@article{Williams2017,

title = { Affective Calibration of Musical Feature Sets in an Emotionally Intelligent Music Composition System},

author = {Duncan Williams and Alexis Kirke and Eduardo Miranda and Ian Daly and Faustina Hwang and James Weaver and Slawomir J. Nasuto},

url = {http://dl.acm.org/citation.cfm?id=3059005},

year  = {2017},

date = {2017-05-22},

journal = {ACM Transactions on Applied Perception (TAP)},

volume = {14},

number = {3},

keywords = {Affective composition, Affective computing, Music, Music generation},

pubstate = {published},

tppubtype = {article}

}

@article{JingDaly2017a,

title = {An improved P300 pattern in BCI to catch user’s attention},

author = {Jing Jin and Hanhan Zhang and Ian Daly and Xingyu Wang and Andrezej Chiciocki},

year  = {2017},

date = {2017-02-24},

journal = {Journal of Neural Engineering},

keywords = {BCI, P300},

pubstate = {published},

tppubtype = {article}

}

@article{Williams2016,

title = {A Perceptual and Affective Evaluation of an Affectively -Driven Engine for Video Game Soundtracking},

author = {Duncan Williams and Jamie Mears and Alexis Kirke and Eduardo Miranda and Ian Daly and Asad Malik and James Weaver and Faustina Hwang and Slawomir Nasuto},

year  = {2016},

date = {2016-06-29},

journal = {ACM Computers in Entertainment},

keywords = {Affective composition, Affective computing, Emotion, Music generation},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2016aBCMI,

title = {Affective Brain-Computer Music Interfacing},

author = {Ian Daly and Duncan Williams and Alexis Kirke and James Weaver and Asad Malik and Faustina Hwang and Eduardo Miranda and Slawomir J. Nasuto},

year  = {2016},

date = {2016-06-21},

journal = {Journal of Neural Engineering},

volume = {(accepted)},

keywords = {aBCMI, Affective composition, BCI, BCMI, Case based reasoning, EEG, Emotion, Hybrid BCI, Music generation},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2016faces,

title = {An Investigation Into The Use Of Six Facially Encoded Emotions In Brain-Computer Interfacing},

author = {Ian Daly and Long Chen and Sijie Zhou and Jing Jin},

year  = {2016},

date = {2016-02-01},

journal = {Brain Computer Interfaces},

keywords = {BCI, Emotion, Event-related potential, Facially encoded emotion, Oddball paradigm},

pubstate = {published},

tppubtype = {article}

}

@article{Huang2016,

title = {An exploration of spatial auditory BCI paradigms with different sounds: Music vs Beeps},

author = {Minqiang Huang and Ian Daly and Jing Jin and Yu Zhang and Xingyu Wang and Andrzej Cichocki},

year  = {2016},

date = {2016-01-20},

journal = {Cognitive Neurodynamics},

keywords = {BCI, Event-related potentials},

pubstate = {published},

tppubtype = {article}

}

@article{Chen2016,

title = {Exploring combinations of different color and facial expression stimuli for gaze-independent BCIs},

author = {Long Chen and Jing Jin and Ian Daly and Yu Zhang and Xingyu Wang and Andrzej Cichocki},

url = {http://journal.frontiersin.org/article/10.3389/fncom.2016.00005/abstract},

doi = {10.3389/fncom.2016.00005},

year  = {2016},

date = {2016-01-11},

journal = {Frontiers in Computational Neuroscience},

keywords = {BCI, Face expression change, Gaze independent BCI},

pubstate = {published},

tppubtype = {article}

}

@article{DalyPred2015,

title = {Music-induced emotions can be predicted from a combination of brain activity and acoustic features},

author = {Ian Daly and Duncan Williams and James Hallowell and Faustina Hwang and Alexis Kirke and Asad Malik and James Weaver and Eduardo Miranda and Slawomir J. Nasuto},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/music-induced-emotions-can-be-predicted-from-a-combination-of-brain-activity-and-acoustic-features.pdf},

doi = {10.1016/j.bandc.2015.08.003},

year  = {2015},

date = {2015-12-01},

journal = {Brain and Cognition},

volume = {101},

pages = {1-11},

abstract = {It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,p<0.001. This regression fit suggests that over 20% of the variance of the participant's music induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01).},

