Abstract
The representation of the various features of waveforms and their correlations, in EEG recording for the diagnosis of different diseases have been carried out by many researchers due to the impact of knowledge based on expert systems development tools and techniques.
The realisation of these system requires a specific hardware and software tool for its implementation, which may be a costly affair. The design and development of low cost effective system for the diagnosis of epileptic patients have benn reported in this paper. Two different and linked (at certain stage) approaches (i) decision tabel; (ii) rule based system have been followed to model the reasoning processes of physician in the diagnosis. In the decision table the features of specific waveforms of EEG are represented in the tabular form. The features are obtained from a 8086 microprocessor based data acquisition system. The rule based system is designed with IF and THEN form of rules using Turbo-Prolog as programming language tool and is implemented on low cost PC-AT. The results obtained are at an intermediate stage of data processing by decision tables and at the final stage being carried out by rule based model.
The performance of the system is evaluated by recording of EEG of some epileptic patients. The results obtained are comparable and to a certain extend appreciable in the opinion of the physician.
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References
Bass L, Broune RJ. A rule based microcomputer system for EEG evaluation. IEEE Trans Biomed Eng 1984; 31: 660–4.
Principe JC, Gala SK, Chang TG. Sleep staging automation based on theory of evidence. IEEE Trans Biomed Eng 1989; 36: 503–9.
Glover Jr JR, Ktonas PY, Jansen BH. Knowledge based interpretation of bioelectric signals. IEEE Mag Eng Med Bio 1990; 9: 51–6.
Glover R, John Jr, Raghavan N, Ktonas PY, Frost DJ. Context based automated detection of epileptic sharp transients in the EEG: Elimination of false positives. IEEE Trans Biomed Eng 1989; 36: 519–27.
Wartak J. A practical approach of decision tables. IEEE Trans Biomed Eng 1970; 17: 37–47.
Chatrian CC, Bergmin L, Dondey M, Klaro DW, Lendox Buchthal M, et al. A glassory of terms most commonly used by clinical electroencephalographer. Electroencephalogr Clin neurophysiol 1974; 37: 538–48.
Hurley BR. Decision tables in software engineering. Van Nostrand, 1983.
Mishra RB, Tripathi AN. Microprocessor based detection of epileptic discharges. Int Jl Clin Monit Comput 1991; 8: 1–11.
Mishra RB. Microcomputer augmented decision table and rule based EEG interpretation system for epileptic transients [Ph D thesis] IT-BHU (India), 1989.
Weiss S, Kulikowski CA. A practical guide to Designing Expert System. Rowman & Allanheld (NJ), 1984.
Kiloh LG, McComas AJ, Osselton JW, Upton ARV. Clinical electroenk phalography. Butterworths, 1981.
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Mishra, R.B. A decision table and rule based interpretation system for epileptic discharges. J Clin Monit Comput 9, 165–178 (1992). https://doi.org/10.1007/BF01145170
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DOI: https://doi.org/10.1007/BF01145170