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A1121
October 15, 2007 9:00 AM - 11:00 AM Room Hall D, Area D, |
| Evaluation of a Data Adaptive Spectral Technique for Detecting Change in Physiological Monitoring |
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Ndaona Chokani, Ph.D., Werner Baulig, M.D., Reto Huber, Ph.D., Reza S. Abhari, Ph.D. ETH Zürich, ETH Zürich, Zürich, Switzerland |
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Background An assessment of the depth of anesthesia is desired to monitor the transition of a patient from/to consciousness to/from unconsciousness. Nowadays the most widely used measure of anesthetic drug effect is the Bispectral Index (BIS®) of the electroencephalographic (EEG) signals. However, particularly during cardiac surgery, the assessment of the level of consciousness is notoriously unreliable as the measurement indices have a large degree of inter-patient variability, Ref. 1. The fast Fourier transform (FFT) is used in the BIS to identify sinusoidal components and their nonlinear interactions. Indeed even in alternate measures of the level of consciousness, such as state- or response-entropies, Ref. 1, a sinusoidal oscillation character is implied. The attendant limitations of the FFT approach, including (i) the need to use windowing, (ii) the need to use ensemble averaging, (iii) the requirement of data stationarity and (iv) the limited frequency resolution, are among the reasons for the large variability observed between patients. The aim of this study was to evaluate a data adaptive spectral method for determining the level of consciousness. This data adaptive method develops a time series model from only the measured EEG data and is thus devoid of the limitations associated with the more routinely used FFT approach. Furthermore since high resolution spectra can be obtained with exceedingly short data lengths, rapidly varying cerebral activity can be detected; therefore there is the potential to develop a more accurate EEG based tool for assessing the depth of anesthesia. Methods The evaluation of the data adaptive spectral method is based on the post-operative analysis of EEG signals. Prior to the operation, the consent of the patient to participate in the study was obtained. During the operation, raw EEG signals were measured together with the BIS®; the latter was monitored using BIS® A-1000 of Aspect Medical Systems Inc., Natick MA. In addition Observer's Assessment of Alertness/Sedation (OAS) tests were performed. Results The post-operative analysis of EEG signals was used to correlate the administering and discontinuing of the anaesthetic drugs (Fentanyl, Propofol, Remifentanil), eye movement and reflex, skin incision, loss & regain of verbal contact, and answering to complex questions. While the correlation between data adaptive spectral method and BIS® is good, the correlation between the data adaptive spectral analysis and the events during operation is found to be very high, even in cases where rapid changes in the patient are occurring. Further post-operation analysis is underway, and then shall be followed by interoperation, pilot studies and subsequently clinical applications. Reference (1) Baulig, W. et al, “Monitoring level sedation during normothermic and hypothermic cardiopulmonary bypass surgery: A comparison between Bispectral Index and EEG-Entropy,” submitted to British Journal of Anaesthesia, 2007.[figure1] Anesthesiology 2007; 107: A1121 |
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