Abstract: An abnormality detection device includes small motion sensors that detect small motions of a person in a house; a data collecting unit that collects and stores sensor signals from the small motion sensors as sensor patterns, and a Markov chain operating unit 33 that transforms the sensor patterns into a cluster sequence by vector-quantizing input patterns which are obtained by averaging and normalizing the sensor patterns, and calculates a transition number matrix and a duration time distribution of a Markov and so on using a Markov chain model. The abnormality detection device also includes a comparing unit that calculates a characteristic amount (Euclid distance and average log likelihood in an appearance frequency of a Markov chain and an average log likelihood to the duration time distribution of a Markov chain) of a sample activity as against a daily activity based on the obtained transition number matrix and the duration time distribution and so on.

Abstract: An abnormality detection device 30 includes small motion sensors 25a˜25c that detect small motions of a person in a house, a data collecting unit 32 that collects and stores sensor signals from the small motion sensors 25a˜25c as sensor patterns, a Markov chain operating unit 33 that transforms the sensor patterns into a cluster sequence by vector-quantizing input patterns which are obtained by averaging and normalizing the sensor patterns and calculates a transition number matrix and a duration time distribution of a Markov chain and so on using a Markov chain model, a comparing unit 34 that calculates characteristic amount (Euclid distance and average log likelihood in appearance frequency of a Markov chain and average log likelihood to the duration time distribution of a Markov chain) of a sample activity as against a daily activity based on the obtained transition number matrix and the duration time distribution and so on, and others.