keywords = {Acoustic features, EEG, Emotion, Music},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2014a,

title = {FORCe: Fully Online and automated artifact Removal for brain-Computer interfacing},

author = {Ian Daly and Martin Billinger and Reinhold Scherer and Gernot Müller-Putz},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/FORCe-fully-online-and-automated-artifact-removal-for-brain-computer-interfacing.pdf},

doi = {10.1109/TNSRE.2014.2346621},

year  = {2015},

date = {2015-09-01},

journal = {IEEE in Transactions on Neural Systems & Rehabilitation Engineering},

volume = {23},

number = {5},

pages = {725-736},

abstract = {A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g., electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged Auto-Mutual Information Clustering (LAMIC) and Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.},

keywords = {Artefact removal, BCI, EEG, ICA, Tools, Wavelets},

pubstate = {published},

tppubtype = {article}

}

@article{WilliamsRD2015,

title = {Investigating Perceived Emotional Correlates of Rhythmic Density in Algorithmic Music Composition},

author = {Duncan Williams and Alexis Kirke and Eduardo Miranda and Ian Daly and James Hallowell and James Weaver and Asad Malik and Etienne Roesch and Faustina Hwang and Slawomir Nasuto},

doi = {10.1145/2749466},

year  = {2015},

date = {2015-07-01},

journal = {ACM Transactions on Applied Perception (TAP)},

volume = {12},

number = {3},

pages = {1-21},

abstract = {Affective algorithmic composition is a growing field that combines perceptually motivated affective computing strategies with novel music generation. This article presents work toward the development of one application. The long-term goal is to develop a responsive and adaptive system for inducing affect that is both controlled and validated by biophysical measures. Literature documenting perceptual responses to music identifies a variety of musical features and possible affective correlations, but perceptual evaluations of these musical features for the purposes of inclusion in a music generation system are not readily available. A discrete feature, rhythmic density (a function of note duration in each musical bar, regardless of tempo), was selected because it was shown to be well-correlated with affective responses in existing literature. A prototype system was then designed to produce controlled degrees of variation in rhythmic density via a transformative algorithm. A two-stage perceptual evaluation of a stimulus set created by this prototype was then undertaken. First, listener responses from a pairwise scaling experiment were analyzed via Multidimensional Scaling Analysis (MDS). The statistical best-fit solution was rotated such that stimuli with the largest range of variation were placed across the horizontal plane in two dimensions. In this orientation, stimuli with deliberate variation in rhythmic density appeared farther from the source material used to generate them than from stimuli generated by random permutation. Second, the same stimulus set was then evaluated according to the order suggested in the rotated two-dimensional solution in a verbal elicitation experiment. A Verbal Protocol Analysis (VPA) found that listener perception of the stimulus set varied in at least two commonly understood emotional descriptors, which might be considered affective correlates of rhythmic density. Thus, these results further corroborate previous studies wherein musical parameters are monitored for changes in emotional expression and that some similarly parameterized control of perceived emotional content in an affective algorithmic composition system can be achieved and provide a methodology for evaluating and including further possible musical features in such a system. Some suggestions regarding the test procedure and analysis techniques are also documented here.},

keywords = {Affective composition, Emotion, Music generation},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2014,

title = {A new hybrid BCI paradigm based on P300 and SSVEP},

author = {Jing Jin and Ian Daly and Yu Zhang and Xingyu Wang and Andrzej Cichocki},

url = {http://www.sciencedirect.com/science/article/pii/S016502701400209X},

doi = {doi:10.1016/j.jneumeth.2014.06.003},

year  = {2015},

date = {2015-04-15},

journal = {Journal of Neural Engineering},

volume = {244},

pages = {16–25},

abstract = {Background



P300 and steady-state visual evoked potential (SSVEP) approaches have been widely used for brain–computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored.



New method



The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength.



Result



The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm.



Comparison with existing method



A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm. All the paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification.



