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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2014 IEEE Healthcare Innovation Conference, HIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages288-291
Number of pages4
ISBN (Print)9781467363648
DOIs
Publication statusPublished - 2015 Feb 10
Externally publishedYes
Event2014 IEEE Healthcare Innovation Conference, HIC 2014 - Seattle, United States
Duration: 2014 Oct 82014 Oct 10

Other

Other2014 IEEE Healthcare Innovation Conference, HIC 2014
CountryUnited States
CitySeattle
Period14/10/814/10/10

Fingerprint

Fuzzy filters
Fuzzy inference
Kalman filters
Sensors
Electric fuses
Thigh
Posture
Human Body
Mean square error
Sampling

ASJC Scopus subject areas

  • Medicine(all)
  • Biomedical Engineering

Cite this

Salah, O., Ramadan, A. A., Sessa, S., Fath El-Bab, A. M. R., Abo-Ismail, A., Zecca, M., ... Fujie, M. (2015). Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter. In 2014 IEEE Healthcare Innovation Conference, HIC 2014 (pp. 288-291). [7038931] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HIC.2014.7038931

Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter. / Salah, Omar; Ramadan, Ahmed A.; Sessa, Salvatore; Fath El-Bab, Ahmed M R; Abo-Ismail, Ahmed; Zecca, M.; Kobayashi, Yo; Takanishi, Atsuo; Fujie, M.

2014 IEEE Healthcare Innovation Conference, HIC 2014. Institute of Electrical and Electronics Engineers Inc., 2015. p. 288-291 7038931.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Salah, O, Ramadan, AA, Sessa, S, Fath El-Bab, AMR, Abo-Ismail, A, Zecca, M, Kobayashi, Y, Takanishi, A & Fujie, M 2015, Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter. in 2014 IEEE Healthcare Innovation Conference, HIC 2014., 7038931, Institute of Electrical and Electronics Engineers Inc., pp. 288-291, 2014 IEEE Healthcare Innovation Conference, HIC 2014, Seattle, United States, 14/10/8. https://doi.org/10.1109/HIC.2014.7038931
Salah O, Ramadan AA, Sessa S, Fath El-Bab AMR, Abo-Ismail A, Zecca M et al. Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter. In 2014 IEEE Healthcare Innovation Conference, HIC 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 288-291. 7038931 https://doi.org/10.1109/HIC.2014.7038931
Salah, Omar ; Ramadan, Ahmed A. ; Sessa, Salvatore ; Fath El-Bab, Ahmed M R ; Abo-Ismail, Ahmed ; Zecca, M. ; Kobayashi, Yo ; Takanishi, Atsuo ; Fujie, M. / Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter. 2014 IEEE Healthcare Innovation Conference, HIC 2014. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 288-291
@inproceedings{710c117496bc4d78bd7252746f428fd7,
title = "Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter",
abstract = "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.",
author = "Omar Salah and Ramadan, {Ahmed A.} and Salvatore Sessa and {Fath El-Bab}, {Ahmed M R} and Ahmed Abo-Ismail and M. Zecca and Yo Kobayashi and Atsuo Takanishi and M. Fujie",
year = "2015",
month = "2",
day = "10",
doi = "10.1109/HIC.2014.7038931",
language = "English",
isbn = "9781467363648",
pages = "288--291",
booktitle = "2014 IEEE Healthcare Innovation Conference, HIC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Sit to stand sensing using wearable IMUs based on adaptive Neuro Fuzzy and Kalman Filter

AU - Salah, Omar

AU - Ramadan, Ahmed A.

AU - Sessa, Salvatore

AU - Fath El-Bab, Ahmed M R

AU - Abo-Ismail, Ahmed

AU - Zecca, M.

AU - Kobayashi, Yo

AU - Takanishi, Atsuo

AU - Fujie, M.

PY - 2015/2/10

Y1 - 2015/2/10

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84924325523&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924325523&partnerID=8YFLogxK

U2 - 10.1109/HIC.2014.7038931

DO - 10.1109/HIC.2014.7038931

M3 - Conference contribution

SN - 9781467363648

SP - 288

EP - 291

BT - 2014 IEEE Healthcare Innovation Conference, HIC 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -