Comparison of time-frequency analysis techniques in intraoperative somatosensory evoked potential (SEP) monitoring

Somatosensory evoked potentials (SEPs) can be monitored during spinal surgery to prevent possible spinal cord injury. In order to improve the reliability of SEP monitoring, an investigation of the application of various time-frequency analysis (TFA) techniques to detect both temporal and spectral changes in SEP waveforms was conducted. SEP signals from 15 scoliosis patients were analysed using various methods. The time-frequency distributions (TFDs) computed using these methods were assessed and compared. The most appropriate TFA technique may depend on the type of SEP signal, Short term Fourier transform (STFT) with a 20 point length Hanning window probably provides the best result for SEP signals.

[1]  M R Nuwer,et al.  Spinal cord monitoring with somatosensory techniques. , 1998, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[2]  R. Traystman,et al.  Anesthetic modulation of cerebral hemodynamic and evoked responses to transient middle cerebral artery occlusion in cats. , 1990, Stroke.

[3]  M. Nuwer,et al.  Intraoperative evoked potential monitoring of the spinal cord. A restricted filter, scalp method during Harrington instrumentation for scoliosis. , 1984, Clinical orthopaedics and related research.

[4]  T. Iwahara,et al.  Automated spinal cord monitoring for spinal surgery , 1989, Paraplegia.

[5]  William J. Williams,et al.  Improved time-frequency representation of multicomponent signals using exponential kernels , 1989, IEEE Trans. Acoust. Speech Signal Process..

[6]  W. Young,et al.  Somatosensory evoked potentials in rat cerebral cortex before and after middle cerebral artery occlusion. , 1990, Stroke.

[7]  S. Akselrod,et al.  Selective discrete Fourier transform algorithm for time-frequency analysis: method and application on simulated and cardiovascular signals , 1996, IEEE Transactions on Biomedical Engineering.

[8]  Shie Qian,et al.  Signal representation using adaptive normalized Gaussian functions , 1994, Signal Process..

[9]  P. Laguna,et al.  Orthonormal (Fourier and Walsh) models of time-varying evoked potentials in neurological injury , 1993, IEEE Transactions on Biomedical Engineering.

[10]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[11]  T. Yamada,et al.  Cerebral potentials evoked by rectal distention in humans. , 1993, Electroencephalography and clinical neurophysiology.

[12]  Metin Akay,et al.  Time frequency and wavelets in biomedical signal processing , 1998 .

[13]  Robert J. Marks,et al.  The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals , 1990, IEEE Trans. Acoust. Speech Signal Process..

[14]  N. Thakor,et al.  Multiresolution wavelet analysis of evoked potentials , 1993, IEEE Transactions on Biomedical Engineering.

[15]  N V Thakor,et al.  Detection of neurological injury using time-frequency analysis of the somatosensory evoked potential. , 1996, Electroencephalography and clinical neurophysiology.

[16]  J. D. Weerd,et al.  Spectro-temporal representations and time-varying spectra of evoked potentials , 1981, Biological Cybernetics.