MOBILE DEVICE FOR DISTINGUISHING USER'S MOVEMENT, METHOD THEREFOR, AND METHOD FOR GENERATING HIERARCHICAL TREE MODEL THEREFOR

摘要

A mobile device for distinguishing a user's movement, a method therefor, and a method for generating a hierarchical tree model therefor. Particularly, the mobile device includes: an acceleration sensor; a buffer for collecting the acceleration data outputted from the acceleration sensor according to a user's specific movement; an extraction unit for extracting the characteristic elements of the user's specific movement based on the acceleration data collected by the buffer; and a movement judgment unit for determining to which class the user's specific movement belongs by inputting the characteristic elements extracted by the extraction unit into a pre-structured hierarchical tree model, wherein the hierarchical tree model is pre-structured based on the characteristic elements extracted for each movement.

主权项

1. A mobile device for distinguishing a movement behavior of a user, comprising:
an acceleration sensor; a buffer that collects acceleration data output from the acceleration sensor according to a specific movement behavior of the user; an extraction unit that extracts and outputs a characteristic factor for the specific movement behavior of the user based on the acceleration data collected in the buffer; and a movement behavior determination unit that distinguishes to which movement behavior the specific movement behavior of the user corresponds, by inputting the characteristic factor extracted by the extraction unit into a pre-constructed hierarchical tree model, wherein the hierarchical tree model is pre-constructed based on characteristic factors extracted for each movement behavior, and the characteristic factor for each movement behavior is extracted based on a first frame group and a second frame group, and the first frame group consists of acceleration data collected separately for each movement behavior and divided based on a preset time unit, and the second frame group consists of acceleration data collected separately for each movement behavior and divided based on a time unit different from the preset time unit, and wherein part of the acceleration data of the second frame group overlaps with the first frame group.