Damien Coyle

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There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice in conjunction with physical practice (PP) of goal-directed rehabilitation tasks leads to enhanced functional recovery of paralyzed limbs among stroke sufferers. It is however difficult to confirm patient engagement during an MI in the absence of any(More)
This paper presents a feature extraction procedure (FEP) for a brain-computer interface (BCI) application where features are extracted from the electroencephalogram (EEG) recorded from subjects performing right and left motor imagery. Two neural networks (NNs) are trained to perform one-step-ahead predictions for the EEG time-series data, where one NN is(More)
This paper reviews several critical issues facing signal processing for brain-computer interfaces (BCIs) and suggests several recent approaches that should be further examined. The topics were selected based on discussions held during the 4th International BCI Meeting at a workshop organized to review and evaluate the current state of, and issues relevant(More)
The quantification of the spectral content of electroencephalogram (EEG) recordings has a substantial role in clinical and scientific applications. It is of particular relevance in the analysis of event-related brain oscillatory responses. This work is focused on the identification and quantification of relevant frequency patterns in motor imagery (MI)(More)
Brain-computer interfaces (BCIs) and basic computer games have been interconnected since BCI development began, exploiting gameplay elements as a means of enhancing performance in BCI training protocols and entertaining and challenging participants while training to use a BCI. By providing the BCI user with an entertaining environment, researchers hope to(More)
We present a lumped computational model of the thalamo-cortico-thalamic circuitry. The model essentially consists of two modules: a thalamic module and a cortical module. The thalamic module circuitry is a modified version of a classic neural mass computational model of the thalamic circuitry to simulate cortical alpha rhythms and which we have used in(More)
Electroencephalography (EEG) studies in Alzheimer's Disease (AD) patients show an attenuation of average power within the alpha band (7.5-13 Hz) and an increase of power in the theta band (4-7 Hz). Significant body of evidence suggest that thalamocortical circuitry underpin the generation and modulation of alpha and theta rhythms. The research presented in(More)
Neural networks (NNs) can be deployed in many different ways in signal processing applications. This paper illustrates how neural networks are employed in a prediction based preprocessing framework, referred to as neural-time-series-prediction-preprocessing (NTSPP), in an electroencephalogram (EEG)-based brain-computer interface (BCI). NTSPP has been shown(More)
Motor imagery can be used to modulate sensorimotor rhythms (SMR) enabling detection of voltage fluctuations on the surface of the scalp using electroencephalographic (EEG) electrodes. Feedback is essential in learning how to intentionally modulate SMR in non-muscular communication using a brain-computer interface (BCI). A BCI that is not reliant upon the(More)