Detection of Vasospasm in Comatose Patients Using Eeg Spectral Characteristics


  • S. Raihan Electrical & Computer Engineering, The University of Western Ontario
  • MD Sharpe Clinical Neurological Sciences, The University of Western Ontario
  • V Parsa Electrical & Computer Engineering,The University of Western Ontario
  • GB Young Clinical Neurological Sciences,The University of Western Ontario
  • HM Ladak Electrical & Computer Engineering and Medical Biophysics, The University of Western Ontario


Subarachnoid hemorrhage (SAH) is usually caused by the rupture of a brain aneurysm. Vasospasm, the constriction of cerebral vessels reducing blood flow to the brain (leading to ischemia or infarction), is a major cause of morbidity/mortality following SAH. Transcranial Doppler and computed tomography are used to detect vasospasm but cannot be used continuously. However, electroencephalography (EEG) is a sensitive indicator of brain ischemia and also can be monitored continuously.

We therefore developed a new algorithm to calculate and detect changes in quantitative EEG features such as alpha band spectral flatness ratio (SFR; ratio of geometric mean of power to the arithmetic mean of power expressed in dB), as an indicator of vasospasm.

SFR was calculated from auto-regressive model coefficients obtained using Burg’s algorithm. Discriminant analysis was used to classify vasospasm and non-vasospasm segments from the EEG. In a pilot study, classification performance was evaluated in 6 patients using the leave-one-out method. The ‘True Positive Fraction’ and ‘True Negative Fraction’ were 83% in both cases. We suggest this algorithm may be used clinically to monitor a patient’s EEG following SAH, for the early detection of vasospasm. As a result, earlier treatment of vasospasm may result in better patient outcome. 




How to Cite

S. Raihan, M. Sharpe, V. Parsa, G. Young, and H. Ladak, “Detection of Vasospasm in Comatose Patients Using Eeg Spectral Characteristics”, CMBES Proc., vol. 30, no. 1, Dec. 2007.