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Subject = BCI;
8 items found
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Displaying Results 1 - 8 of 8 on page 1 of 1
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An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy
(2014)
Leamy, Darren J.; Kocijan, Jus; Domijan, Katarina; Duffin, Joseph; Roche, Richard; Comm...
An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy
(2014)
Leamy, Darren J.; Kocijan, Jus; Domijan, Katarina; Duffin, Joseph; Roche, Richard; Commins, Sean; Collins, Ronan; Ward, Tomas E.
Abstract:
Background: Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke. Methods: 32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data. Results: Stroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification accuracy of stroke-affected EEG is lower than the average for healthy EEG. Classificati...
http://mural.maynoothuniversity.ie/6074/
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Artefact detection and removal algorithms for EEG diagnostic systems
(2013)
O'Regan, Simon H.
Artefact detection and removal algorithms for EEG diagnostic systems
(2013)
O'Regan, Simon H.
Abstract:
The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be ...
http://hdl.handle.net/10468/1391
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Independent brain computer interface control using visual spatial attention-dependent modulations of parieto-occipital alpha
(2005)
LALOR, EDMUND; REILLY, RICHARD
Independent brain computer interface control using visual spatial attention-dependent modulations of parieto-occipital alpha
(2005)
LALOR, EDMUND; REILLY, RICHARD
Abstract:
peer-reviewed
Parieto-occipital alpha band (8-14 Hz) EEG activity was examined daring a spatial attention-based brain computer interface paradigm for its potential use as a feature for left/right spatial attention classification. In this paradigm 64-channel EEG data were recorded from subjects who covertly attended to a sequence of letters superimposed on a flicker stimulus in one visual field while ignoring a similar stimulus in the opposite visual field. Increases in alpha band activity were observed over parieto-occipital cortex contralateral to the location of the ignored stimulus, consistent with previous reports, and the subsequent use of alpha band power over bilateral parieto-occipital sites as a feature yielded an average classification accuracy of 73% across 10 subjects, with highest 87%. The highest achievable bit rate from these data is 7.5 bits/minute
http://hdl.handle.net/2262/19519
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Independent brain computer interfacing control using visual spatial attention-dependent modulations of parieto-occipital alpha
(2005)
LALOR, EDMUND; REILLY, RICHARD
Independent brain computer interfacing control using visual spatial attention-dependent modulations of parieto-occipital alpha
(2005)
LALOR, EDMUND; REILLY, RICHARD
Abstract:
peer-reviewed
Parieto-occipital alpha band (8-14 Hz) EEG activity was examined daring a spatial attention-based brain computer interface paradigm for its potential use as a feature for left/right spatial attention classification. In this paradigm 64-channel EEG data were recorded from subjects who covertly attended to a sequence of letters superimposed on a flicker stimulus in one visual field while ignoring a similar stimulus in the opposite visual field. Increases in alpha band activity were observed over parieto-occipital cortex contralateral to the location of the ignored stimulus, consistent with previous reports, and the subsequent use of alpha band power over bilateral parieto-occipital sites as a feature yielded an average classification accuracy of 73% across 10 subjects, with highest 87%. The highest achievable bit rate from these data is 7.5 bits/minute
http://hdl.handle.net/2262/19659
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Motion-onset visual evoked potentials for gaming: A pilot study
(2013)
Marshall, D.; Coyle, D.; Wilson, S.
Motion-onset visual evoked potentials for gaming: A pilot study
(2013)
Marshall, D.; Coyle, D.; Wilson, S.
Abstract:
This paper details a pilot study for a motion onset Visual Evoked Potential (mVEP) based Brain Computer Interface (BCI) controlled game. mVEP is a type of VEP that uses visual responses from the dorsal pathway of the visual system allowing elegant visual stimuli to elicit different brain patterns depending on the motion and position of the stimuli. The study here was conducted to determine the most appropriate methods, parameters and EEG setup to use in order to extract reliable information when classifying responses on up to five different stimuli. Initial offline results show that 80% accuracy can achieved by averaging stimuli over 5 seconds when discriminating target versus non target. This was achieved by the use of simple averaging techniques and support vector machines. The initial results are encouraging, showing that mVEP may be used as a control system within a computer game. Details of the proposed games are also included.
http://hdl.handle.net/10759/338647
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Movement-related cortical potentials in paraplegic patients: abnormal patterns and considerations for BCI-rehabilitation.
