EMG based design and evaluation of micro macro neural network for rollover support trunk orthosis

Takeshi Ando; Jun Okamoto; Mitsuru Takahashi; Masakatsu G. Fujie

doi:10.1109/ROBOT.2010.5509868

EMG based design and evaluation of micro macro neural network for rollover support trunk orthosis

Takeshi Ando^*, Jun Okamoto, Mitsuru Takahashi, Masakatsu G. Fujie

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

An EMG controlled intelligent orthosis was developed to support the rollover movement of cancer bone metastasis patients. In this paper, the validation of the developed signal processing algorithm to recognize the rollover was focused. Firstly, the ElectroMechanicalDelay of the internal oblique muscle was measured as the about 65 (msec). Secondly, it was confirmed that the rollover movement was recognized about 65 (msec) before the movement started. Therefore, the developed Micro Macro Neural Network (MMNN) recognized the rollover movement using the EMG signal as quick as possible. Finally, the robustness of the developed MMNN was discussed by conducting the experiment to discriminate between the rollover and turning out. We proposed and developed the original algorithm in which the logical XOR operation was added to the MMNN, because the MMNN which learned the characteristics of the only rollover recognized the turning out movement as the rollover movement perfectly. When the proposed algorithm that combined the MMNN and XOR operator was used, the rollover and turning out movements were discriminated 83%.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Robotics and Automation
Pages	2916-2921
Number of pages	6
DOIs	https://doi.org/10.1109/ROBOT.2010.5509868
Publication status	Published - 2010
Event	2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK Duration: 2010 May 3 → 2010 May 7

Other

Other	2010 IEEE International Conference on Robotics and Automation, ICRA 2010
City	Anchorage, AK
Period	10/5/3 → 10/5/7

ASJC Scopus subject areas

Software
Artificial Intelligence
Control and Systems Engineering
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ROBOT.2010.5509868

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Ando, T, Okamoto, J, Takahashi, M & Fujie, MG 2010, EMG based design and evaluation of micro macro neural network for rollover support trunk orthosis. in Proceedings - IEEE International Conference on Robotics and Automation., 5509868, pp. 2916-2921, 2010 IEEE International Conference on Robotics and Automation, ICRA 2010, Anchorage, AK, 10/5/3. https://doi.org/10.1109/ROBOT.2010.5509868

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title = "EMG based design and evaluation of micro macro neural network for rollover support trunk orthosis",

abstract = "An EMG controlled intelligent orthosis was developed to support the rollover movement of cancer bone metastasis patients. In this paper, the validation of the developed signal processing algorithm to recognize the rollover was focused. Firstly, the ElectroMechanicalDelay of the internal oblique muscle was measured as the about 65 (msec). Secondly, it was confirmed that the rollover movement was recognized about 65 (msec) before the movement started. Therefore, the developed Micro Macro Neural Network (MMNN) recognized the rollover movement using the EMG signal as quick as possible. Finally, the robustness of the developed MMNN was discussed by conducting the experiment to discriminate between the rollover and turning out. We proposed and developed the original algorithm in which the logical XOR operation was added to the MMNN, because the MMNN which learned the characteristics of the only rollover recognized the turning out movement as the rollover movement perfectly. When the proposed algorithm that combined the MMNN and XOR operator was used, the rollover and turning out movements were discriminated 83%.",

author = "Takeshi Ando and Jun Okamoto and Mitsuru Takahashi and Fujie, {Masakatsu G.}",

year = "2010",

doi = "10.1109/ROBOT.2010.5509868",

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AU - Ando, Takeshi

AU - Okamoto, Jun

AU - Takahashi, Mitsuru

AU - Fujie, Masakatsu G.

PY - 2010

Y1 - 2010

N2 - An EMG controlled intelligent orthosis was developed to support the rollover movement of cancer bone metastasis patients. In this paper, the validation of the developed signal processing algorithm to recognize the rollover was focused. Firstly, the ElectroMechanicalDelay of the internal oblique muscle was measured as the about 65 (msec). Secondly, it was confirmed that the rollover movement was recognized about 65 (msec) before the movement started. Therefore, the developed Micro Macro Neural Network (MMNN) recognized the rollover movement using the EMG signal as quick as possible. Finally, the robustness of the developed MMNN was discussed by conducting the experiment to discriminate between the rollover and turning out. We proposed and developed the original algorithm in which the logical XOR operation was added to the MMNN, because the MMNN which learned the characteristics of the only rollover recognized the turning out movement as the rollover movement perfectly. When the proposed algorithm that combined the MMNN and XOR operator was used, the rollover and turning out movements were discriminated 83%.

AB - An EMG controlled intelligent orthosis was developed to support the rollover movement of cancer bone metastasis patients. In this paper, the validation of the developed signal processing algorithm to recognize the rollover was focused. Firstly, the ElectroMechanicalDelay of the internal oblique muscle was measured as the about 65 (msec). Secondly, it was confirmed that the rollover movement was recognized about 65 (msec) before the movement started. Therefore, the developed Micro Macro Neural Network (MMNN) recognized the rollover movement using the EMG signal as quick as possible. Finally, the robustness of the developed MMNN was discussed by conducting the experiment to discriminate between the rollover and turning out. We proposed and developed the original algorithm in which the logical XOR operation was added to the MMNN, because the MMNN which learned the characteristics of the only rollover recognized the turning out movement as the rollover movement perfectly. When the proposed algorithm that combined the MMNN and XOR operator was used, the rollover and turning out movements were discriminated 83%.

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ER -

EMG based design and evaluation of micro macro neural network for rollover support trunk orthosis

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UN SDGs

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