Gait Analysis using Gravity-Center Fluctuation of the Sole at Walking based on Self-Organizing Map

被引:0
|
作者
Makino, Koji [1 ]
Nakamura, Masahiro [2 ]
Omori, Hidenori [2 ]
Terada, Hidetsugu [1 ]
机构
[1] Univ Yamanashi, Grad Sch Med & Engn, Dept Res Interdisciplinary, Takdeda 4-3-11, Kofu, Yamanashi 4008511, Japan
[2] Kofu Municipal Hosp, Kofu, Yamanashi 4000832, Japan
来源
2015 IEEE 24TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2015年
关键词
Gait motion; Self-organizing map; Rehabilitation;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
It is important to evaluate the condition of a walk in rehabilitation. In this paper, we focus on Gravity-Center Fluctuation (GCF) of the sole, and analyze the gait motion using Self-Organizing Map (SOM). First, it is clear that the shape of the GCF that is obtained by developed measurement system includes the feature of the gait motion. Secondly, the relation between the shape of GCF and the gait motion is considered by the SOM. Next, we described that the stride width and the walking velocity are predicted. Finally, it is investigated that the position where new test data is arranged on the map is according to prediction. As a consequence, it is shown that the gait motion is able to be analyzed and estimated by the method based on the SOM.
引用
收藏
页码:900 / 905
页数:6
相关论文
共 50 条
  • [21] TreeSOM: Cluster analysis in the self-organizing map
    Samsonova, Elena V.
    Kok, Joost N.
    IJzerman, Ad P.
    NEURAL NETWORKS, 2006, 19 (6-7) : 935 - 949
  • [22] The Principal Components Analysis self-organizing map
    López-Rubio, E
    Muñoz-Pérez, J
    Gómez-Ruiz, JA
    ARTIFICIAL NEURAL NETWORKS - ICANN 2002, 2002, 2415 : 865 - 870
  • [23] Analysis of DNA microarray data using self-organizing map and kernel based clustering
    Kotani, M
    Sugiyama, A
    Ozawa, S
    ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, : 755 - 759
  • [24] Study of TSP based on self-organizing map
    宋锦娟
    白艳萍
    胡红萍
    JournalofMeasurementScienceandInstrumentation, 2013, 4 (04) : 353 - 360
  • [25] Self-organizing map based on block learning
    Ohtsuka, A
    Kamiura, N
    Isokawa, T
    Matsui, N
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2005, E88A (11) : 3151 - 3160
  • [26] GPU Based Parallelism for Self-Organizing Map
    Gajdos, Petr
    Platos, Jan
    PROCEEDING OF THE THIRD INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN COMPUTER INTERACTION (IHCI 2011), 2013, 179 : 231 - 242
  • [27] Energy spectrum-based analysis of musical sounds using self-organizing map
    Masugi, M
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2003, E86D (09): : 1934 - 1938
  • [28] Homicide and Its Social Context: Analysis Using the Self-Organizing Map
    Li, Xingan
    Joutsijoki, Henry
    Laurikkala, Jorma
    Siermala, Markku
    Juhola, Martti
    APPLIED ARTIFICIAL INTELLIGENCE, 2015, 29 (04) : 382 - 401
  • [29] Traffic data analysis using kernel PCA and self-organizing map
    Chen, Yudong
    Hu, Jianming
    Zhang, Yi
    Li, Xiang
    2006 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2006, : 474 - 476
  • [30] Strategy Analysis of RoboCup Soccer Teams Using Self-Organizing Map
    Tominaga, Moeko
    Takemura, Yasunori
    Ishii, Kazuo
    ICAROB 2017: PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS, 2017, : P421 - P424