20. A non-transitory computer readable storage medium that stores an arousal state classifying program for classifying an arousal state of an object person, the program when executed causing a computer to perform: a blink data acquisition step acquiring blink data of at least one eye of the object person at the time of blinking; a first feature data extraction step extracting first feature data corresponding to a first pattern model generated by the arousal state classification model generating program according to claim 17 from the blink data acquired by the blink data acquisition step; a blink waveform identification step identifying a specific type of blink waveform corresponding to the first feature data extracted in the first feature data extraction step based on the first feature data and the first pattern model; a second feature data generation step generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms based on an identification result by the blink waveform identification step with respect to the blink data of the object person acquired in a sequence of analysis intervals; and an arousal state classification step classifying the arousal state of the object person based on the second feature data generated in the second feature data generation step and a second pattern model generated by the arousal state classification model generating program.
20. A non-transitory computer readable storage medium that stores an arousal state classifying program for classifying an arousal state of an object person, the program when executed causing a computer to perform: a blink data acquisition step acquiring blink data of at least one eye of the object person at the time of blinking; a first feature data extraction step extracting first feature data corresponding to a first pattern model generated by the arousal state classification model generating program according to claim 17 from the blink data acquired by the blink data acquisition step; a blink waveform identification step identifying a specific type of blink waveform corresponding to the first feature data extracted in the first feature data extraction step based on the first feature data and the first pattern model; a second feature data generation step generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms based on an identification result by the blink waveform identification step with respect to the blink data of the object person acquired in a sequence of analysis intervals; and an arousal state classification step classifying the arousal state of the object person based on the second feature data generated in the second feature data generation step and a second pattern model generated by the arousal state classification model generating program. 21. The non-transitory computer readable storage medium according to claim 20 , wherein the data on the occurrence ratio is a time variation of the occurrence ratio or a time variation of the number of occurrences.