Conclusions



The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm.},

keywords = {BCI, Event-related potential, Hybrid BCI, P300, SSVEP},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2014_featSel,

title = {Automated identification of neural correlates of continuous variables},

author = {Ian Daly and Faustina Hwang and Alexis Kirke and Asad Malik and James Weaver and Duncan Williams and Eduardo Miranda and Slawomir Nasuto},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/Automated-identification-of-neural-correlates-of-continous-variables.pdf},

doi = {10.1016/j.jneumeth.2014.12.012},

year  = {2015},

date = {2015-03-15},

journal = {Journal of Neuroscience Methods},

volume = {242},

pages = { 65–71},

abstract = {Background



The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables.



New method



A method is presented for the automated identification of features that differentiate two or more groups in neurological datasets based upon a spectral decomposition of the feature set. Furthermore, the method is able to identify features that relate to continuous independent variables.



Results



The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally, the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions.



Comparison with existing methods



The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases.



Conclusions



The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.},

keywords = {EEG, Feature selection},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2014tempoBCI,

title = {Investigating music tempo as a feedback mechanism for closed-loop BCI control},

author = {Ian Daly and Duncan Williams and Faustina Hwang and Alexis Kirke and Asad Malik and Etienne Roesch and James Weaver and Eduardo Miranda and Slawomir Nasuto},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/tempoBCI.pdf},

doi = {10.1080/2326263X.2014.979728},

year  = {2014},

date = {2014-10-17},

journal = {Brain-Computer Interfaces},

volume = {1},

number = {3},

pages = {158-169},

abstract = {The feedback mechanism used in a brain-computer interface (BCI) forms an integral part of the closed-loop learning process required for successful operation of a BCI. However, ultimate success of the BCI may be dependent upon the modality of the feedback used. This study explores the use of music tempo as a feedback mechanism in BCI and compares it to the more commonly used visual feedback mechanism. Three different feedback modalities are compared for a kinaesthetic motor imagery BCI: visual, auditory via music tempo, and a combined visual and auditory feedback modality. Visual feedback is provided via the position, on the y-axis, of a moving ball. In the music feedback condition, the tempo of a piece of continuously generated music is dynamically adjusted via a novel music-generation method. All the feedback mechanisms allowed users to learn to control the BCI. However, users were not able to maintain as stable control with the music tempo feedback condition as they could in the visual feedback and combined conditions. Additionally, the combined condition exhibited significantly less inter-user variability, suggesting that multi-modal feedback may lead to more robust results. Finally, common spatial patterns are used to identify participant-specific spatial filters for each of the feedback modalities. The mean optimal spatial filter obtained for the music feedback condition is observed to be more diffuse and weaker than the mean spatial filters obtained for the visual and combined feedback conditions.},

keywords = {BCI, BCMI, ERD, Motor imagery, Music, Tempo},

pubstate = {published},

tppubtype = {article}

}

@article{Williams2014,

title = {Investigating affect in algorithmic composition systems},

author = {Duncan Williams and Alexis Kirke and Eduardo Miranda and Etienne Roesch and Ian Daly and Slawomir Nasuto},

doi = {10.1177/0305735614543282},

year  = {2014},

date = {2014-09-15},

journal = {Psychology of Music},

pages = {1-24},

abstract = {There has been a significant amount of work implementing systems for algorithmic composition with the intention of targeting specific emotional responses in the listener, but a full review of this work is not currently available. This gap creates a shared obstacle to those entering the field. Our aim is thus to give an overview of progress in the area of these affectively driven systems for algorithmic composition. Performative and transformative systems are included and differentiated where appropriate, highlighting the challenges these systems now face if they are to be adapted to, or have already incorporated, some form of affective control. Possible real-time applications for such systems, utilizing affectively driven algorithmic composition and biophysical sensing to monitor and induce affective states in the listener are suggested.},

keywords = {Emotion, Music, Music generation},

pubstate = {published},

tppubtype = {article}

}

@article{Bauernfeind2014,

title = {Separating heart and brain: On the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals},

author = {Gunther Bauernfeind and Selina Wriessnegger and Ian Daly and Gernot Müller-Putz},

doi = {10.1088/1741-2560/11/5/056010},

year  = {2014},

date = {2014-09-11},

journal = {Journal of Neural Engineering},

volume = {11},

number = {5},

pages = {1-18},

abstract = {Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.},

keywords = {Artefact removal, fNIRS, ICA, Mayer wave},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2014,

