Abstract
A fully automatic interpretation of an awake electroencephalogram (EEG) has been developed. Automatic integrative EEG interpretation consists of four main parts: quantitative EEG interpretation, EEG report making, preprocessing of EEG data, and adaptable EEG interpretation. Automatic integrative EEG interpretation reveals essentially the same findings as those of an electroencephalographer (EEGer), and is therefore applicable in clinical situations as an additional tool for the EEGer. The method has been developed through collaboration between the engineering field (Saga University) and the medical field (Kyoto University). This work can be understood as a realization of artificial intelligence. The procedure for this realization of artificial intelligence will also be applicable in other fields of systems control.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Frost JD Jr (1985) Automatic recognition and characterization of epileptiform discharges in the human EEG. J Clin Neurophysiol 2(3):231–249
Gotman J (1985) Practical use of computer-assisted EEG interpretation in epilepsy. J Clin Neurophysiol 2(3):251–265
Smith JR, Karacan I, Yang M (1978) Automatic analysis of the human sleep EEG. Waking Sleeping 2:75–82
Kowada M, Sato S, Hiraga H, et al. (1971) Automatic pattern recognition of clinical EEG: a method for waveform recognition (in Japanese). Clin Electroenceph 13:647–656
Nakamura M, Shibasaki H, Imajoh K, et al. (1992) Automatic EEG interpretation: a new computer assisted system for the automatic integrative interpretation of awake background EEG. Electroenceph Clin Neurophysiol 82:423–431
Cooley JW, Tukey JW (1965) An algorithm for the machine calculation of complex Fourier series. Math Comput 19:297–301
Ash T (1989) Dynamic node creation in back propagation networks. Connect Sci 1(4):365–375
Nakamura M, Sugi T, Ikeda A, et al. (1996) Clinical application of automatic integrative interpretation of awake background EEG: quantitative interpretation report making and detection of artifacts and reduced vigilance level. Electroenceph Clin Neurophysiol 98:103–112
Ishikawa M (1990) A structural learning algorithm with forgetting of link weights. Cognitive Science Section, Information Division, TR 90-7, pp 1–17
Nakamura M, Chen Y, Sugi T, et al. (1996) Neural network configuration for automatic EEG interpretation adaptable to individual electroencephalographer. 11th International Conference on Systems Engineering (ICSE'96), pp 31–36
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Nakamura, M., Sugi, T., Ikeda, A. et al. Realization of artificial intelligence for integrative electroencephalogram interpretation. Artificial Life and Robotics 2, 91–95 (1998). https://doi.org/10.1007/BF02471161
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF02471161