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This study aims to determine whether the time-frequency components (TFCs) of somatosensory evoked potentials (SEPs) can be used to identify the specific location of a compressive spinal cord injury using a classification technique. Waveforms of SEPs after compressive injuries at various locations (C4, C5 and C6) in rat spinal cords were decomposed into a series of TFCs using a high-resolution time-frequency analysis method. A classification method based on support vector machine (SVM) was applied to the distributions of these TFCs among different pathological locations. The difference among injury locations manifests itself in different categories of SEP TFCs. High-energy TFCs of normal-state SEPs have significantly higher power and frequency than those of injury-state SEPs. The location of C5 is characterized by a unique distribution pattern of middle-energy TFCs. The difference between C4 and C6 is evidenced by the distribution pattern of low-energy TFCs. The proposed classification method based on SEP TFCs offers a discrimination accuracy of 80.2%. In this study, meaningful information contained in various SEP components was investigated and used to propose a new application of SEPs for identification of the location of pathological changes in the cervical spinal cord.

Component analysis of somatosensory evoked potentials for identifying spinal cord injury location