title = {Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control},

author = {Ian Daly and Josef Faller and Reinhold Scherer and Catherine Sweeney-Reed and Slawomir J. Nasuto and Martin Billinger and Gernot Müller-Putz},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/Exploration-of-the-neural-correlates-of-cerebral-palsy-for-sensorimotor-BCI-control.pdf},

doi = {10.3389/fneng.2014.00020},

year  = {2014},

date = {2014-07-09},

journal = {Frontiers in Neuroengineering},

volume = {7},

number = {20},

abstract = {Cerebral palsy (CP) includes a broad range of disorders, which can result in impairment of posture and movement control. Brain-computer interfaces (BCIs) have been proposed as assistive devices for individuals with CP. Better understanding of the neural processing underlying motor control in affected individuals could lead to more targeted BCI rehabilitation and treatment options. We have explored well-known neural correlates of movement, including event-related desynchronization (ERD), phase synchrony, and a recently-introduced measure of phase dynamics, in participants with CP and healthy control participants. Although present, significantly less ERD and phase locking were found in the group with CP. Additionally, inter-group differences in phase dynamics were also significant. Taken together these findings suggest that users with CP exhibit lower levels of motor cortex activation during motor imagery, as reflected in lower levels of ongoing mu suppression and less functional connectivity. These differences indicate that development of BCIs for individuals with CP may pose additional challenges beyond those faced in providing BCIs to healthy individuals.},

keywords = {BCI, Cerebral palsy, ERD, Motor imagery},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2014NC,

title = {Neural correlates of emotional responses to music: an EEG study},

author = {Ian Daly and Asad Malik and Faustina Hwang and Etienne Roesch and James Weaver and Alexis Kirke and Duncan Williams and Eduardo Miranda and Slawomir J. Nasuto},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/Neural-correlates-of-emotional-responses-to-music-an-EEG-study-pub.pdf},

doi = {10.1016/j.neulet.2014.05.003},

year  = {2014},

date = {2014-06-24},

journal = {Neuroscience letters},

volume = {573},

pages = {52–57},

abstract = {This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses.



We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures, to be significantly different between groups of music-induced emotional responses.},

keywords = {Asymmetry, EEG, Emotion, Functional connectivity, Music},

pubstate = {published},

tppubtype = {article}

}

@article{Muller-Putz2014,

title = {Motor imagery induced EEG patterns in spinal cord injury patients and their impact on Brain-Computer Interface accuracy},

author = {Gernot Müller-Putz and Ian Daly and Vera Kaiser},

url = {http://www.ncbi.nlm.nih.gov/pubmed/24835837},

doi = {10.1088/1741-2560/11/3/035011},

year  = {2014},

date = {2014-06-01},

journal = {Journal of Neural Engineering},

volume = {11},

number = {3},

pages = {1-9},

abstract = {OBJECTIVE:

Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI.

APPROACH:

Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups.

MAIN RESULTS:

It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%).

SIGNIFICANCE:

The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.},

keywords = {BCI, ERD, Functional connectivity, Motor imagery, SCI},

pubstate = {published},

tppubtype = {article}

}

@article{Jin2014,

title = {An optimized ERP Brain-computer interface based on facial expression changes},

author = {Jing Jin and Ian Daly and Yu Zhang and Xingyu Wang and Andrzej Cichocki},

url = {http://iopscience.iop.org/article/10.1088/1741-2560/11/3/036004/pdf},

doi = {10.1088/1741-2560/11/3/036004},

year  = {2014},

date = {2014-06-01},

journal = {Journal of Neural Engineering},

volume = {11},

number = {3},

pages = {1-11},

abstract = {OBJECTIVE:

Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain-computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern.

APPROACH:

Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures.

MAIN RESULTS:

The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05).

SIGNIFICANCE:

The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.},

keywords = {BCI, Event-related potentials, Facial expressions},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2013artComp,

title = {Automated artifact removal from the electroencephalogram; a comparative study},

author = {Ian Daly and Nicoletta Nicolaou and Slawomir J. Nasuto and Kevin Warwick},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/published_MS_authors_copy.pdf},

doi = {10.1177/1550059413476485},

year  = {2013},

date = {2013-10-01},

journal = {Clinical EEG and Neuroscience},

volume = {44},

number = {4},

pages = {291-306},

abstract = {Contamination of the electroencephalogram (EEG) by artifacts greatly reduces the quality of the recorded signals. There is a need for automated artifact removal methods. However, such methods are rarely evaluated against one another via rigorous criteria, with results often presented based upon visual inspection alone. This work presents a comparative study of automatic methods for removing blink, electrocardiographic, and electromyographic artifacts from the EEG. Three methods are considered; wavelet, blind source separation (BSS), and multivariate singular spectrum analysis (MSSA)-based correction. These are applied to data sets containing mixtures of artifacts. Metrics are devised to measure the performance of each method. The BSS method is seen to be the best approach for artifacts of high signal to noise ratio (SNR). By contrast, MSSA performs well at low SNRs but at the expense of a large number of false positive corrections.},

keywords = {Artefact removal, EEG, ICA, MSSA, Wavelets},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2013cpBCI,

title = {On the control of Brain-computer interfaces by users with Cerebral palsy},

author = {Ian Daly and Martin Billinger and Jose Laparra-Hernandez and Fabio Aloise and Mariano Lloria Garcia and Josef Faller and Reinhold Scherer and Gernot Muller-Putz},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/draft_6-0.pdf},

doi = {10.1016/j.clinph.2013.02.118},

year  = {2013},

date = {2013-09-01},

journal = {Clinical Neurophysiology},

volume = {124},

number = {9},

pages = {1787-1797},

abstract = {OBJECTIVE:

Brain-computer interfaces (BCIs) have been proposed as a potential assistive device for individuals with cerebral palsy (CP) to assist with their communication needs. However, it is unclear how well-suited BCIs are to individuals with CP. Therefore, this study aims to investigate to what extent these users are able to gain control of BCIs.

METHODS:

This study is conducted with 14 individuals with CP attempting to control two standard online BCIs (1) based upon sensorimotor rhythm modulations, and (2) based upon steady state visual evoked potentials.

RESULTS:

Of the 14 users, 8 are able to use one or other of the BCIs, online, with a statistically significant level of accuracy, without prior training. Classification results are driven by neurophysiological activity and not seen to correlate with occurrences of artifacts. However, many of these users' accuracies, while statistically significant, would require either more training or more advanced methods before practical BCI control would be possible.

CONCLUSIONS:

The results indicate that BCIs may be controlled by individuals with CP but that many issues need to be overcome before practical application use may be achieved.

SIGNIFICANCE:

This is the first study to assess the ability of a large group of different individuals with CP to gain control of an online BCI system. The results indicate that six users could control a sensorimotor rhythm BCI and three a steady state visual evoked potential BCI at statistically significant levels of accuracy (SMR accuracies; mean ± STD, 0.821 ± 0.116, SSVEP accuracies; 0.422 ± 0.069).},

keywords = {BCI, Cerebral palsy, ERD, Motor imagery, SSVEP},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2012phase,

title = {Testing for significance of phase synchronisation dynamics in the EEG},

author = {Ian Daly and Catherine Sweeney-Reed and Slawomir J. Nasuto},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/Testing-for-significance-of-phase-synchronisation-dynamics-in.pdf},

doi = {10.1007/s10827-012-0428-2},

year  = {2013},

date = {2013-06-01},

journal = {Journal of Computational Neuroscience},

volume = {34},

number = {3},

pages = {411-432},

abstract = {A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.},

keywords = {EEG, Functional connectivity, Markov models, Semi-Markov models, Significance testing},

pubstate = {published},

tppubtype = {article}

}

@article{Scherer2013,

title = {On the use of games for non-invasive EEG-based Functional Brain Mapping},

author = {Reinhold Scherer and Gunther Moitzi and Ian Daly and Gernot Müller-Putz},

url = {https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwivypDisKzKAhWDaxQKHSN7CVgQFgggMAA&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel7%2F4804728%2F6527957%2F06472046.pdf%3Farnumber%3D6472046&usg=AFQjCNF1qrlxBoeaT4OaHviOGyqy6IZmNg&sig2=lgQU_N9tXnpU7wRB3M9Efg},

doi = {10.1109/TCIAIG.2013.2250287},

year  = {2013},

date = {2013-06-01},

journal = {IEEE Transactions on Computational Intelligence and AI in Games},

volume = {5},

number = {2},

pages = {155-163},

abstract = {The use of statistical models and statistical inference

for characterizing the interplay between brain structures and

human behavior (functional brain mapping) is common in neuroscience.

