Comparison of Features for Movement Prediction From Single-trial Movement-related Cortical Potentials in Healthy Subjects and Stroke Patients

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aut.relation.journalComputational Intelligence and Neuroscienceen_NZ
aut.relation.volume2015en_NZ
aut.researcherNiazi, Imran
dc.contributor.authorKamavuako, ENen_NZ
dc.contributor.authorJochumsen, Men_NZ
dc.contributor.authorNiazi, IKen_NZ
dc.contributor.authorDremstrup, Ken_NZ
dc.date.accessioned2017-07-26T00:23:37Z
dc.date.available2017-07-26T00:23:37Z
dc.date.copyright2015en_NZ
dc.date.issued2015en_NZ
dc.description.abstractDetection of movement intention from the movement-related cortical potential (MRCP) derived from the electroencephalogram (EEG) signals has shown to be important in combination with assistive devices for effective neurofeedback in rehabilitation. In this study, we compare time and frequency domain features to detect movement intention from EEG signals prior to movement execution. Data were recoded from 24 able-bodied subjects, 12 performing real movements, and 12 performing imaginary movements. Furthermore, six stroke patients with lower limb paresis were included. Temporal and spectral features were investigated in combination with linear discriminant analysis and compared with template matching. The results showed that spectral features were best suited for differentiating between movement intention and noise across different tasks. The ensemble average across tasks when using spectral features was (error = 3.4 ± 0.8%, sensitivity = 97.2 ± 0.9%, and specificity = 97 ± 1%) significantly better (P<0.01) than temporal features (error = 15 ± 1.4%, sensitivity: 85 ± 1.3%, and specificity: 84 ± 2%). The proposed approach also (error = 3.4 ± 0.8%) outperformed template matching (error = 26.9 ± 2.3%) significantly (P>0.001). Results imply that frequency information is important for detecting movement intention, which is promising for the application of this approach to provide patient-driven real-time neurofeedback.en_NZ
dc.identifier.citationComputational Intelligence and Neuroscience, vol. 2015, Article ID 858015, 8 pages, 2015. doi:10.1155/2015/858015
dc.identifier.doi10.1155/2015/858015en_NZ
dc.identifier.issn1687-5265en_NZ
dc.identifier.issn1687-5273en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/10686
dc.languageengen_NZ
dc.publisherHindawi Publishing Corporationen_NZ
dc.relation.urihttps://www.hindawi.com/journals/cin/2015/858015/
dc.rightsCopyright © 2015 Ernest Nlandu Kamavuako et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.accessrightsOpenAccessen_NZ
dc.titleComparison of Features for Movement Prediction From Single-trial Movement-related Cortical Potentials in Healthy Subjects and Stroke Patientsen_NZ
dc.typeJournal Article
pubs.elements-id188768
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Health & Environmental Science
pubs.organisational-data/AUT/Health & Environmental Science/Clinical Sciences
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