A set of EEG parameters to predict clinically anaesthetized state in humans for halothane anaesthesia

Journal of Medical Engineering and Technology

Volumn 31, Issue 1, 2007, Pages 46-53

  Kumar, A ^a   Anand, S ^b   Chari, P ^c   Yaddanapudi, L N ^c   Srivastava, A ^b  

^a Biomedical Division   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^c POSTGRADUATE INSTITUTE OF MEDICAL EDUCATION AND RESEARCH   (India)

Author keywords

Artificial neural network; Depth of anaesthesia; EEG; Stepwise discriminant analysis; Variance analysis

Indexed keywords

COMPUTATIONAL COMPLEXITY; CONVERGENCE OF NUMERICAL METHODS; DRUG DOSAGE; NEURAL NETWORKS; PARAMETER ESTIMATION; PATIENT TREATMENT;

DEPTH OF ANAESTHESIA; STEPWISE DISCRIMINANT ANALYSIS; VARIANCE ANALYSIS;

ELECTROENCEPHALOGRAPHY;

HALOTHANE;

ACCURACY; ADULT; ANALYSIS; ANESTHESIA; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLINICAL ARTICLE; ELECTROENCEPHALOGRAM; ENTROPY; HUMAN; PATIENT CODING; STEPWISE DISCRIMINANT ANALYSIS; WAKEFULNESS;

ADULT; ANESTHESIA; ANESTHETICS, INHALATION; ELECTROENCEPHALOGRAPHY; HALOTHANE; HUMANS; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); SLEEP; WAKEFULNESS;

EID: 33847042218     PISSN: 03091902     EISSN: 1464522X     Source Type: Journal    
DOI: 10.1080/03091900500431874     Document Type: Article

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