Statistical methods, however, require the availability of

sufficiently large data sets. As a result, experimental paradigms

used to collect behavioral trials from individuals are data centered

and not user centered. This means that experimental paradigms

are tuned to collect as many trials as possible, are generally rather

demanding, and are not always motivating or engaging for individuals.

Subject cooperation and their compliance with the task may

decrease over time. Whenever possible, paradigms are designed

to control for factors such as fatigue, attention, and motivation.

In this paper, we propose the use of the Kinect motion tracking

sensor (Microsoft, Inc., Redmond, WA, USA) in a game-based

paradigm for noninvasive electroencephalogram (EEG)-based

functional motor mapping. Results from an experimental study

with able-bodied subjects playing a virtual ball game suggest

that the Kinect sensor is useful for isolating specific movements

during the interaction with the game, and that the computed EEG

patterns for hand and feet movements are in agreement with

results described in the literature},

keywords = {BCI, ERD, Games, Kinect, Motor imagery},

pubstate = {published},

tppubtype = {article}

}

@article{Daly2013headArtifacts,

title = {On the automated removal of artifacts related to head movement from the EEG},

author = {Ian Daly and Martin Billinger and Reinhold Scherer and Gernot Muller-Putz},

url = {http://www.iandaly.co.uk/newDesign2016/wp-content/uploads/2016/01/On-the-automated-removal-of-artifacts-related-to-head-movement-from-the-EEG.pdf},

doi = {10.1109/TNSRE.2013.2254724},

issn = {1534-4320},

year  = {2013},

date = {2013-05-01},

journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},

volume = {21},

number = {3},

pages = {427 - 434},

abstract = {Contamination of the electroencephalogram (EEG) by artifacts related to head movement is a major cause of reduced signal quality. This is a problem in both neuroscience and other uses of the EEG. To attempt to reduce the influence, on the EEG, of artifacts related to head movement, an accelerometer is placed on the head and independent component analysis is applied to attempt to separate artifacts which are statistically related to head movements. To evaluate the method, EEG and accelerometer measurements are made from 14 individuals with Cerebral palsy attempting to control a sensorimotor rhythm based brain-computer interface. Results show that the approach significantly reduces the influence of head movement related artifacts in the EEG.},

keywords = {Artefact removal, EEG, EMG, Head movement, ICA},

pubstate = {published},

tppubtype = {article}

}

@article{Chen2013a,

title = {Event-related desynchronization (ERD) in the alpha band during a hand mental rotation task},

author = {Xiaogang Chen and Guangyu Bin and Ian Daly and Xiaorong Gao},

url = {http://www.ncbi.nlm.nih.gov/pubmed/23458675},

doi = {10.1016/j.neulet.2013.02.036},

year  = {2013},

date = {2013-04-29},

journal = {Neuroscience Letters},

volume = {541},

pages = {238-242},

abstract = {Recent studies have demonstrated that mentally rotating the hands involves participants engaging in motor imagery processing. However, far less is known about the possible neurophysiological basis of such processing. To contribute to a better understanding of hand mental rotation processing, event-related spectral perturbation (ERSP) methods were applied to electroencephalography (EEG) data collected from participants mentally rotating their hands. Time-frequency analyses revealed that alpha-band power suppression was larger over central-parietal regions. This is in accordance with motor imagery findings suggesting that the motor regions may be involved in processing or detection of kinaesthetic information. Furthermore, the presence of a significant negative correlation between reaction times (RTs) and alpha-band power suppression over central regions is illustrated. These findings are consistent with the neural efficiency hypothesis, which proposes the non-use of many brain regions irrelevant for the task performance as well as the more focused use of specific task-related regions in individuals with better performance. These results indicate that ERSP provides some independent insights into the mental rotation process and further confirms that parietal and motor cortices are involved in mental rotation.},

keywords = {EEG, ERD, Hand rotation},

pubstate = {published},

tppubtype = {article}

}

@article{Jin2012,

title = {Whether generic model works for rapid ERP-based BCI calibration},

author = {Jing Jin and Eric W. Sellers and Yu Zhang and Ian Daly and Xingyu Wang and Andrzej Cichocki},

