Knowledge acquisition for multi-channel electroencephalogram interpretation

摘要

Knowledge-based systems for the automated interpretation of electrophysiological data require: (1) domain-dependent knowledge as used by, say, a cardiologist, and (2) digital signal processing knowledge. Typically, a knowledge engineer is used to encode the rules of thumb used by the domain expert, but it is more desirable that the domain expert directly enters his/her knowledge into the system. This is even more so in our application domain, where the knowledge of two experts needs to be extracted and encoded. A knowledge representation scheme and acquisition tool is presented here that makes it possible to actively involve the domain expert(s) in the encoding of the domain knowledge. The system has been evaluated on a well-defined problem taken from the area of automated EEG analysis. The results obtained indicate that the approach is especially useful in coding and handling complex spatio-temporal relationships.