Analysis of touching motion using singular spectrum transformation

Author

Fujii, Eri ; Katsura, Seiichiro

Author_Institution

Dept. of Syst. Design Eng., Keio Univ., Yokohama, Japan

fYear

2015

fDate

6-8 March 2015

Firstpage

464

Lastpage

469

Abstract

Recently, robots have been increasing demand for elderly care problem, dangerous work involved in life, disappearing skilled work and so on. To use robots like human, human motion information is needed to obtain. The motion information is also needed to analyze in order to use effectively information. In this paper, motion information is extracted by motion-copying system. Motion-copying system is suitable for obtained touching motion. To analyze motion information, Singular Spectrum Transformation (SST) is introduced. SST is one of the most adaptive data mining techniques to analyze time-series data. Motion information has various parameters in time-series data. This mining system has probability to use for motion segmentation and classification. According to the experiments and the analysis, touching motion can be analyzed.

Keywords

control engineering computing; data analysis; data mining; geriatrics; medical computing; medical robotics; motion control; patient care; time series; SST; data mining techniques; elderly care; human motion information; motion classification; motion segmentation; motion-copying system; robots; singular spectrum transformation; time-series data analysis; touching motion analysis; Acceleration; Data mining; Force; Frequency modulation; Matrix decomposition; Robots; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics (ICM), 2015 IEEE International Conference on

Conference_Location

Nagoya

Type

conf

DOI

10.1109/ICMECH.2015.7084021

Filename

7084021