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ECG contamination of EEG signals: effect on entropy

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Abstract

Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.

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Authors and Affiliations

  1. Department of Neuroanaesthesia, Neurocentre, National Institute of Mental Health and Neuro Sciences (NIMHANS), 3rd Floor, Faculty Block, Hosur Road, Bangalore, 560029, India

    Dhritiman Chakrabarti & Sonia Bansal

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  1. Dhritiman Chakrabarti
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  2. Sonia Bansal
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Correspondence to Dhritiman Chakrabarti.

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Chakrabarti, D., Bansal, S. ECG contamination of EEG signals: effect on entropy. J Clin Monit Comput 30, 119–122 (2016). https://doi.org/10.1007/s10877-015-9694-7

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  • DOI: https://doi.org/10.1007/s10877-015-9694-7

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