Anaesthesia administration during surgery is a demanding task. It requires complete knowledge\ud about the exact sleep state of the patient. However, accurate judgement of the patient’s exact state has been a\ud problem faced by anaesthesiologists for years. Till date several electroencephalogram (EEG) parameters have\ud been computed which form the index to indicate the unconsciousness of a patient. Efforts are still continuing to find out parameters with better accuracy in prediction, high repeatability & reproducibility of results and drug\ud independence. A recently discovered parameter from EEG Signal, the cumulative power spectrum (CPS) promises\ud a significant improvement over the existing parameters with higher correlation with awake and sleep state of the\ud patient. This paper focuses on the comparison of the CPS of the awake and sleep states and analyses it with respect to the frequency components in the signal.After analysis, results show that when the patient is in the awake state, the lower frequency components have high power whereas in the sleep state the lower frequency components have comparatively low power. Thus from the cumulative power spectrum plots, one is able to judge the degree of unconsciousness of the patient accurately.\ud The judgement is confirmed by comparing it with a characteristic EEG index which has unique values for the\ud awake and sleep state
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