doi = {10.1016/j.jneumeth.2012.09.020},

year  = {2013},

date = {2013-01-13},

journal = {Journal of Neuroscience Methods},

volume = {212},

number = {1},

pages = {94-99},

abstract = {Event-related potential (ERP)-based brain-computer interfacing (BCI) is an effective method of basic communication. However, collecting calibration data, and classifier training, detracts from the amount of time allocated for online communication. Decreasing calibration time can reduce preparation time thereby allowing for additional online use, potentially lower fatigue, and improved performance. Previous studies, using generic online training models which avoid offline calibration, afford more time for online spelling. Such studies have not examined the direct effects of the model on individual performance, and the training sequence exceeded the time reported here. The first goal of this work is to survey whether one generic model works for all subjects and the second goal is to show the performance of a generic model using an online training strategy when participants could use the generic model. The generic model was derived from 10 participant's data. An additional 11 participants were recruited for the current study. Seven of the participants were able to use the generic model during online training. Moreover, the generic model performed as well as models obtained from participant specific offline data with a mean training time of less than 2 min. However, four of the participants could not use this generic model, which shows that one generic mode is not generic for all subjects. More research on ERPs of subjects with different characteristics should be done, which would be helpful to build generic models for subject groups. This result shows a potential valuable direction for improving the BCI system.},

keywords = {BCI, Classification, Event-related potentials, Generic model},

pubstate = {published},

tppubtype = {article}

}

@article{Pfurtscheller2012a,

title = {Coupling between intrinsic prefrontal HbO2 and central EEG beta power oscillations in the resting brain},

author = {Gert Pfurtscheller and Ian Daly and Gunther Bauernfeind and Gernot R. Muller-Putz},

url = {http://www.iandaly.co.uk/wp-content/uploads/2016/01/journal.pone_.0043640.pdf},

doi = {10.1371/journal.pone.0043640},

year  = {2012},

date = {2012-08-24},

journal = {PLOS One},

volume = {7},

number = {8},

pages = {1-9},

abstract = {There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration  100s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence >0.8) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains’ motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007).},

keywords = {Beta coupling, EEG, fNIRS, Resting state},

pubstate = {published},

tppubtype = {article}

}

@article{Kaiser2012stroke,

title = {Relationship between electrical brain responses to motor imagery and motor impairment in stroke.},

author = {Vera Kaiser and Ian Daly and Floriana Pichiorri and Donatella Mattia and Gernot R. Muller-Putz and Christa Neuper},

doi = {10.1161/​STROKEAHA.112.665489},

year  = {2012},

date = {2012-08-14},

journal = {Stroke},

volume = {43},

number = {10},

pages = {2735-2740},

abstract = {BACKGROUND AND PURPOSE:

New strategies like motor imagery based brain-computer interfaces, which use brain signals such as event-related desynchronization (ERD) or event-related synchronization (ERS) for motor rehabilitation after a stroke, are undergoing investigation. However, little is known about the relationship between ERD and ERS patterns and the degree of stroke impairment. The aim of this work was to clarify this relationship.

METHODS:

EEG during motor imagery and execution were measured in 29 patients with first-ever monolateral stroke causing any degree of motor deficit in the upper limb. The strength and laterality of the ERD or ERS patterns were correlated with the scores of the European Stroke Scale, the Medical Research Council, and the Modified Ashworth Scale.

RESULTS:

Mean age of the patients was 58 ± 15 years; mean time from the incident was 4 ± 4 months. Stroke lesions were cortical (n=8), subcortical (n=11), or mixed (n=10), attributable to either an ischemic event (n=26) or a hemorrhage (n=3), affecting the right (n=16) or left (n=13) hemisphere. Higher impairment was related to stronger ERD in the unaffected hemisphere and higher spasticity was related to stronger ERD in the affected hemisphere. Both were related to a relatively stronger ERS in the affected hemisphere.

CONCLUSIONS:

The results of this study may have implications for the design of potential poststroke rehabilitation interventions based on brain-computer interface technologies that use neurophysiological signals like ERD or ERS as neural substrates for the mutual interaction between brain and machine and, ultimately, help stroke patients to regain motor control.},

keywords = {BCI, ERD, Motor imagery, Stroke},

pubstate = {published},

tppubtype = {article}

}