MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM
M., E., Elkfafi, A., Alian, S. (2006). MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM. EKB Journal Management System, 5(5th International Conference on Electrical Engineering ICEENG 2006), 1-9. doi: 10.21608/iceeng.2006.33502
Essam A., M.; A. Elkfafi; S. Alian. "MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM". EKB Journal Management System, 5, 5th International Conference on Electrical Engineering ICEENG 2006, 2006, 1-9. doi: 10.21608/iceeng.2006.33502
M., E., Elkfafi, A., Alian, S. (2006). 'MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM', EKB Journal Management System, 5(5th International Conference on Electrical Engineering ICEENG 2006), pp. 1-9. doi: 10.21608/iceeng.2006.33502
M., E., Elkfafi, A., Alian, S. MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM. EKB Journal Management System, 2006; 5(5th International Conference on Electrical Engineering ICEENG 2006): 1-9. doi: 10.21608/iceeng.2006.33502

MIDDLE LATENCY AUDUTORY EVOKED RESPONSE FOR MONITORING DEPTH OF ANESTHESIA USING FUZZY LOGIC SYSTEM

The International Conference on Electrical Engineering
Article 6, Volume 5, 5th International Conference on Electrical Engineering ICEENG 2006, May 2006, Page 1-9  XML PDF (308.68 K)
Document Type: Original Article
DOI: 10.21608/iceeng.2006.33502
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Authors
Essam A., M.1; A. Elkfafi2; S. Alian3
1Graduate student, Biomedical Department, MTC, Cairo, Egypt.
2PHD, Electronic Department, MTC, Cairo, Egypt.
3Professor, Electronic Department, Modern Academy, Cairo, Egypt.
Abstract
ABSTRACT
The depth of anesthesia is generally considered adequate if the patient neither moves in response to
surgical stimulus nor shows any signs of autonomic reflexes. So the measuring of depth of
anesthesia is very important because it helps the anesthetist to monitor the anesthetic state of the
patient from the start of giving the anesthetic drugs up to the patient awareness and helps him to
control the required amounts of the anesthetic drugs during the surgery. The middle latency
auditory evoked response (MLAER) was seemed to be the most promising measure of DOA, which
is independent of the agent being used; the monitoring of DOA is complex and dependent on many
factors, which vary between patients and operating procedures. Fuzzy set theory can be adapted for
handling complex and inexact knowledge (DOA). This paradigm seems to be suitable for medical
process, 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.
The aim of this paper is to extract significant features from the processed auditory evoked response
(AER) signal using ARX model which, describing the changes in amplitudes and latencies of
MLAER waves and merging together using fuzzy logic to create a reliable index for DOA every 30
sec.
Keywords
Middle latency auditory evoked response (MLAER); Depth of Anesthesia (DOA); autoregressive with exogenous input (ARX model); Fuzzy Logic System (FLS); and auditory evoked response (AER)
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