Publications
2021
Li, Shurui; Daly, Ian; Wang, Xingyu; Lam, Hak-Keung; Cichocki, Andrzej
Enhancing P300 based character recognition performance using a combination of ensemble classifiers and a fuzzy fusion method Journal Article
In: Journal of Neuroscience Methods, 2021.
BibTeX | Tags: BCI, Classification, EEG, ERP, Event-related potential, Fuzzy logic, P300
@article{Li2021,
title = {Enhancing P300 based character recognition performance using a combination of ensemble classifiers and a fuzzy fusion method},
author = {Shurui Li and Ian Daly and Xingyu Wang and Hak-Keung Lam and Andrzej Cichocki},
year = {2021},
date = {2021-08-05},
journal = {Journal of Neuroscience Methods},
keywords = {BCI, Classification, EEG, ERP, Event-related potential, Fuzzy logic, P300},
pubstate = {published},
tppubtype = {article}
}
Torres, Juan Ramirez; Daly, Ian
How to build a fast and accurate Code-Modulated Brain-Computer Interface Journal Article
In: Journal of Neural Engineering, 2021.
BibTeX | Tags: BCI, Classification, cVEP, EEG, ERP, Event-related potential, Feature selection
@article{Ramirez-Torres2021,
title = {How to build a fast and accurate Code-Modulated Brain-Computer Interface},
author = {Juan Ramirez Torres and Ian Daly},
year = {2021},
date = {2021-04-21},
journal = {Journal of Neural Engineering},
keywords = {BCI, Classification, cVEP, EEG, ERP, Event-related potential, Feature selection},
pubstate = {published},
tppubtype = {article}
}
2020
Daly, Ian
Neural component analysis: a spatial filter for electroencephalogram analysis Journal Article
In: Journal of Neuroscience Methods, 2020.
BibTeX | Tags: Classification, EEG, ERP, Event-related potential, Feature selection, Machine learning
@article{Daly2020NCA,
title = {Neural component analysis: a spatial filter for electroencephalogram analysis},
author = {Ian Daly},
year = {2020},
date = {2020-10-20},
journal = {Journal of Neuroscience Methods},
keywords = {Classification, EEG, ERP, Event-related potential, Feature selection, Machine learning},
pubstate = {published},
tppubtype = {article}
}
Li, Shurui; Jin, Jing; Daly, Ian; Zuo, Cili; Wang, Xingyu; Cichocki, Andrzej
Comparison of the ERP-Based BCI Performance Among Chromatic (RGB) Semitransparent Face Patterns Journal Article
In: Frontiers Neuroscience, vol. 14, no. 54, pp. 12, 2020.
Abstract | Links | BibTeX | Tags: BCI, ERP, Event-related potential
@article{Li2020,
title = {Comparison of the ERP-Based BCI Performance Among Chromatic (RGB) Semitransparent Face Patterns},
author = {Shurui Li and Jing Jin and Ian Daly and Cili Zuo and Xingyu Wang and Andrzej Cichocki},
doi = {10.3389/fnins.2020.00054},
year = {2020},
date = {2020-01-31},
journal = {Frontiers Neuroscience},
volume = {14},
number = {54},
pages = {12},
abstract = {Objective: Previous studies have shown that combing with color properties may be
used as part of the display presented to BCI users in order to improve performance.
Build on this, we explored the effects of combinations of face stimuli with three
primary colors (RGB) on BCI performance which is assessed by classification accuracy
and information transfer rate (ITR). Furthermore, we analyzed the waveforms of
three patterns.
Methods: We compared three patterns in which semitransparent face is overlaid three
primary colors as stimuli: red semitransparent face (RSF), green semitransparent face
(GSF), and blue semitransparent face (BSF). Bayesian linear discriminant analysis (BLDA)
was used to construct the individual classifier model. In addition, a Repeated-measures
ANOVA (RM-ANOVA) and Bonferroni correction were chosen for statistical analysis.
Results: The results indicated that the RSF pattern achieved the highest online
averaged accuracy with 93.89%, followed by the GSF pattern with 87.78%, while the
lowest performance was caused by the BSF pattern with an accuracy of 81.39%.
Furthermore, significant differences in classification accuracy and ITR were found
between RSF and GSF .p < 0:05/ and between RSF and BSF patterns .p < 0:05/.
