Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter

Omar Salah, Ahmed A. Ramadan, Salvatore Sessa, Ahmed M R Fath El-Bab, Ahmed Abo-Ismail, M. Zecca, Yo Kobayashi, Atsuo Takanishi, M. Fujie

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

This paper present a method for measuring the posture of a human body during different phases of sit to stand motion using inertial sensors. The proposed method fuses data from inertial sensors placed in trunk and thigh using Adaptive Neuro-Fuzzy Inference System (ANFIS) followed by a Kalman Filter (KF). The ANFIS attempts to estimate the position of shoulder of the human, at each sampling instant when measurement update step is carried out. The Kalman filter supervises the performance of the ANFIS with the aim of reducing the mismatch between the estimated and actual. The performance of the method is verified by measurements from VICON (motion analysis system). The obtained results show the effectiveness of the proposed algorithm in prediction the human shoulder position with root mean square error 0.018 m and 0.016 m in the x and y direction, respectively.

本文言語English
ホスト出版物のタイトル2014 IEEE Healthcare Innovation Conference, HIC 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ288-291
ページ数4
ISBN(印刷版)9781467363648
DOI
出版ステータスPublished - 2015 2月 10
外部発表はい
イベント2014 IEEE Healthcare Innovation Conference, HIC 2014 - Seattle, United States
継続期間: 2014 10月 82014 10月 10

Other

Other2014 IEEE Healthcare Innovation Conference, HIC 2014
国/地域United States
CitySeattle
Period14/10/814/10/10

ASJC Scopus subject areas

  • 医学(全般)
  • 生体医工学

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