Fractal dimension of Electroencephalogram for assessment of hypnosis state of patient during anaesthesia

Sanjeev Kumar, Amod Kumar, Satinder Gombar, Anjan Trikha, Sneh Anand

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4 Scopus citations


Depth of Anaesthesia (DoA) measurement and control is a demanding task that must be done to avoid intraoperative awareness and explicit recall of pain during surgery. Conventional methods of assessing DoA involve monitoring of physiological parameters, which are not found reliable, as patient awareness during surgery with anaesthetic agents has been reported. Electroencephalogram (EEG) is found to be a reliable means to determine the real anaesthetic state of a patient during surgery. Balanced anaesthesia is the fusion of four different components: hypnosis, analgesia, amnesia and neuromuscular blockade. The accurate control of anaesthesia is possible only with the accurate assessment of the different components of anaesthesia. The major component of balanced anaesthesia is hypnosis, which gives the level of unconsciousness of the patient during surgery. In the present study, efforts were made to calculate and validate an EEG-based parameter which is able to predict the awake and anaesthetic sleep state of the patient. In the present study, the EEG of 60 patients were recorded during normal awake state and while under anaesthesia. Analysis of the EEG signals was performed by non-linear quantifi ers. Higuchi's Fractal Dimension (HFD) has been calculated for this recorded EEG waveform for all patients in both states. It was found that HFD is able to predict the awake/sleep state of the patient quite accurately. Validation of the study was done by monitoring BIS in parallel and concluded that the HFD of the EEG goes down as the patient moves into deep hypnosis state.

Original languageEnglish (US)
Pages (from-to)30-37
Number of pages8
JournalInternational Journal of Biomedical Engineering and Technology
Issue number1
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

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