(2014)
NASSEROLESLAMI, BAHMAN
Movement-related cortical potentials in paraplegic patients: abnormal patterns and considerations for BCI-rehabilitation.
(2014)
NASSEROLESLAMI, BAHMAN
Abstract:
Non-invasive EEG-based Brain-Computer Interfaces (BCI) can be promising for the motor neuro-rehabilitation of paraplegic patients. However, this shall require detailed knowledge of the abnormalities in the EEG signatures of paraplegic patients. The association of abnormalities in different subgroups of patients and their relation to the sensorimotor integration are relevant for the design, implementation and use of BCI systems in patient populations. This study explores the patterns of abnormalities of movement related cortical potentials (MRCP) during motor imagery tasks of feet and right hand in patients with paraplegia (including the subgroups with/without central neuropathic pain (CNP) and complete/incomplete injury patients) and the level of distinctiveness of abnormalities in these groups using pattern classification. The most notable observed abnormalities were the amplified execution negativity and its slower rebound in the patient group. The potential underlying mechanisms ...
http://hdl.handle.net/2262/74892
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The Influence of Central Neuropathic Pain in Paraplegic Patients on Performance of a Motor Imagery Based Brain Computer Interface
(2015)
Nasseroleslami, Bahman
The Influence of Central Neuropathic Pain in Paraplegic Patients on Performance of a Motor Imagery Based Brain Computer Interface
(2015)
Nasseroleslami, Bahman
Abstract:
Objective The aim of this study was to test how the presence of central neuropathic pain (CNP) influences the performance of a motor imagery based Brain Computer Interface (BCI). Methods In this electroencephalography (EEG) based study, we tested BCI classification accuracy and analysed event related desynchronisation (ERD) in 3 groups of volunteers during imagined movements of their arms and legs. The groups comprised of nine able-bodied people, ten paraplegic patients with CNP (lower abdomen and legs) and nine paraplegic patients without CNP. We tested two types of classifiers: a 3 channel bipolar montage and classifiers based on common spatial patterns (CSPs), with varying number of channels and CSPs. Results Paraplegic patients with CNP achieved higher classification accuracy and had stronger ERD than paraplegic patients with no pain for all classifier configurations. Highest 2-class classification accuracy was achieved for CSP classifier covering wider cortical area: 82 ? 7%...
http://hdl.handle.net/2262/76633
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Validation and Improvement of the Beef Production Sub-index in Ireland for Beef Cattle
(2017)
Drennan, Michael J; McGee, Michael; Clarke, Anne Marie; Kenny, David A.; Evans, R. D.; ...
Validation and Improvement of the Beef Production Sub-index in Ireland for Beef Cattle
(2017)
Drennan, Michael J; McGee, Michael; Clarke, Anne Marie; Kenny, David A.; Evans, R. D.; Berry, Donagh
Abstract:
End of Project Report
The objectives of the following study were to: a. Quantify the effect of sire genetic merit for BCI on: 1. feed intake, growth and carcass traits of progeny managed under bull or steer beef production systems. 2. live animal scores, carcass composition and plasma hormone and metabolite concentrations in their progeny. b. Compare the progeny of : 1. Late-maturing beef with dairy breeds and 2. Charolais (CH), Limousin (LM), Simmental (SM) and Belgian Blue (BB) sires bred to beef suckler dams, for feed intake, blood hormones and
http://hdl.handle.net/11019/1197
Displaying Results 1 - 8 of 8 on page 1 of 1
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Institution
Connacht-Ulster Alliance (1)
Maynooth University (1)
Teagasc (1)
Trinity College Dublin (4)
University College Cork (1)
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Conference item (3)
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Other (1)
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Peer-reviewed (5)
Non-peer-reviewed (1)
Unknown (2)
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2017 (1)
2015 (1)
2014 (2)
2013 (2)
2005 (2)
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