Conclusion: The semitransparent faces colored red (RSF) pattern yielded the best
performance of the three patterns. The proposed patterns based on ERP-BCI system
have a clinically significant impact by increasing communication speed and accuracy of
the P300-speller for patients with severe motor impairment.},
keywords = {BCI, ERP, Event-related potential},
pubstate = {published},
tppubtype = {article}
}
used as part of the display presented to BCI users in order to improve performance.
Build on this, we explored the effects of combinations of face stimuli with three
primary colors (RGB) on BCI performance which is assessed by classification accuracy
and information transfer rate (ITR). Furthermore, we analyzed the waveforms of
three patterns.
Methods: We compared three patterns in which semitransparent face is overlaid three
primary colors as stimuli: red semitransparent face (RSF), green semitransparent face
(GSF), and blue semitransparent face (BSF). Bayesian linear discriminant analysis (BLDA)
was used to construct the individual classifier model. In addition, a Repeated-measures
ANOVA (RM-ANOVA) and Bonferroni correction were chosen for statistical analysis.
Results: The results indicated that the RSF pattern achieved the highest online
averaged accuracy with 93.89%, followed by the GSF pattern with 87.78%, while the
lowest performance was caused by the BSF pattern with an accuracy of 81.39%.
Furthermore, significant differences in classification accuracy and ITR were found
between RSF and GSF .p < 0:05/ and between RSF and BSF patterns .p < 0:05/.
Conclusion: The semitransparent faces colored red (RSF) pattern yielded the best
performance of the three patterns. The proposed patterns based on ERP-BCI system
have a clinically significant impact by increasing communication speed and accuracy of
the P300-speller for patients with severe motor impairment.
2019
Jin, Jing; Li, Shurui; Daly, Ian; Miao, Yangyang; Liu, Chang; Wang, Xingyu; Cichocki, Andrzej
The Study of Generic Model Set for Reducing Calibration Time in P300-based Brain-Computer Interface Journal Article
In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019.
Abstract | Links | BibTeX | Tags: BCI, ERP, Event-related potential, Machine learning, P300
@article{Jin2019c,
title = {The Study of Generic Model Set for Reducing Calibration Time in P300-based Brain-Computer Interface},
author = {Jing Jin and Shurui Li and Ian Daly and Yangyang Miao and Chang Liu and Xingyu Wang and Andrzej Cichocki},
url = {https://ieeexplore.ieee.org/document/8917686},
doi = {10.1109/TNSRE.2019.2956488},
year = {2019},
date = {2019-11-28},
journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
abstract = {P300-based brain-computer interfaces (BCIs) provide an additional communication channel for individuals with communication disabilities. In general, P300-based BCIs need to be trained, offline, for a considerable period of time, which causes users to become fatigued. This reduces the efficiency and performance of the system. In order to shorten calibration time and improve system performance, we introduce the concept of a generic model set. We used ERP data from 116 participants to train the generic model set. The resulting set consists of ten models, which are trained by weighted linear discriminant analysis (WLDA). Twelve new participants were then invited to test the validity of the generic model set. The results demonstrated that all new participants matched the best generic model. The resulting mean classification accuracy equaled 80% after online training, an accuracy that was broadly equivalent to the typical training model method. Moreover, the calibration time was shortened by 70.7% of the calibration time of the typical model method. In other words, the best matching model method only took 81s to calibrate, while the typical model method took 276s. There were also significant differences in both accuracy and raw bit rate between the best and the worst matching model methods. We conclude that the strategy of combining the generic models with online training is easily accepted and achieves higher levels of user satisfaction (as measured by subjective reports). Thus, we provide a valuable new strategy for improving the performance of P300-based BCI.},
keywords = {BCI, ERP, Event-related potential, Machine learning, P300},
pubstate = {published},
tppubtype = {article}
}
Cheng, J; Jin, J; Daly, I; Zhang, Y; Wang, B; Wang, X; Cichocki, A
Effect of a combination of flip and zooming stimuli on the performance of a visual brain-computer interface for spelling Journal Article
In: Biomedical Engineering/Biomedizinische Technik, vol. 64, no. 1, pp. 29-38, 2019.
