FATIGUE RECOGNITION USING EMG SIGNALS AND STOCHASTIC SWITCHED ARX MODEL

Hiroyuki Okuda, Fumio Kometani, Shinkichi Inagaki, Tatsuya Suzuki

Abstract

The man-machine cooperative system is attracting great attention in many fields, such as industry, welfare and so on. The assisting system must be designed so as to accommodate the operator’s skill, which might be strongly affected by the fatigue. This paper presents a new fatigue recognizer based on the Electro Myo-Gram (EMG) signals and the Stochastic Switched ARX (SS-ARX) model which is one of the extended model of the standard Hidden Markov Model (HMM). Since the SS-ARX model can represent complex dynamical relationship which involves switching and stochastic variance, it is expected to show higher performance as the fatigue recognizer than using simple statistical characteristics of the EMG signal and/or standard HMM. The usefulness of the proposed strategy is demonstrated by applying to a peg-in-hole task.

References

  1. D. K. Kumar, N. D. P. and Bradley, A. (2003). Wavelet analysis of surface electromyography to determine muscle fatigue.
  2. Hirana, K., Suzuki, T., and Okuma, S. (2004). Formulation and motion planning of the peg-in-hole task with mixed logical dynamical system theory.
  3. Lippold, O., Ledfean, J., and Vuco, J. (1960). The electromyography of fatigue.
  4. Rabiner, L. (1989). A tutorial on hidden markov models and selected applications in speech recognition. In Proc. of the IEEE, Vol. 77, No. 2, pp. 257-286.
  5. Ricker, S., Sarkar, N., and Rudie, K. (1996). A discreteevent systems approach to modeling dextrous manipulation.
  6. Sadoyama, T. and Miyano, H. (1981). Frequency analysis of surface emg to evaluation of muscle fatigue.
  7. Sekizawa, S., Inagaki, S., Suzuki, T., Hayakawa, S., Tsuchida, N., Tsuda, T., and Fujinami, H. (2007). Modeling and recognition of driving behavior based on stochastic switched arx model.
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Paper Citation


in Harvard Style

Okuda H., Kometani F., Inagaki S. and Suzuki T. (2009). FATIGUE RECOGNITION USING EMG SIGNALS AND STOCHASTIC SWITCHED ARX MODEL . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 202-207. DOI: 10.5220/0002205502020207


in Bibtex Style

@conference{icinco09,
author={Hiroyuki Okuda and Fumio Kometani and Shinkichi Inagaki and Tatsuya Suzuki},
title={FATIGUE RECOGNITION USING EMG SIGNALS AND STOCHASTIC SWITCHED ARX MODEL},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={202-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002205502020207},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - FATIGUE RECOGNITION USING EMG SIGNALS AND STOCHASTIC SWITCHED ARX MODEL
SN - 978-989-674-000-9
AU - Okuda H.
AU - Kometani F.
AU - Inagaki S.
AU - Suzuki T.
PY - 2009
SP - 202
EP - 207
DO - 10.5220/0002205502020207