The present invention provides a new sleep analysis technique with which sleep analysis with relatively high reliability can be simply and speedily performed by using sleeping depth data. An appearance ratio conversion processing portion reads sleeping depth data (qualitative variable) stored in a RAM to calculate a movement appearance ratio n-M.A.R. (quantitative variable) meeting a relation of sleeping depth=2 (deep sleep: SWS). Then, an evaluation result calculation processing portion reads the calculated movement appearance ratio data (quantitative variable) from the RAM, and processes the calculated movement appearance ratio data in accordance with an evaluation rule in an evaluation rule storage portion to calculate an evaluation score for the evaluation factor concerned. When the evaluation factor is 'rapidity of falling asleep' for example, a time period from a point when a person goes to bed to a point when the movement appearance ratio n-M.A.R. of the SWS rises is detected from the movement appearance ratio n-M.A.R. of the SWS. Then, an evaluation score corresponding to a length of a time period of the rising is acquired from a corresponding score table. According to the present invention, the sleeping depth data expressed as the qualitative variable is converted into the data related to the appearance ratio of the sleeping depth and expressed as the quantitative variable, and the evaluation factors are analyzed and evaluated using the data after the conversion. Thus, various evaluation factors such as 'rhythm of sleep', 'mental recovery', 'physical recovery' and 'rapidity of falling asleep' can be quantitatively evaluated. As a result, simplification for the processing can be realized and at the same time, highly reliable sleep analysis results can be provided.
Sleep analyzer and program product for giving sleep analysis function to computer