Beyond Medical Applications,
Computer(45), No. 4, April 2012, pp. 26-34.
IEEE DOI 1204
BibRef

Escolano, C., Antelis, J.M., Minguez, J.,
A Telepresence Mobile Robot Controlled With a Noninvasive Brain-Computer Interface,
SMC-B(42), No. 3, June 2012, pp. 793-804.
IEEE DOI 1202
BibRef

Suk, H.I.[Heung-Il], Lee, S.W.[Seong-Whan],
A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces,
PAMI(35), No. 2, February 2013, pp. 286-299.
IEEE DOI 1301
EEG based interface. Learning. BibRef

Bi, L.Z.[Lu-Zheng], Fan, X.A.[Xin-An], Liu, Y.[Yili],
EEG-Based Brain-Controlled Mobile Robots: A Survey,
HMS(43), No. 2, March 2013, pp. 161-176.
IEEE DOI 1303
Survey, BCI. BibRef

Lee, K.Y.[Kyeong-Yeon], Kim, S.[Sun],
Designing discriminative spatial filter vectors in motor imagery brain-computer interface,
IJIST(23), No. 2, 2013, pp. 147-151.
DOI Link 1307
brain-computer interface, common spatial pattern, feature selection, motor imagery classification, electroencephalography BibRef

Wang, H.X.[Hai-Xian],
Discriminant and adaptive extensions to local temporal common spatial patterns,
PRL(34), No. 10, 15 July 2013, pp. 1125-1129.
Elsevier DOI 1306
Common spatial patterns; Brain-computer interfaces (BCI); Fisher criterion; Sparse representation BibRef

Bi, L., Fan, X.A., Luo, N., Jie, K., Li, Y., Liu, Y.,
A Head-Up Display-Based P300 Brain-Computer Interface for Destination Selection,
ITS(14), No. 4, 2013, pp. 1996-2001.
IEEE DOI 1312
Brain-computer interfaces BibRef

Fan, X., Bi, L., Teng, T., Ding, H., Liu, Y.,
A Brain-Computer Interface-Based Vehicle Destination Selection System Using P300 and SSVEP Signals,
ITS(16), No. 1, February 2015, pp. 274-283.
IEEE DOI 1502
Accuracy BibRef

Kao, J.C., Stavisky, S.D., Sussillo, D., Nuyujukian, P., Shenoy, K.V.,
Information Systems Opportunities in Brain-Machine Interface Decoders,
PIEEE(102), No. 5, May 2014, pp. 666-682.
IEEE DOI 1405
Algorithm design and analysis BibRef

Shi, Z.Z.[Zhong-Zhi], Zhang, J.H.[Jian-Hua], Yang, X.[Xi], Ma, G.[Gang], Qi, B.Y.[Bao-Yuan], Yue, J.P.[Jin-Peng],
Computational Cognitive Models for Brain-Machine Collaborations,
IEEE_Int_Sys(29), No. 6, November 2014, pp. 24-31.
IEEE DOI 1502
brain-computer interfaces BibRef

Lee, M.H.[Min-Ho], Fazli, S.[Siamac], Mehnert, J.[Jan], Lee, S.W.[Seong-Whan],
Subject-dependent classification for robust idle state detection using multi-modal neuroimaging and data-fusion techniques in BCI,
PR(48), No. 8, 2015, pp. 2725-2737.
Elsevier DOI 1505
Hybrid brain-computer interfacing BibRef

Muller-Putz, G., del R Millan, J., Schalk, G., Muller, K.,
The Plurality of Human Brain-Computer Interfacing,
PIEEE(103), No. 6, June 2015, pp. 868-870.
IEEE DOI 1506
[Scanning the Issue]. Biomedical monitoring BibRef

Lotte, F.,
Signal Processing Approaches to Minimize or Suppress Calibration Time in Oscillatory Activity-Based Brain-Computer Interfaces,
PIEEE(103), No. 6, June 2015, pp. 871-890.
IEEE DOI 1506
brain-computer interfaces BibRef

