Position sensing and control with FMG sensors for exoskeleton physical assistance

Muhammad R.U. Islam; Kun Xu; Shaoping Bai

doi:10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance

Muhammad R.U. Islam^*, Kun Xu, Shaoping Bai

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

4 Citations (Scopus)

Abstract

Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

Original language	English
Title of host publication	Wearable Robotics: Challenges and Trends : Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018
Editors	Maria Chiara Carrozza, Silvestro Micera, Jóse L. Pons
Number of pages	5
Publisher	Springer Publishing Company
Publication date	2019
Pages	3-7
ISBN (Print)	978-3-030-01886-3
ISBN (Electronic)	978-3-030-01887-0
DOIs	https://doi.org/10.1007/978-3-030-01887-0_1
Publication status	Published - 2019

Series	Biosystems and Biorobotics
Volume	22
ISSN	2195-3562

Bibliographical note

Funding Information:
Acknowledgment. The reported work is partially supported by EU-AAL Joint Programme through project AXO-SUIT and Innovation Fund Denmark through project EXO-AIDER.

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

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Islam, M. R. U., Xu, K., & Bai, S. (2019). Position sensing and control with FMG sensors for exoskeleton physical assistance. In M. C. Carrozza, S. Micera, & J. L. Pons (Eds.), Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018 (pp. 3-7). Springer Publishing Company. https://doi.org/10.1007/978-3-030-01887-0_1

Islam, Muhammad R.U. ; Xu, Kun ; Bai, Shaoping. / Position sensing and control with FMG sensors for exoskeleton physical assistance. Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. editor / Maria Chiara Carrozza ; Silvestro Micera ; Jóse L. Pons. Springer Publishing Company, 2019. pp. 3-7 (Biosystems and Biorobotics, Vol. 22).

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title = "Position sensing and control with FMG sensors for exoskeleton physical assistance",

abstract = "Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.",

author = "Islam, {Muhammad R.U.} and Kun Xu and Shaoping Bai",

note = "Funding Information: Acknowledgment. The reported work is partially supported by EU-AAL Joint Programme through project AXO-SUIT and Innovation Fund Denmark through project EXO-AIDER. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.",

year = "2019",

doi = "10.1007/978-3-030-01887-0_1",

language = "English",

isbn = "978-3-030-01886-3",

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publisher = "Springer Publishing Company",

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editor = "Carrozza, {Maria Chiara} and Silvestro Micera and Pons, {J{\'o}se L.}",

booktitle = "Wearable Robotics: Challenges and Trends",

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}

Islam, MRU, Xu, K & Bai, S 2019, Position sensing and control with FMG sensors for exoskeleton physical assistance. in MC Carrozza, S Micera & JL Pons (eds), Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. Springer Publishing Company, Biosystems and Biorobotics, vol. 22, pp. 3-7. https://doi.org/10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance. / Islam, Muhammad R.U.; Xu, Kun; Bai, Shaoping.
Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. ed. / Maria Chiara Carrozza; Silvestro Micera; Jóse L. Pons. Springer Publishing Company, 2019. p. 3-7 (Biosystems and Biorobotics, Vol. 22).

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

TY - CHAP

T1 - Position sensing and control with FMG sensors for exoskeleton physical assistance

AU - Islam, Muhammad R.U.

AU - Xu, Kun

AU - Bai, Shaoping

N1 - Funding Information: Acknowledgment. The reported work is partially supported by EU-AAL Joint Programme through project AXO-SUIT and Innovation Fund Denmark through project EXO-AIDER. Publisher Copyright: © Springer Nature Switzerland AG 2019. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2019

Y1 - 2019

N2 - Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

AB - Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

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U2 - 10.1007/978-3-030-01887-0_1

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AN - SCOPUS:85055050357

SN - 978-3-030-01886-3

T3 - Biosystems and Biorobotics

SP - 3

EP - 7

BT - Wearable Robotics: Challenges and Trends

A2 - Carrozza, Maria Chiara

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Islam MRU, Xu K, Bai S. Position sensing and control with FMG sensors for exoskeleton physical assistance. In Carrozza MC, Micera S, Pons JL, editors, Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. Springer Publishing Company. 2019. p. 3-7. (Biosystems and Biorobotics, Vol. 22). doi: 10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance

Abstract

Bibliographical note

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FMG based upper limb motion detection methods, performance analysis and control of assistive exoskeletons

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