Title :
Computer assisted analysis of electromyographic data in diagnosis of low back pain
Author :
Graham, James H. ; Espinosa, Adriana
Author_Institution :
Dept. of Eng. Math. & Comput. Sci., Louisville Univ., KY, USA
Abstract :
A computerized system is presented to provide expert assistance to a physician in the evaluation of electromyographic findings in the clinical diagnosis of compressive radiculopathies. The system uses an object-oriented, frame-based representation of the nerve-root and muscular structure of the lower back and leg, and uses a rule-based reasoning system to interpret electromyographic findings and relate them to potential pathologies in the nerve roots in the lower spinal column. A novel feature of this research was the development of a hybrid system of Bayesian regulated belief functions and symbolic endorsements for the resolution of uncertainty in the clinical observations. This hybrid system provided quantitative estimates of the nerve pathologies. while simultaneously providing the physician with qualitative information regarding the interrelations of the clinical findings and the diagnosis
Keywords :
Bayes methods; bioelectric potentials; knowledge based systems; knowledge representation; medical diagnostic computing; muscle; neurophysiology; Bayesian regulated belief functions; EMG; back pain; compressive radiculopathies; electromyographic data; frame-based representation; medical diagnostic computing; muscular structure; nerve-root; rule-based reasoning; Back; Bayesian methods; Data analysis; Diagnostic expert systems; Medical diagnostic imaging; Medical expert systems; Muscles; Pain; Pathology; Uncertainty;
Conference_Titel :
Systems, Man and Cybernetics, 1989. Conference Proceedings., IEEE International Conference on
Conference_Location :
Cambridge, MA
DOI :
10.1109/ICSMC.1989.71475