Finding Major Patterns of Aging Process by Data Synchronization

Abstract

We developed a method for extracting feature patterns from multivariate data using a network of coupled phase oscillators subject to an analogue of the Kuramoto model for collective synchronization. Our method may be called data synchronization. We applied data synchronization to the care-needs-certification data, provided by Otsu City as a historical old city near Kyoto City, in the Japanese public long-term care insurance program to find the trend of the major patterns of the aging process for elderly people needing nursing care.