Monitoring Depth of Anaesthesia using Fuzzy Logic System | ||||
| International Conference on Aerospace Sciences and Aviation Technology | ||||
| Article 61, Volume 10, 10th International Conference On Aerospace Sciences & Aviation Technology, May 2003, Page 907-921 PDF (1.67 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asat.2013.24710 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| M. A. Elkfafi | ||||
| Egyptian Armed Forces. | ||||
| Abstract | ||||
| The depth of anaesthesia (DOA) achieved is a result of the concentration of the anaesthetic drugs in the brain. Until recent years, there has been no simple, accurate and objective method for assessing the DOA or alerting the anaesthetist to a state of awareness. The monitoring of DOA is complex, and dependent on many factors, which vary between patients and operating procedures. A method that can be adapted for handling complex and inexact knowledge (e.g. DOA) within a computer program is fuzzy set theory. This paradigm seems to be specially suitable for medical processes, since it depends upon expert experiences which are not precisely quantifiable, such as patients' subjective sensations, interpretation of clinical signs and effects of instrumental accuracy. In this paper, two significant extracted features from the processed auditory evoked response (AER) signal, describing the changes in amplitudes and latencies of MLAER waves, have been merged together using fuzzy logic to create a reliable index for DOA every 30 seconds. | ||||
| Keywords | ||||
| Depth of Anaesthesia (DOA); Mid Latency Auditory Evoked Response (MLAER); Evoked Potential (EP); Fuzzy Logic System (FLS); Averaged Phase of MLAER signal in S - domain (Ph); Averaged Magnitude of MLAER signal in S - domain (Mag); Feature Extraction (FE); Fuzzy Logic Modeling (FLM); Digital Signal Processing (DSP); Auditory Evoked Response (AER) | ||||
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