Infantile unhealthy lifestyle increases the risk of their adult diseases and cost of medical care in their future. If children life-log is measured and their physical condition can be analyzed, it is expected that such information can be utilized for prevention of adult diseases and for the health-promoting. Therefore, activity recognition for children is treated in the present paper. Feature points for activity recognition are computed from accelerations which are measured by a 3-axis acceleration sensor attached to child's upper-arm. Two-phased classification was performed by using Self-Organizing Map. As a result, it was confirmed that the classification accuracy was 65.92[%].
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