Fazli, S., Dahne, S., Samek, W., Bieszmann, F., Muller, K.R.,
Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain-Computer Interfaces,
PIEEE(103), No. 6, June 2015, pp. 891-906.
IEEE DOI 1506
brain-computer interfaces BibRef

He, B.[Bin], Baxter, B., Edelman, B.J., Cline, C.C., Ye, W.W.,
Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms,
PIEEE(103), No. 6, June 2015, pp. 907-925.
IEEE DOI 1506
brain-computer interfaces BibRef

Muller-Putz, G., Leeb, R., Tangermann, M., Hohne, J., Kubler, A., Cincotti, F., Mattia, D., Rupp, R., Muller, K.R., Millan, J.D.[J. Del_R],
Towards Noninvasive Hybrid Brain-Computer Interfaces: Framework, Practice, Clinical Application, and Beyond,
PIEEE(103), No. 6, June 2015, pp. 926-943.
IEEE DOI 1506
assisted living BibRef

Rupp, R., Rohm, M., Schneiders, M., Kreilinger, A., Muller-Putz, G.R.,
Functional Rehabilitation of the Paralyzed Upper Extremity After Spinal Cord Injury by Noninvasive Hybrid Neuroprostheses,
PIEEE(103), No. 6, June 2015, pp. 954-968.
IEEE DOI 1506
brain-computer interfaces BibRef

Leeb, R., Tonin, L., Rohm, M., Desideri, L., Carlson, T., del R Millan, J.,
Towards Independence: A BCI Telepresence Robot for People With Severe Motor Disabilities,
PIEEE(103), No. 6, June 2015, pp. 969-982.
IEEE DOI 1506
brain-computer interfaces BibRef

Peck, E.M.[Evan M.], Carlin, E.[Emily], Jacob, R.[Robert],
Designing Brain-Computer Interfaces for Attention-Aware Systems,
Computer(48), No. 10, October 2015, pp. 34-42.
IEEE DOI 1511
BCIs BibRef

Cecotti, H.[Hubert],
Toward shift invariant detection of event-related potentials in non-invasive brain-computer interface,
PRL(66), No. 1, 2015, pp. 127-134.
Elsevier DOI 1511
Event-related potentials (ERP) BibRef

Lu, J.[Jie], Mamun, K.A.[Khondaker A.], Chau, T.[Tom],
Pattern classification to optimize the performance of Transcranial Doppler Ultrasonography-based brain machine interface,
PRL(66), No. 1, 2015, pp. 135-143.
Elsevier DOI 1511
Transcranial Doppler (TCD) Ultrasonography BibRef

Obeidat, Q.T., Campbell, T.A., Kong, J.,
Introducing the Edges Paradigm: A P300 Brain-Computer Interface for Spelling Written Words,
HMS(45), No. 6, December 2015, pp. 727-738.
IEEE DOI 1512
Accuracy. BibRef

Higger, M., Akcakaya, M., Nezamfar, H., La Mountain, G., Orhan, U., Erdogmus, D.,
A Bayesian Framework for Intent Detection and Stimulation Selection in SSVEP BCIs,
SPLetters(22), No. 6, June 2015, pp. 743-747.
IEEE DOI 1411
Brain Computer Interfaces (BCI). BibRef

Zhao, X., Chu, Y., Han, J., Zhang, Z.,
SSVEP-Based Brain-Computer Interface Controlled Functional Electrical Stimulation System for Upper Extremity Rehabilitation,
SMCS(46), No. 7, July 2016, pp. 947-956.
IEEE DOI 1606
Electroencephalography BibRef

Bhattacharyya, S., Shimoda, S., Hayashibe, M.,
A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control,
SMCS(46), No. 7, July 2016, pp. 957-968.
IEEE DOI 1606
Decoding BibRef