BibTeX | Tags: BCI, ERP, Event-related potential, Event-related potentials
@article{Cheng2019,
title = {Effect of a combination of flip and zooming stimuli on the performance of a visual brain-computer interface for spelling},
author = {J Cheng and J Jin and I Daly and Y Zhang and B Wang and X Wang and A Cichocki},
year = {2019},
date = {2019-01-14},
journal = {Biomedical Engineering/Biomedizinische Technik},
volume = {64},
number = {1},
pages = {29-38},
keywords = {BCI, ERP, Event-related potential, Event-related potentials},
pubstate = {published},
tppubtype = {article}
}
2018
Cheng, J; Jin, J; Daly, I; Zhang, Y; Wang, B; Wang, X; Cichocki, A
Effect of a combination of flip and zooming stimuli on the performance of a visual brain-computer interface for spelling. Journal Article
In: Biomed Tech (Berl), 2018.
Links | BibTeX | Tags: BCI, ERP, P300
@article{Cheng2018,
title = {Effect of a combination of flip and zooming stimuli on the performance of a visual brain-computer interface for spelling.},
author = {J Cheng and J Jin and I Daly and Y Zhang and B Wang and X Wang and A Cichocki},
doi = {10.1515/bmt-2017-0082},
year = {2018},
date = {2018-02-13},
journal = {Biomed Tech (Berl)},
keywords = {BCI, ERP, P300},
pubstate = {published},
tppubtype = {article}
}
2017
Minqiang, Huang; Daly, Ian; Xingyu, Wang; Jing, Jin
A pleasant auditory brain computer interface using natural environment sounds Conference
Graz BCI conference 2017, 2017.
@conference{Minqiang2017,
title = {A pleasant auditory brain computer interface using natural environment sounds},
author = {Huang Minqiang and Ian Daly and Wang Xingyu and Jin Jing},
year = {2017},
date = {2017-05-05},
publisher = {Graz BCI conference 2017},
keywords = {BCI, EEG, ERP},
pubstate = {published},
tppubtype = {conference}
}
2013
Daly, Ian; Billinger, Martin; Scherer, Reinhold; Muller-Putz, Gernot
Brain-computer interfacing for users with Cerebral palsy, challenges and opportunities Conference
Lecture notes in computer science, 7th International Conference, UAHCI 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013, Proceedings, Part I, Springer, 2013, ISBN: 978-3-642-39187-3.
Abstract | Links | BibTeX | Tags: BCI, Cerebral palsy, ERD, ERP, SVEP, Tools
@conference{Daly2013HCI,
title = {Brain-computer interfacing for users with Cerebral palsy, challenges and opportunities},
author = {Ian Daly and Martin Billinger and Reinhold Scherer and Gernot Muller-Putz},
url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/draft_1-1.pdf},
doi = {10.1007/978-3-642-39188-0_67},
isbn = {978-3-642-39187-3},
year = {2013},
date = {2013-07-21},
booktitle = {Lecture notes in computer science, 7th International Conference, UAHCI 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013, Proceedings, Part I},
journal = {Lecture notes in computer science},
pages = {623-632},
publisher = {Springer},
abstract = {It has been proposed that hybrid Brain-computer interfaces (hBCIs) could benefit individuals with Cerebral palsy (CP). To this end we review the results of two BCI studies undertaken with a total of 20 individuals with CP to determine if individuals in this user group can achieve BCI control.
Large performance differences are found between individuals. These are investigated to determine their possible causes. Differences in subject characteristics are observed to significantly relate to BCI performance accuracy. Additionally, significant relationships are also found between some subject characteristics and EEG components that are important for BCI control. Therefore, it is suggested that knowledge of individual users may guide development towards overcoming the challenges involved in providing BCIs that work well for individuals with CP.},
keywords = {BCI, Cerebral palsy, ERD, ERP, SVEP, Tools},
pubstate = {published},
tppubtype = {conference}
}
Large performance differences are found between individuals. These are investigated to determine their possible causes. Differences in subject characteristics are observed to significantly relate to BCI performance accuracy. Additionally, significant relationships are also found between some subject characteristics and EEG components that are important for BCI control. Therefore, it is suggested that knowledge of individual users may guide development towards overcoming the challenges involved in providing BCIs that work well for individuals with CP.