Y Hu1, K D K Luk, W W Lu, J C Y Leong. 1. Department of Orthopaedic Surgery, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong, ROC. yhud@hkusua.hku.hk
Abstract
OBJECTIVE: To investigate the improvement in the reliability of intraoperative spinal cord monitoring by applying time-frequency analysis to somatosensory evoked potentials (SEP). METHODS: 34 patients undergoing scoliosis surgery were studied. SEP were recorded during different stages of scoliosis surgery. Averaged SEP signals were analysed intraoperatively by short time Fourier transform (STFT). The time-frequency characteristics of SEP were observed during surgery. The main peak in the time-frequency interpretation of SEP was measured in peak time, peak frequency, and peak power. The changes in these variables were compared with the changes in latency and amplitude during different surgical stages. RESULTS: During different surgical stages, changes in peak times and peak powers were found to correlate with the changes in latency and amplitude, respectively. Peak time showed more variability than latency (p < 0.01), while peak power showed less variability than amplitude (p < 0.01). The peak frequency of SEP appeared to be unchanged during surgery. SEP signals were found to have specific time-frequency characteristics, with the time-frequency distribution of the signals being located in a particular time-frequency space. CONCLUSIONS: Time-frequency analysis of SEP waveforms reveals stable and easily identifiable characteristics. Peak power is recommended as a more reliable monitoring parameter than amplitude, while peak time monitoring was not superior to latency measurement. Applying time-frequency analysis to SEP can improve the reliability of intraoperative spinal cord monitoring.
OBJECTIVE: To investigate the improvement in the reliability of intraoperative spinal cord monitoring by applying time-frequency analysis to somatosensory evoked potentials (SEP). METHODS: 34 patients undergoing scoliosis surgery were studied. SEP were recorded during different stages of scoliosis surgery. Averaged SEP signals were analysed intraoperatively by short time Fourier transform (STFT). The time-frequency characteristics of SEP were observed during surgery. The main peak in the time-frequency interpretation of SEP was measured in peak time, peak frequency, and peak power. The changes in these variables were compared with the changes in latency and amplitude during different surgical stages. RESULTS: During different surgical stages, changes in peak times and peak powers were found to correlate with the changes in latency and amplitude, respectively. Peak time showed more variability than latency (p < 0.01), while peak power showed less variability than amplitude (p < 0.01). The peak frequency of SEP appeared to be unchanged during surgery. SEP signals were found to have specific time-frequency characteristics, with the time-frequency distribution of the signals being located in a particular time-frequency space. CONCLUSIONS: Time-frequency analysis of SEP waveforms reveals stable and easily identifiable characteristics. Peak power is recommended as a more reliable monitoring parameter than amplitude, while peak time monitoring was not superior to latency measurement. Applying time-frequency analysis to SEP can improve the reliability of intraoperative spinal cord monitoring.
Authors: Jai Madhok; Anil Maybhate; Wei Xiong; Matthew A Koenig; Romergryko G Geocadin; Xiaofeng Jia; Nitish V Thakor Journal: Crit Care Med Date: 2010-08 Impact factor: 7.598