Waytowich, N.R., Krusienski, D.J.,
Multiclass Steady-State Visual Evoked Potential Frequency Evaluation Using Chirp-Modulated Stimuli,
HMS(46), No. 4, August 2016, pp. 593-600.
IEEE DOI 1608
brain-computer interfaces BibRef

Alt, M.T., Fiedler, E., Rudmann, L., Ordonez, J.S., Ruther, P., Stieglitz, T.,
Let There Be Light: Optoprobes for Neural Implants,
PIEEE(105), No. 1, January 2017, pp. 101-138.
IEEE DOI 1612
Biological tissues BibRef

Maharbiz, M.M., Muller, R., Alon, E., Rabaey, J.M., Carmena, J.M.,
Reliable Next-Generation Cortical Interfaces for Chronic Brain-Machine Interfaces and Neuroscience,
PIEEE(105), No. 1, January 2017, pp. 73-82.
IEEE DOI 1612
Electrodes BibRef

Muraskin, J., Sherwin, J., Lieberman, G., Garcia, J.O., Verstynen, T., Vettel, J.M., Sajda, P.,
Fusing Multiple Neuroimaging Modalities to Assess Group Differences in Perception-Action Coupling,
PIEEE(105), No. 1, January 2017, pp. 83-100.
IEEE DOI 1612
Couplings BibRef

Raspopovic, S., Petrini, F.M., Zelechowski, M., Valle, G.,
Framework for the Development of Neuroprostheses: From Basic Understanding by Sciatic and Median Nerves Models to Bionic Legs and Hands,
PIEEE(105), No. 1, January 2017, pp. 34-49.
IEEE DOI 1612
Biological system modeling BibRef

Ha, S., Akinin, A., Park, J., Kim, C., Wang, H., Maier, C., Mercier, P.P., Cauwenberghs, G.,
Silicon-Integrated High-Density Electrocortical Interfaces,
PIEEE(105), No. 1, January 2017, pp. 11-33.
IEEE DOI 1612
Biomedical monitoring BibRef

Akay, M., Sajda, P., Micera, S., Carmena, J.M.,
Advanced Technologies for Brain Research,
PIEEE(105), No. 1, January 2017, pp. 8-10.
IEEE DOI 1612
BibRef

Dweiri, Y.M., Eggers, T.E., Gonzalez-Reyes, L.E., Drain, J., McCallum, G.A., Durand, D.M.,
Stable Detection of Movement Intent From Peripheral Nerves: Chronic Study in Dogs,
PIEEE(105), No. 1, January 2017, pp. 50-65.
IEEE DOI 1612
Dogs BibRef

Ohta, J., Ohta, Y., Takehara, H., Noda, T., Sasagawa, K., Tokuda, T., Haruta, M., Kobayashi, T., Akay, Y.M., Akay, M.,
Implantable Microimaging Device for Observing Brain Activities of Rodents,
PIEEE(105), No. 1, January 2017, pp. 158-166.
IEEE DOI 1612
Brain BibRef


Camilleri, T.A.[Tracey A.], Camilleri, K.P.[Kenneth P.], Fabri, S.G.[Simon G.],
Segmentation and Labelling of EEG for Brain Computer Interfaces,
CAIP15(I:288-299).
Springer DOI 1511
BibRef

Lee, M.H.[Min-Ho], Fazli, S., Mehnert, J., Lee, S.W.[Seong-Whan],
Improving the Performance of Brain-Computer Interface Using Multi-modal Neuroimaging,
ACPR13(511-515)
IEEE DOI 1408
brain-computer interfaces BibRef

Christopher, K.R., Kapur, A., Carnegie, D.A., Grimshaw, G.M.,
Implementing 3D visualizations of EEG signals in artistic applications,
IVCNZ13(364-369)
IEEE DOI 1402
brain-computer interfaces BibRef

Zhou, W.[Wei], Yang, Y.[Ya], Yu, Z.L.[Zhu-Liang],
Discriminative dictionary learning for EEG signal classification in Brain-computer interface,
ICARCV12(1582-1585).
IEEE DOI 1304
BibRef

