TY - GEN
T1 - Enhancement of Signal-to-noise Ratio of Peroneal Nerve Somatosensory Evoked Potential Using Independent Component Analysis and Time-Frequency Template
AU - Hung, C. I.
AU - Yang, Y. R.
AU - Wang, R. Y.
AU - Chou, W. L.
AU - Hsieh, J. C.
AU - Wu, Y. T.
PY - 2009
Y1 - 2009
N2 - This study aims to recover the somatosensory evoked potentials (SSEPs) from the smearing electroencephalography (EEG) recordings using independent component analysis (ICA) in conjunction with the proposed timefrequency SSEP template (TF-SSEP). The SSEPs induced from patients with the impaired motor functions exhibit longer latency and lower amplitude than the normal SSEPs and are inevitably contaminated by artifacts and environmental noise. Although ICA has been demonstrated as a novel technique to segregate the EEG into independent sources, the selection of task-related components needs to be further elaborated. The TF-SSEP template, generated by the Morelet wavelet transformation of the averaged SSEPs from three normal subjects, was used to automatically extract the SSEP-related features. The performance of the TF-SSEP template was further validated using EEGs through the left and right peroneal nerve stimulation of four stroke patients. After ICA decomposition, the sources were selected for reconstruction if their correlation coefficients with the TF-SSEP template were higher than the predetermined threshold. On the other hand, the unselected sources were considered as the event-unrelated components or artifacts. Among all patients, the topography maps at four peak times, namely P40, N45, P60 and N75, showed higher contrast in the vicinity of the foot-associated motor area, and the resolved SSEPs demonstrated uncontaminated waveforms in comparison with the conventionally averaging method. This indicated that the proposed method can remarkably suppress artifacts and effectively extracted the SSEP-related features.
AB - This study aims to recover the somatosensory evoked potentials (SSEPs) from the smearing electroencephalography (EEG) recordings using independent component analysis (ICA) in conjunction with the proposed timefrequency SSEP template (TF-SSEP). The SSEPs induced from patients with the impaired motor functions exhibit longer latency and lower amplitude than the normal SSEPs and are inevitably contaminated by artifacts and environmental noise. Although ICA has been demonstrated as a novel technique to segregate the EEG into independent sources, the selection of task-related components needs to be further elaborated. The TF-SSEP template, generated by the Morelet wavelet transformation of the averaged SSEPs from three normal subjects, was used to automatically extract the SSEP-related features. The performance of the TF-SSEP template was further validated using EEGs through the left and right peroneal nerve stimulation of four stroke patients. After ICA decomposition, the sources were selected for reconstruction if their correlation coefficients with the TF-SSEP template were higher than the predetermined threshold. On the other hand, the unselected sources were considered as the event-unrelated components or artifacts. Among all patients, the topography maps at four peak times, namely P40, N45, P60 and N75, showed higher contrast in the vicinity of the foot-associated motor area, and the resolved SSEPs demonstrated uncontaminated waveforms in comparison with the conventionally averaging method. This indicated that the proposed method can remarkably suppress artifacts and effectively extracted the SSEP-related features.
KW - Independent component analysis (ICA)
KW - Peroneal nerve
KW - Somatosensory evoked potential (SSEP)
KW - Time-frequency template
UR - http://www.scopus.com/inward/record.url?scp=84891928456&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-92841-6_176
DO - 10.1007/978-3-540-92841-6_176
M3 - Conference contribution
AN - SCOPUS:84891928456
SN - 9783540928409
T3 - IFMBE Proceedings
SP - 718
EP - 721
BT - 13th International Conference on Biomedical Engineering - ICBME 2008
T2 - 13th International Conference on Biomedical Engineering, ICBME 2008
Y2 - 3 December 2008 through 6 December 2008
ER -