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Recently, attention is paid to monitoring systems that watch behavior of a solitude person in home as the population of solitude seniors has increased. This paper proposes a monitoring system focused on behavioral patterns of a solitude senior. In general, the number of behavioral patterns are limited in the case of aged person in a room. It is possible for a system like a HMM to learn the frequently appeared behavioral patterns. By utilizing HMMs to deal with behavioral patterns, the system can detect irregular pattern by the degree of likelihood in the case when non-daily behavioral patterns appeared. Such a case could be an irregular state of the living life of the person. Soon after, the system reports an alarm of occurrence of the irregular state according to demand.

Detection of a Solitude Senior's Irregular States Based on Learning and Recognizing of Behavioral Patterns