Multi-Valued Decision Making for Transitional Stochastic Event: Determination of Sleep Stages Through EEG Record

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of knowledge database which included experts'knowledge and experience. The proposed multi-valued decision making was successfully adopted to the determination of the five levels of the vigilance of a subject during the EEG (electroencephalogram) recording; awake stage (stage W), and sleep stages (stage REM (rapid eye movement), stage 1, stage 2, stage $\sfrac{3}{4}$). Innovative feature of the proposed method is that the algorithm of decision making can be constructed only by use of the knowledge database, inspected by experts. The proposed multi-valued decision making with a mathematical background of the probability can also be applicable widely, in industries and in other medical fields for purposes of the multi-valued decision making.