Non-stationary feature relationship parameters for awareness monitoring

Abstract

Methods and systems are presented for determining physiological information in a physiological monitor. A physiological signal (e.g., an EEG signal) received from a subject is wavelet transformed and first and second related features that vary in scale over time are identified in the transformed signal. First and second coupled ridges of the respective first and second related features may also be identified in the transformed signal. A non-stationary relationship parameter is determined and is indicative of the relationship between the first and second features and/or between the first and second ridges. Physiological information, which may be indicative of a level of awareness of a subject, is determined based on the non-stationary relationship parameter. This physiological information may be used, for example, in an operating room to monitor/regulate the subject's anesthetic state while under general anesthesia or in an intensive care unit to monitor the subject's sedateness and administer medication accordingly.