Abstract: A time series data analyzer includes a segment condition input section, an analysis condition input section, and an optimum condition deriving section for analyzing all segments based on the segment conditions and analysis conditions inputted in the respective input sections, under all analysis conditions by a maximum entropy method and a nonlinear least squares method. The time series data analyzer derives the optimum segment length and the optimum lag value in correspondence to selected results, and an analysis execution section executes analysis by the maximum entropy method by setting the optimum analysis conditions derived as described above. The trending of the spectrum of electroencephalogram data is used as an indicator of the state of the subject based on the findings that the spectrum of electroencephalogram data is an exponential spectrum and the gradient changes depending on the state of the subject.

Abstract: The inventor had proposed to use the value of the overall trend of the spectrum of electroencephalogram data as an indicator of the state of the subject on the basis of the findings that the spectrum of electroencephalogram data is an exponential spectrum and that the gradient changes depending on the state of the subject, but the respective states of a subject could not be identified by referring to the value of the gradient only.