Satti, A.[Abdul], Guan, C.T.[Cun-Tai], Coyle, D.[Damien], Prasad, G.[Girijesh],
A Covariate Shift Minimisation Method to Alleviate Non-stationarity Effects for an Adaptive Brain-Computer Interface,
ICPR10(105-108).
IEEE DOI 1008
BibRef

Amcalar, A.[Armagan], Cetin, M.[Mujdat],
Design, Implementation and Evaluation of a Real-Time P300-based Brain-Computer Interface System,
ICPR10(117-120).
IEEE DOI 1008
BibRef

Ang, K.K.[Kai Keng], Guan, C.T.[Cun-Tai], Lee, K.[Kerry], Lee, J.Q.[Jie Qi], Nioka, S.[Shoko], Chance, B.[Britton],
A Brain-Computer Interface for Mental Arithmetic Task from Single-Trial Near-Infrared Spectroscopy Brain Signals,
ICPR10(3764-3767).
IEEE DOI 1008
BibRef

Argunsah, A.O.[Ali Ozgur], Cetin, M.[Mujdat],
AR-PCA-HMM Approach for Sensorimotor Task Classification in EEG-based Brain-Computer Interfaces,
ICPR10(113-116).
IEEE DOI 1008
BibRef

Lu, S.J.[Shi-Jian], Guan, C.T.[Cun-Tai], Zhang, H.H.[Hai-Hong],
Subject-independent brain computer interface through boosting,
ICPR08(1-4).
IEEE DOI 0812
EEG classification BibRef

Lotte, F.[Fabien], Mouchere, H.[Harold], Lecuyer, A.[Anatole],
Pattern rejection strategies for the design of self-paced EEG-based Brain-Computer Interfaces,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Poli, R.[Riccardo], Salvaris, M.[Mathew], Cinel, C.[Caterina],
Evolutionary Synthesis of a Trajectory Integrator for an Analogue Brain-Computer Interface Mouse,
EvoIASP11(214-223).
Springer DOI 1104
BibRef

Poli, R.[Riccardo], Cinel, C.[Caterina], Citi, L.[Luca], Sepulveda, F.[Francisco],
Evolutionary Brain Computer Interfaces,
EvoIASP07(301-310).
Springer DOI 0704
BibRef

Millán, J.D.[José Del_R.], Ferrez, P.W.[Pierre W.], Galán, F.[Ferran], Lew, E.[Eileen], Chavarriaga, R.[Ricardo],
Non-invasive Brain-Actuated Interaction,
BVAI07(438-447).
Springer DOI 0710
BibRef

Liefhold, C.[Christian], Grosse-Wentrup, M.[Moritz], Gramann, K.[Klaus], Buss, M.[Martin],
Comparison of Adaptive Spatial Filters with Heuristic and Optimized Region of Interest for EEG Based Brain-Computer-Interfaces,
DAGM07(274-283).
Springer DOI 0709
BibRef

Song, X.M.[Xiao-Mu], Iordanescu, G.[George], Wyrwicz, A.M.[Alice M.],
One-class Machine Learning for Brain Activation Detection,
CVPR07(1-6).
IEEE DOI 0706
BibRef

Zhu, X.Y.[Xiao-Yuan], Wu, J.K.[Jian-Kang], Cheng, Y.M.[Yi-Min], Wang, Y.X.[Yi-Xiao],
GMM-Based Classification Method for Continuous Prediction in Brain-Computer Interface,
ICPR06(I: 1171-1174).
IEEE DOI 0609
BibRef

Cheng, D.S.[Dong Seon], d'Amato, V., Murino, V.,
Wavelet-based Processing of EEG Data for Brain-Computer Interfaces,
VHCI05(III: 74-74).
IEEE DOI 0507
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Multiple Sclerosis Detection and Analysis .


Last update:Nov 18, 2017 at 20:56:18