Development of an expert system for multichannel EEG signal analysis

An automated computer analyzing system is designed for multichannel sleep data analysis. Sleep data are normally analyzed by a human scorer's visual inspection of the record including perception of waveforms and segment-wise classification. A knowledge-based expert system, for data interpretation and classification, is designed on top of an early-processing system in which a heuristic signal processing approach is applied to design various waveform recognizers. This is a new approach to the sleep data analysis, providing a different problem solving methodology from analytic signal processing techniques used in conventional approaches. This research also represents a new application of a knowledge-based expert system to an intensive signal processing problem which requires a processing of a large amount of data with an on-line monitoring feature. The whole idea of this approach is the simulation of the human expert's knowledge. The sleep data analyzing problem falls into the category of a knowledge-intensive heuristic problem domain where well-defined algorithms or rules do not exist, but the gestalt perception and heuristic interpretation of a human expert are applied to solve the problem. Large variability of EEG characteristics and the lack of objective EEG models add to the difficulties of analytic signal processing approaches in designing an automated computer analyzing system. The expert system technology proposes a different method for problem solving in heuristic domains such as sleep EEG analysis. It also provides a flexible and transparent research environment allowing an easy access and modification of the system knowledge in accordance with frequently varying requirements of the sleep data analysis and its clinical application areas. The developed system shows a man-machine agreement of average 83.6% with a set of randomly selected 16 sample records for subjects 5 to 79 years old. The system performance is discussed with the test result. Limitations and problems for further improvements are also discussed based on the test result.